how to write a qualitative research hypothesis

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

Step 1. Ask a question

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved April 5, 2024, from https://www.scribbr.com/methodology/hypothesis/

Is this article helpful?

Shona McCombes

Other students also liked, construct validity | definition, types, & examples, what is a conceptual framework | tips & examples, operationalization | a guide with examples, pros & cons, what is your plagiarism score.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• How to Write a Strong Hypothesis | Guide & Examples

How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

Prevent plagiarism, run a free check.

Step 1: ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2: Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise more complex constructs.

Step 3: Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

Step 4: Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

Step 5: Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

Step 6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis. The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2022, May 06). How to Write a Strong Hypothesis | Guide & Examples. Scribbr. Retrieved 2 April 2024, from https://www.scribbr.co.uk/research-methods/hypothesis-writing/

Is this article helpful?

Shona McCombes

Other students also liked, operationalisation | a guide with examples, pros & cons, what is a conceptual framework | tips & examples, a quick guide to experimental design | 5 steps & examples.

How to Write a Hypothesis: A Step-by-Step Guide

Introduction

An overview of the research hypothesis, different types of hypotheses, variables in a hypothesis, how to formulate an effective research hypothesis, designing a study around your hypothesis.

The scientific method can derive and test predictions as hypotheses. Empirical research can then provide support (or lack thereof) for the hypotheses. Even failure to find support for a hypothesis still represents a valuable contribution to scientific knowledge. Let's look more closely at the idea of the hypothesis and the role it plays in research.

As much as the term exists in everyday language, there is a detailed development that informs the word "hypothesis" when applied to research. A good research hypothesis is informed by prior research and guides research design and data analysis , so it is important to understand how a hypothesis is defined and understood by researchers.

What is the simple definition of a hypothesis?

A hypothesis is a testable prediction about an outcome between two or more variables . It functions as a navigational tool in the research process, directing what you aim to predict and how.

What is the hypothesis for in research?

In research, a hypothesis serves as the cornerstone for your empirical study. It not only lays out what you aim to investigate but also provides a structured approach for your data collection and analysis.

Essentially, it bridges the gap between the theoretical and the empirical, guiding your investigation throughout its course.

What is an example of a hypothesis?

If you are studying the relationship between physical exercise and mental health, a suitable hypothesis could be: "Regular physical exercise leads to improved mental well-being among adults."

This statement constitutes a specific and testable hypothesis that directly relates to the variables you are investigating.

What makes a good hypothesis?

A good hypothesis possesses several key characteristics. Firstly, it must be testable, allowing you to analyze data through empirical means, such as observation or experimentation, to assess if there is significant support for the hypothesis. Secondly, a hypothesis should be specific and unambiguous, giving a clear understanding of the expected relationship between variables. Lastly, it should be grounded in existing research or theoretical frameworks , ensuring its relevance and applicability.

Understanding the types of hypotheses can greatly enhance how you construct and work with hypotheses. While all hypotheses serve the essential function of guiding your study, there are varying purposes among the types of hypotheses. In addition, all hypotheses stand in contrast to the null hypothesis, or the assumption that there is no significant relationship between the variables .

Here, we explore various kinds of hypotheses to provide you with the tools needed to craft effective hypotheses for your specific research needs. Bear in mind that many of these hypothesis types may overlap with one another, and the specific type that is typically used will likely depend on the area of research and methodology you are following.

Null hypothesis

The null hypothesis is a statement that there is no effect or relationship between the variables being studied. In statistical terms, it serves as the default assumption that any observed differences are due to random chance.

For example, if you're studying the effect of a drug on blood pressure, the null hypothesis might state that the drug has no effect.

Alternative hypothesis

Contrary to the null hypothesis, the alternative hypothesis suggests that there is a significant relationship or effect between variables.

Using the drug example, the alternative hypothesis would posit that the drug does indeed affect blood pressure. This is what researchers aim to prove.

Simple hypothesis

A simple hypothesis makes a prediction about the relationship between two variables, and only two variables.

For example, "Increased study time results in better exam scores." Here, "study time" and "exam scores" are the only variables involved.

Complex hypothesis

A complex hypothesis, as the name suggests, involves more than two variables. For instance, "Increased study time and access to resources result in better exam scores." Here, "study time," "access to resources," and "exam scores" are all variables.

This hypothesis refers to multiple potential mediating variables. Other hypotheses could also include predictions about variables that moderate the relationship between the independent variable and dependent variable .

Directional hypothesis

A directional hypothesis specifies the direction of the expected relationship between variables. For example, "Eating more fruits and vegetables leads to a decrease in heart disease."

Here, the direction of heart disease is explicitly predicted to decrease, due to effects from eating more fruits and vegetables. All hypotheses typically specify the expected direction of the relationship between the independent and dependent variable, such that researchers can test if this prediction holds in their data analysis .

Statistical hypothesis

A statistical hypothesis is one that is testable through statistical methods, providing a numerical value that can be analyzed. This is commonly seen in quantitative research .

For example, "There is a statistically significant difference in test scores between students who study for one hour and those who study for two."

Empirical hypothesis

An empirical hypothesis is derived from observations and is tested through empirical methods, often through experimentation or survey data . Empirical hypotheses may also be assessed with statistical analyses.

For example, "Regular exercise is correlated with a lower incidence of depression," could be tested through surveys that measure exercise frequency and depression levels.

Causal hypothesis

A causal hypothesis proposes that one variable causes a change in another. This type of hypothesis is often tested through controlled experiments.

For example, "Smoking causes lung cancer," assumes a direct causal relationship.

Associative hypothesis

Unlike causal hypotheses, associative hypotheses suggest a relationship between variables but do not imply causation.

For instance, "People who smoke are more likely to get lung cancer," notes an association but doesn't claim that smoking causes lung cancer directly.

Relational hypothesis

A relational hypothesis explores the relationship between two or more variables but doesn't specify the nature of the relationship.

For example, "There is a relationship between diet and heart health," leaves the nature of the relationship (causal, associative, etc.) open to interpretation.

Logical hypothesis

A logical hypothesis is based on sound reasoning and logical principles. It's often used in theoretical research to explore abstract concepts, rather than being based on empirical data.

For example, "If all men are mortal and Socrates is a man, then Socrates is mortal," employs logical reasoning to make its point.

Let ATLAS.ti take you from research question to key insights

Get started with a free trial and see how ATLAS.ti can make the most of your data.

In any research hypothesis, variables play a critical role. These are the elements or factors that the researcher manipulates, controls, or measures. Understanding variables is essential for crafting a clear, testable hypothesis and for the stages of research that follow, such as data collection and analysis.

In the realm of hypotheses, there are generally two types of variables to consider: independent and dependent. Independent variables are what you, as the researcher, manipulate or change in your study. It's considered the cause in the relationship you're investigating. For instance, in a study examining the impact of sleep duration on academic performance, the independent variable would be the amount of sleep participants get.

Conversely, the dependent variable is the outcome you measure to gauge the effect of your manipulation. It's the effect in the cause-and-effect relationship. The dependent variable thus refers to the main outcome of interest in your study. In the same sleep study example, the academic performance, perhaps measured by exam scores or GPA, would be the dependent variable.

Beyond these two primary types, you might also encounter control variables. These are variables that could potentially influence the outcome and are therefore kept constant to isolate the relationship between the independent and dependent variables . For example, in the sleep and academic performance study, control variables could include age, diet, or even the subject of study.

By clearly identifying and understanding the roles of these variables in your hypothesis, you set the stage for a methodologically sound research project. It helps you develop focused research questions, design appropriate experiments or observations, and carry out meaningful data analysis . It's a step that lays the groundwork for the success of your entire study.

Crafting a strong, testable hypothesis is crucial for the success of any research project. It sets the stage for everything from your study design to data collection and analysis . Below are some key considerations to keep in mind when formulating your hypothesis:

• Be specific : A vague hypothesis can lead to ambiguous results and interpretations . Clearly define your variables and the expected relationship between them.
• Ensure testability : A good hypothesis should be testable through empirical means, whether by observation , experimentation, or other forms of data analysis.
• Ground in literature : Before creating your hypothesis, consult existing research and theories. This not only helps you identify gaps in current knowledge but also gives you valuable context and credibility for crafting your hypothesis.
• Use simple language : While your hypothesis should be conceptually sound, it doesn't have to be complicated. Aim for clarity and simplicity in your wording.
• State direction, if applicable : If your hypothesis involves a directional outcome (e.g., "increase" or "decrease"), make sure to specify this. You also need to think about how you will measure whether or not the outcome moved in the direction you predicted.
• Keep it focused : One of the common pitfalls in hypothesis formulation is trying to answer too many questions at once. Keep your hypothesis focused on a specific issue or relationship.
• Account for control variables : Identify any variables that could potentially impact the outcome and consider how you will control for them in your study.
• Be ethical : Make sure your hypothesis and the methods for testing it comply with ethical standards , particularly if your research involves human or animal subjects.

Designing your study involves multiple key phases that help ensure the rigor and validity of your research. Here we discuss these crucial components in more detail.

Literature review

Starting with a comprehensive literature review is essential. This step allows you to understand the existing body of knowledge related to your hypothesis and helps you identify gaps that your research could fill. Your research should aim to contribute some novel understanding to existing literature, and your hypotheses can reflect this. A literature review also provides valuable insights into how similar research projects were executed, thereby helping you fine-tune your own approach.

Research methods

Choosing the right research methods is critical. Whether it's a survey, an experiment, or observational study, the methodology should be the most appropriate for testing your hypothesis. Your choice of methods will also depend on whether your research is quantitative, qualitative, or mixed-methods. Make sure the chosen methods align well with the variables you are studying and the type of data you need.

Preliminary research

Before diving into a full-scale study, it’s often beneficial to conduct preliminary research or a pilot study . This allows you to test your research methods on a smaller scale, refine your tools, and identify any potential issues. For instance, a pilot survey can help you determine if your questions are clear and if the survey effectively captures the data you need. This step can save you both time and resources in the long run.

Data analysis

Finally, planning your data analysis in advance is crucial for a successful study. Decide which statistical or analytical tools are most suited for your data type and research questions . For quantitative research, you might opt for t-tests, ANOVA, or regression analyses. For qualitative research , thematic analysis or grounded theory may be more appropriate. This phase is integral for interpreting your results and drawing meaningful conclusions in relation to your research question.

Turn data into evidence for insights with ATLAS.ti

Powerful analysis for your research paper or presentation is at your fingertips starting with a free trial.

How to Develop a Good Research Hypothesis

The story of a research study begins by asking a question. Researchers all around the globe are asking curious questions and formulating research hypothesis. However, whether the research study provides an effective conclusion depends on how well one develops a good research hypothesis. Research hypothesis examples could help researchers get an idea as to how to write a good research hypothesis.

This blog will help you understand what is a research hypothesis, its characteristics and, how to formulate a research hypothesis

Table of Contents

What is Hypothesis?

Hypothesis is an assumption or an idea proposed for the sake of argument so that it can be tested. It is a precise, testable statement of what the researchers predict will be outcome of the study.  Hypothesis usually involves proposing a relationship between two variables: the independent variable (what the researchers change) and the dependent variable (what the research measures).

What is a Research Hypothesis?

Research hypothesis is a statement that introduces a research question and proposes an expected result. It is an integral part of the scientific method that forms the basis of scientific experiments. Therefore, you need to be careful and thorough when building your research hypothesis. A minor flaw in the construction of your hypothesis could have an adverse effect on your experiment. In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment).

Characteristics of a Good Research Hypothesis

As the hypothesis is specific, there is a testable prediction about what you expect to happen in a study. You may consider drawing hypothesis from previously published research based on the theory.

A good research hypothesis involves more effort than just a guess. In particular, your hypothesis may begin with a question that could be further explored through background research.

To help you formulate a promising research hypothesis, you should ask yourself the following questions:

• Is the language clear and focused?
• What is the relationship between your hypothesis and your research topic?
• Is your hypothesis testable? If yes, then how?
• What are the possible explanations that you might want to explore?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate your variables without hampering the ethical standards?
• Does your research predict the relationship and outcome?
• Is your research simple and concise (avoids wordiness)?
• Is it clear with no ambiguity or assumptions about the readers’ knowledge
• Is your research observable and testable results?
• Is it relevant and specific to the research question or problem?

The questions listed above can be used as a checklist to make sure your hypothesis is based on a solid foundation. Furthermore, it can help you identify weaknesses in your hypothesis and revise it if necessary.

Source: Educational Hub

How to formulate a research hypothesis.

A testable hypothesis is not a simple statement. It is rather an intricate statement that needs to offer a clear introduction to a scientific experiment, its intentions, and the possible outcomes. However, there are some important things to consider when building a compelling hypothesis.

1. State the problem that you are trying to solve.

Make sure that the hypothesis clearly defines the topic and the focus of the experiment.

2. Try to write the hypothesis as an if-then statement.

Follow this template: If a specific action is taken, then a certain outcome is expected.

3. Define the variables

Independent variables are the ones that are manipulated, controlled, or changed. Independent variables are isolated from other factors of the study.

Dependent variables , as the name suggests are dependent on other factors of the study. They are influenced by the change in independent variable.

4. Scrutinize the hypothesis

Evaluate assumptions, predictions, and evidence rigorously to refine your understanding.

Types of Research Hypothesis

The types of research hypothesis are stated below:

1. Simple Hypothesis

It predicts the relationship between a single dependent variable and a single independent variable.

2. Complex Hypothesis

It predicts the relationship between two or more independent and dependent variables.

3. Directional Hypothesis

It specifies the expected direction to be followed to determine the relationship between variables and is derived from theory. Furthermore, it implies the researcher’s intellectual commitment to a particular outcome.

4. Non-directional Hypothesis

It does not predict the exact direction or nature of the relationship between the two variables. The non-directional hypothesis is used when there is no theory involved or when findings contradict previous research.

5. Associative and Causal Hypothesis

The associative hypothesis defines interdependency between variables. A change in one variable results in the change of the other variable. On the other hand, the causal hypothesis proposes an effect on the dependent due to manipulation of the independent variable.

6. Null Hypothesis

Null hypothesis states a negative statement to support the researcher’s findings that there is no relationship between two variables. There will be no changes in the dependent variable due the manipulation of the independent variable. Furthermore, it states results are due to chance and are not significant in terms of supporting the idea being investigated.

7. Alternative Hypothesis

It states that there is a relationship between the two variables of the study and that the results are significant to the research topic. An experimental hypothesis predicts what changes will take place in the dependent variable when the independent variable is manipulated. Also, it states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.

Research Hypothesis Examples of Independent and Dependent Variables

Research Hypothesis Example 1 The greater number of coal plants in a region (independent variable) increases water pollution (dependent variable). If you change the independent variable (building more coal factories), it will change the dependent variable (amount of water pollution).

Research Hypothesis Example 2 What is the effect of diet or regular soda (independent variable) on blood sugar levels (dependent variable)? If you change the independent variable (the type of soda you consume), it will change the dependent variable (blood sugar levels)

You should not ignore the importance of the above steps. The validity of your experiment and its results rely on a robust testable hypothesis. Developing a strong testable hypothesis has few advantages, it compels us to think intensely and specifically about the outcomes of a study. Consequently, it enables us to understand the implication of the question and the different variables involved in the study. Furthermore, it helps us to make precise predictions based on prior research. Hence, forming a hypothesis would be of great value to the research. Here are some good examples of testable hypotheses.

More importantly, you need to build a robust testable research hypothesis for your scientific experiments. A testable hypothesis is a hypothesis that can be proved or disproved as a result of experimentation.

Importance of a Testable Hypothesis

To devise and perform an experiment using scientific method, you need to make sure that your hypothesis is testable. To be considered testable, some essential criteria must be met:

• There must be a possibility to prove that the hypothesis is true.
• There must be a possibility to prove that the hypothesis is false.
• The results of the hypothesis must be reproducible.

Without these criteria, the hypothesis and the results will be vague. As a result, the experiment will not prove or disprove anything significant.

What are your experiences with building hypotheses for scientific experiments? What challenges did you face? How did you overcome these challenges? Please share your thoughts with us in the comments section.

Frequently Asked Questions

The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a ‘if-then’ structure. 3. Defining the variables: Define the variables as Dependent or Independent based on their dependency to other factors. 4. Scrutinizing the hypothesis: Identify the type of your hypothesis

Hypothesis testing is a statistical tool which is used to make inferences about a population data to draw conclusions for a particular hypothesis.

Hypothesis in statistics is a formal statement about the nature of a population within a structured framework of a statistical model. It is used to test an existing hypothesis by studying a population.

Research hypothesis is a statement that introduces a research question and proposes an expected result. It forms the basis of scientific experiments.

The different types of hypothesis in research are: • Null hypothesis: Null hypothesis is a negative statement to support the researcher’s findings that there is no relationship between two variables. • Alternate hypothesis: Alternate hypothesis predicts the relationship between the two variables of the study. • Directional hypothesis: Directional hypothesis specifies the expected direction to be followed to determine the relationship between variables. • Non-directional hypothesis: Non-directional hypothesis does not predict the exact direction or nature of the relationship between the two variables. • Simple hypothesis: Simple hypothesis predicts the relationship between a single dependent variable and a single independent variable. • Complex hypothesis: Complex hypothesis predicts the relationship between two or more independent and dependent variables. • Associative and casual hypothesis: Associative and casual hypothesis predicts the relationship between two or more independent and dependent variables. • Empirical hypothesis: Empirical hypothesis can be tested via experiments and observation. • Statistical hypothesis: A statistical hypothesis utilizes statistical models to draw conclusions about broader populations.

Wow! You really simplified your explanation that even dummies would find it easy to comprehend. Thank you so much.

Thanks a lot for your valuable guidance.

I enjoy reading the post. Hypotheses are actually an intrinsic part in a study. It bridges the research question and the methodology of the study.

Useful piece!

This is awesome.Wow.

It very interesting to read the topic, can you guide me any specific example of hypothesis process establish throw the Demand and supply of the specific product in market

Nicely explained

It is really a useful for me Kindly give some examples of hypothesis

It was a well explained content ,can you please give me an example with the null and alternative hypothesis illustrated

clear and concise. thanks.

So Good so Amazing

Good to learn

Thanks a lot for explaining to my level of understanding

Explained well and in simple terms. Quick read! Thank you

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Reporting Research

Choosing the Right Analytical Approach: Thematic analysis vs. content analysis for data interpretation

In research, choosing the right approach to understand data is crucial for deriving meaningful insights.…

Comparing Cross Sectional and Longitudinal Studies: 5 steps for choosing the right approach

The process of choosing the right research design can put ourselves at the crossroads of…

• Industry News

COPE Forum Discussion Highlights Challenges and Urges Clarity in Institutional Authorship Standards

The COPE forum discussion held in December 2023 initiated with a fundamental question — is…

• Career Corner

Unlocking the Power of Networking in Academic Conferences

Embarking on your first academic conference experience? Fear not, we got you covered! Academic conferences…

Research Recommendations – Guiding policy-makers for evidence-based decision making

Research recommendations play a crucial role in guiding scholars and researchers toward fruitful avenues of…

Choosing the Right Analytical Approach: Thematic analysis vs. content analysis for…

Comparing Cross Sectional and Longitudinal Studies: 5 steps for choosing the right…

How to Design Effective Research Questionnaires for Robust Findings

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

What should universities' stance be on AI tools in research and academic writing?

• Resources Home 🏠
• Try SciSpace Copilot
• Search research papers
• Add Copilot Extension
• Try AI Detector
• Try Paraphraser
• Try Citation Generator
• April Papers
• June Papers
• July Papers

The Craft of Writing a Strong Hypothesis

Table of Contents

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good  alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

• Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
• Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher  the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

• A research hypothesis has to be simple yet clear to look justifiable enough.
• It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
• It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
• A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
• If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
• A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

You might also like

Consensus GPT vs. SciSpace GPT: Choose the Best GPT for Research

Literature Review and Theoretical Framework: Understanding the Differences

Types of Essays in Academic Writing - Quick Guide (2024)

• Manuscript Preparation

What is and How to Write a Good Hypothesis in Research?

• 4 minute read
• 289.2K views

Table of Contents

One of the most important aspects of conducting research is constructing a strong hypothesis. But what makes a hypothesis in research effective? In this article, we’ll look at the difference between a hypothesis and a research question, as well as the elements of a good hypothesis in research. We’ll also include some examples of effective hypotheses, and what pitfalls to avoid.

What is a Hypothesis in Research?

Simply put, a hypothesis is a research question that also includes the predicted or expected result of the research. Without a hypothesis, there can be no basis for a scientific or research experiment. As such, it is critical that you carefully construct your hypothesis by being deliberate and thorough, even before you set pen to paper. Unless your hypothesis is clearly and carefully constructed, any flaw can have an adverse, and even grave, effect on the quality of your experiment and its subsequent results.

Research Question vs Hypothesis

It’s easy to confuse research questions with hypotheses, and vice versa. While they’re both critical to the Scientific Method, they have very specific differences. Primarily, a research question, just like a hypothesis, is focused and concise. But a hypothesis includes a prediction based on the proposed research, and is designed to forecast the relationship of and between two (or more) variables. Research questions are open-ended, and invite debate and discussion, while hypotheses are closed, e.g. “The relationship between A and B will be C.”

A hypothesis is generally used if your research topic is fairly well established, and you are relatively certain about the relationship between the variables that will be presented in your research. Since a hypothesis is ideally suited for experimental studies, it will, by its very existence, affect the design of your experiment. The research question is typically used for new topics that have not yet been researched extensively. Here, the relationship between different variables is less known. There is no prediction made, but there may be variables explored. The research question can be casual in nature, simply trying to understand if a relationship even exists, descriptive or comparative.

How to Write Hypothesis in Research

Writing an effective hypothesis starts before you even begin to type. Like any task, preparation is key, so you start first by conducting research yourself, and reading all you can about the topic that you plan to research. From there, you’ll gain the knowledge you need to understand where your focus within the topic will lie.

Remember that a hypothesis is a prediction of the relationship that exists between two or more variables. Your job is to write a hypothesis, and design the research, to “prove” whether or not your prediction is correct. A common pitfall is to use judgments that are subjective and inappropriate for the construction of a hypothesis. It’s important to keep the focus and language of your hypothesis objective.

An effective hypothesis in research is clearly and concisely written, and any terms or definitions clarified and defined. Specific language must also be used to avoid any generalities or assumptions.

Use the following points as a checklist to evaluate the effectiveness of your research hypothesis:

• Predicts the relationship and outcome
• Simple and concise – avoid wordiness
• Clear with no ambiguity or assumptions about the readers’ knowledge
• Observable and testable results
• Relevant and specific to the research question or problem

Research Hypothesis Example

Perhaps the best way to evaluate whether or not your hypothesis is effective is to compare it to those of your colleagues in the field. There is no need to reinvent the wheel when it comes to writing a powerful research hypothesis. As you’re reading and preparing your hypothesis, you’ll also read other hypotheses. These can help guide you on what works, and what doesn’t, when it comes to writing a strong research hypothesis.

Here are a few generic examples to get you started.

Eating an apple each day, after the age of 60, will result in a reduction of frequency of physician visits.

Budget airlines are more likely to receive more customer complaints. A budget airline is defined as an airline that offers lower fares and fewer amenities than a traditional full-service airline. (Note that the term “budget airline” is included in the hypothesis.

Workplaces that offer flexible working hours report higher levels of employee job satisfaction than workplaces with fixed hours.

Each of the above examples are specific, observable and measurable, and the statement of prediction can be verified or shown to be false by utilizing standard experimental practices. It should be noted, however, that often your hypothesis will change as your research progresses.

Language Editing Plus

Elsevier’s Language Editing Plus service can help ensure that your research hypothesis is well-designed, and articulates your research and conclusions. Our most comprehensive editing package, you can count on a thorough language review by native-English speakers who are PhDs or PhD candidates. We’ll check for effective logic and flow of your manuscript, as well as document formatting for your chosen journal, reference checks, and much more.

• Research Process

Systematic Literature Review or Literature Review?

What is a Problem Statement? [with examples]

You may also like.

Make Hook, Line, and Sinker: The Art of Crafting Engaging Introductions

Can Describing Study Limitations Improve the Quality of Your Paper?

A Guide to Crafting Shorter, Impactful Sentences in Academic Writing

6 Steps to Write an Excellent Discussion in Your Manuscript

How to Write Clear and Crisp Civil Engineering Papers? Here are 5 Key Tips to Consider

The Clear Path to An Impactful Paper: ②

The Essentials of Writing to Communicate Research in Medicine

Changing Lines: Sentence Patterns in Academic Writing

Input your search keywords and press Enter.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Korean Med Sci
• v.36(50); 2021 Dec 27

Formulating Hypotheses for Different Study Designs

Durga prasanna misra.

1 Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.

Armen Yuri Gasparyan

2 Departments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, UK.

Olena Zimba

3 Department of Internal Medicine #2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.

Marlen Yessirkepov

4 Department of Biology and Biochemistry, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.

Vikas Agarwal

George d. kitas.

5 Centre for Epidemiology versus Arthritis, University of Manchester, Manchester, UK.

Generating a testable working hypothesis is the first step towards conducting original research. Such research may prove or disprove the proposed hypothesis. Case reports, case series, online surveys and other observational studies, clinical trials, and narrative reviews help to generate hypotheses. Observational and interventional studies help to test hypotheses. A good hypothesis is usually based on previous evidence-based reports. Hypotheses without evidence-based justification and a priori ideas are not received favourably by the scientific community. Original research to test a hypothesis should be carefully planned to ensure appropriate methodology and adequate statistical power. While hypotheses can challenge conventional thinking and may be controversial, they should not be destructive. A hypothesis should be tested by ethically sound experiments with meaningful ethical and clinical implications. The coronavirus disease 2019 pandemic has brought into sharp focus numerous hypotheses, some of which were proven (e.g. effectiveness of corticosteroids in those with hypoxia) while others were disproven (e.g. ineffectiveness of hydroxychloroquine and ivermectin).

Graphical Abstract

DEFINING WORKING AND STANDALONE SCIENTIFIC HYPOTHESES

Science is the systematized description of natural truths and facts. Routine observations of existing life phenomena lead to the creative thinking and generation of ideas about mechanisms of such phenomena and related human interventions. Such ideas presented in a structured format can be viewed as hypotheses. After generating a hypothesis, it is necessary to test it to prove its validity. Thus, hypothesis can be defined as a proposed mechanism of a naturally occurring event or a proposed outcome of an intervention. 1 , 2

Hypothesis testing requires choosing the most appropriate methodology and adequately powering statistically the study to be able to “prove” or “disprove” it within predetermined and widely accepted levels of certainty. This entails sample size calculation that often takes into account previously published observations and pilot studies. 2 , 3 In the era of digitization, hypothesis generation and testing may benefit from the availability of numerous platforms for data dissemination, social networking, and expert validation. Related expert evaluations may reveal strengths and limitations of proposed ideas at early stages of post-publication promotion, preventing the implementation of unsupported controversial points. 4

Thus, hypothesis generation is an important initial step in the research workflow, reflecting accumulating evidence and experts' stance. In this article, we overview the genesis and importance of scientific hypotheses and their relevance in the era of the coronavirus disease 2019 (COVID-19) pandemic.

DO WE NEED HYPOTHESES FOR ALL STUDY DESIGNS?

Broadly, research can be categorized as primary or secondary. In the context of medicine, primary research may include real-life observations of disease presentations and outcomes. Single case descriptions, which often lead to new ideas and hypotheses, serve as important starting points or justifications for case series and cohort studies. The importance of case descriptions is particularly evident in the context of the COVID-19 pandemic when unique, educational case reports have heralded a new era in clinical medicine. 5

Case series serve similar purpose to single case reports, but are based on a slightly larger quantum of information. Observational studies, including online surveys, describe the existing phenomena at a larger scale, often involving various control groups. Observational studies include variable-scale epidemiological investigations at different time points. Interventional studies detail the results of therapeutic interventions.

Secondary research is based on already published literature and does not directly involve human or animal subjects. Review articles are generated by secondary research. These could be systematic reviews which follow methods akin to primary research but with the unit of study being published papers rather than humans or animals. Systematic reviews have a rigid structure with a mandatory search strategy encompassing multiple databases, systematic screening of search results against pre-defined inclusion and exclusion criteria, critical appraisal of study quality and an optional component of collating results across studies quantitatively to derive summary estimates (meta-analysis). 6 Narrative reviews, on the other hand, have a more flexible structure. Systematic literature searches to minimise bias in selection of articles are highly recommended but not mandatory. 7 Narrative reviews are influenced by the authors' viewpoint who may preferentially analyse selected sets of articles. 8

In relation to primary research, case studies and case series are generally not driven by a working hypothesis. Rather, they serve as a basis to generate a hypothesis. Observational or interventional studies should have a hypothesis for choosing research design and sample size. The results of observational and interventional studies further lead to the generation of new hypotheses, testing of which forms the basis of future studies. Review articles, on the other hand, may not be hypothesis-driven, but form fertile ground to generate future hypotheses for evaluation. Fig. 1 summarizes which type of studies are hypothesis-driven and which lead on to hypothesis generation.

STANDARDS OF WORKING AND SCIENTIFIC HYPOTHESES

A review of the published literature did not enable the identification of clearly defined standards for working and scientific hypotheses. It is essential to distinguish influential versus not influential hypotheses, evidence-based hypotheses versus a priori statements and ideas, ethical versus unethical, or potentially harmful ideas. The following points are proposed for consideration while generating working and scientific hypotheses. 1 , 2 Table 1 summarizes these points.

Evidence-based data

A scientific hypothesis should have a sound basis on previously published literature as well as the scientist's observations. Randomly generated (a priori) hypotheses are unlikely to be proven. A thorough literature search should form the basis of a hypothesis based on published evidence. 7

Unless a scientific hypothesis can be tested, it can neither be proven nor be disproven. Therefore, a scientific hypothesis should be amenable to testing with the available technologies and the present understanding of science.

Supported by pilot studies

If a hypothesis is based purely on a novel observation by the scientist in question, it should be grounded on some preliminary studies to support it. For example, if a drug that targets a specific cell population is hypothesized to be useful in a particular disease setting, then there must be some preliminary evidence that the specific cell population plays a role in driving that disease process.

Testable by ethical studies

The hypothesis should be testable by experiments that are ethically acceptable. 9 For example, a hypothesis that parachutes reduce mortality from falls from an airplane cannot be tested using a randomized controlled trial. 10 This is because it is obvious that all those jumping from a flying plane without a parachute would likely die. Similarly, the hypothesis that smoking tobacco causes lung cancer cannot be tested by a clinical trial that makes people take up smoking (since there is considerable evidence for the health hazards associated with smoking). Instead, long-term observational studies comparing outcomes in those who smoke and those who do not, as was performed in the landmark epidemiological case control study by Doll and Hill, 11 are more ethical and practical.

Balance between scientific temper and controversy

Novel findings, including novel hypotheses, particularly those that challenge established norms, are bound to face resistance for their wider acceptance. Such resistance is inevitable until the time such findings are proven with appropriate scientific rigor. However, hypotheses that generate controversy are generally unwelcome. For example, at the time the pandemic of human immunodeficiency virus (HIV) and AIDS was taking foot, there were numerous deniers that refused to believe that HIV caused AIDS. 12 , 13 Similarly, at a time when climate change is causing catastrophic changes to weather patterns worldwide, denial that climate change is occurring and consequent attempts to block climate change are certainly unwelcome. 14 The denialism and misinformation during the COVID-19 pandemic, including unfortunate examples of vaccine hesitancy, are more recent examples of controversial hypotheses not backed by science. 15 , 16 An example of a controversial hypothesis that was a revolutionary scientific breakthrough was the hypothesis put forth by Warren and Marshall that Helicobacter pylori causes peptic ulcers. Initially, the hypothesis that a microorganism could cause gastritis and gastric ulcers faced immense resistance. When the scientists that proposed the hypothesis themselves ingested H. pylori to induce gastritis in themselves, only then could they convince the wider world about their hypothesis. Such was the impact of the hypothesis was that Barry Marshall and Robin Warren were awarded the Nobel Prize in Physiology or Medicine in 2005 for this discovery. 17 , 18

DISTINGUISHING THE MOST INFLUENTIAL HYPOTHESES

Influential hypotheses are those that have stood the test of time. An archetype of an influential hypothesis is that proposed by Edward Jenner in the eighteenth century that cowpox infection protects against smallpox. While this observation had been reported for nearly a century before this time, it had not been suitably tested and publicised until Jenner conducted his experiments on a young boy by demonstrating protection against smallpox after inoculation with cowpox. 19 These experiments were the basis for widespread smallpox immunization strategies worldwide in the 20th century which resulted in the elimination of smallpox as a human disease today. 20

Other influential hypotheses are those which have been read and cited widely. An example of this is the hygiene hypothesis proposing an inverse relationship between infections in early life and allergies or autoimmunity in adulthood. An analysis reported that this hypothesis had been cited more than 3,000 times on Scopus. 1

LESSONS LEARNED FROM HYPOTHESES AMIDST THE COVID-19 PANDEMIC

The COVID-19 pandemic devastated the world like no other in recent memory. During this period, various hypotheses emerged, understandably so considering the public health emergency situation with innumerable deaths and suffering for humanity. Within weeks of the first reports of COVID-19, aberrant immune system activation was identified as a key driver of organ dysfunction and mortality in this disease. 21 Consequently, numerous drugs that suppress the immune system or abrogate the activation of the immune system were hypothesized to have a role in COVID-19. 22 One of the earliest drugs hypothesized to have a benefit was hydroxychloroquine. Hydroxychloroquine was proposed to interfere with Toll-like receptor activation and consequently ameliorate the aberrant immune system activation leading to pathology in COVID-19. 22 The drug was also hypothesized to have a prophylactic role in preventing infection or disease severity in COVID-19. It was also touted as a wonder drug for the disease by many prominent international figures. However, later studies which were well-designed randomized controlled trials failed to demonstrate any benefit of hydroxychloroquine in COVID-19. 23 , 24 , 25 , 26 Subsequently, azithromycin 27 , 28 and ivermectin 29 were hypothesized as potential therapies for COVID-19, but were not supported by evidence from randomized controlled trials. The role of vitamin D in preventing disease severity was also proposed, but has not been proven definitively until now. 30 , 31 On the other hand, randomized controlled trials identified the evidence supporting dexamethasone 32 and interleukin-6 pathway blockade with tocilizumab as effective therapies for COVID-19 in specific situations such as at the onset of hypoxia. 33 , 34 Clues towards the apparent effectiveness of various drugs against severe acute respiratory syndrome coronavirus 2 in vitro but their ineffectiveness in vivo have recently been identified. Many of these drugs are weak, lipophilic bases and some others induce phospholipidosis which results in apparent in vitro effectiveness due to non-specific off-target effects that are not replicated inside living systems. 35 , 36

Another hypothesis proposed was the association of the routine policy of vaccination with Bacillus Calmette-Guerin (BCG) with lower deaths due to COVID-19. This hypothesis emerged in the middle of 2020 when COVID-19 was still taking foot in many parts of the world. 37 , 38 Subsequently, many countries which had lower deaths at that time point went on to have higher numbers of mortality, comparable to other areas of the world. Furthermore, the hypothesis that BCG vaccination reduced COVID-19 mortality was a classic example of ecological fallacy. Associations between population level events (ecological studies; in this case, BCG vaccination and COVID-19 mortality) cannot be directly extrapolated to the individual level. Furthermore, such associations cannot per se be attributed as causal in nature, and can only serve to generate hypotheses that need to be tested at the individual level. 39

IS TRADITIONAL PEER REVIEW EFFICIENT FOR EVALUATION OF WORKING AND SCIENTIFIC HYPOTHESES?

Traditionally, publication after peer review has been considered the gold standard before any new idea finds acceptability amongst the scientific community. Getting a work (including a working or scientific hypothesis) reviewed by experts in the field before experiments are conducted to prove or disprove it helps to refine the idea further as well as improve the experiments planned to test the hypothesis. 40 A route towards this has been the emergence of journals dedicated to publishing hypotheses such as the Central Asian Journal of Medical Hypotheses and Ethics. 41 Another means of publishing hypotheses is through registered research protocols detailing the background, hypothesis, and methodology of a particular study. If such protocols are published after peer review, then the journal commits to publishing the completed study irrespective of whether the study hypothesis is proven or disproven. 42 In the post-pandemic world, online research methods such as online surveys powered via social media channels such as Twitter and Instagram might serve as critical tools to generate as well as to preliminarily test the appropriateness of hypotheses for further evaluation. 43 , 44

Some radical hypotheses might be difficult to publish after traditional peer review. These hypotheses might only be acceptable by the scientific community after they are tested in research studies. Preprints might be a way to disseminate such controversial and ground-breaking hypotheses. 45 However, scientists might prefer to keep their hypotheses confidential for the fear of plagiarism of ideas, avoiding online posting and publishing until they have tested the hypotheses.

SUGGESTIONS ON GENERATING AND PUBLISHING HYPOTHESES

Publication of hypotheses is important, however, a balance is required between scientific temper and controversy. Journal editors and reviewers might keep in mind these specific points, summarized in Table 2 and detailed hereafter, while judging the merit of hypotheses for publication. Keeping in mind the ethical principle of primum non nocere, a hypothesis should be published only if it is testable in a manner that is ethically appropriate. 46 Such hypotheses should be grounded in reality and lend themselves to further testing to either prove or disprove them. It must be considered that subsequent experiments to prove or disprove a hypothesis have an equal chance of failing or succeeding, akin to tossing a coin. A pre-conceived belief that a hypothesis is unlikely to be proven correct should not form the basis of rejection of such a hypothesis for publication. In this context, hypotheses generated after a thorough literature search to identify knowledge gaps or based on concrete clinical observations on a considerable number of patients (as opposed to random observations on a few patients) are more likely to be acceptable for publication by peer-reviewed journals. Also, hypotheses should be considered for publication or rejection based on their implications for science at large rather than whether the subsequent experiments to test them end up with results in favour of or against the original hypothesis.

Hypotheses form an important part of the scientific literature. The COVID-19 pandemic has reiterated the importance and relevance of hypotheses for dealing with public health emergencies and highlighted the need for evidence-based and ethical hypotheses. A good hypothesis is testable in a relevant study design, backed by preliminary evidence, and has positive ethical and clinical implications. General medical journals might consider publishing hypotheses as a specific article type to enable more rapid advancement of science.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Data curation: Gasparyan AY, Misra DP, Zimba O, Yessirkepov M, Agarwal V, Kitas GD.

Join thousands of product people at Insight Out Conf on April 11. Register free.

Insights hub solutions

Analyze data

Uncover deep customer insights with fast, powerful features, store insights, curate and manage insights in one searchable platform, scale research, unlock the potential of customer insights at enterprise scale.

Featured reads

Inspiration

Three things to look forward to at Insight Out

Tips and tricks

Make magic with your customer data in Dovetail

Four ways Dovetail helps Product Managers master continuous product discovery

Events and videos

© Dovetail Research Pty. Ltd.

How to write a research hypothesis

Last updated

19 January 2023

Reviewed by

Miroslav Damyanov

Start with a broad subject matter that excites you, so your curiosity will motivate your work. Conduct a literature search to determine the range of questions already addressed and spot any holes in the existing research.

Narrow the topics that interest you and determine your research question. Rather than focusing on a hole in the research, you might choose to challenge an existing assumption, a process called problematization. You may also find yourself with a short list of questions or related topics.

Use the FINER method to determine the single problem you'll address with your research. FINER stands for:

I nteresting

You need a feasible research question, meaning that there is a way to address the question. You should find it interesting, but so should a larger audience. Rather than repeating research that others have already conducted, your research hypothesis should test something novel or unique. 

The research must fall into accepted ethical parameters as defined by the government of your country and your university or college if you're an academic. You'll also need to come up with a relevant question since your research should provide a contribution to the existing research area.

This process typically narrows your shortlist down to a single problem you'd like to study and the variable you want to test. You're ready to write your hypothesis statements.

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

• Types of research hypotheses

It is important to narrow your topic down to one idea before trying to write your research hypothesis. You'll only test one problem at a time. To do this, you'll write two hypotheses – a null hypothesis (H0) and an alternative hypothesis (Ha).

You'll come across many terms related to developing a research hypothesis or referring to a specific type of hypothesis. Let's take a quick look at these terms.

Null hypothesis

The term null hypothesis refers to a research hypothesis type that assumes no statistically significant relationship exists within a set of observations or data. It represents a claim that assumes that any observed relationship is due to chance. Represented as H0, the null represents the conjecture of the research.

Alternative hypothesis

The alternative hypothesis accompanies the null hypothesis. It states that the situation presented in the null hypothesis is false or untrue, and claims an observed effect in your test. This is typically denoted by Ha or H(n), where “n” stands for the number of alternative hypotheses. You can have more than one alternative hypothesis. 

Simple hypothesis

The term simple hypothesis refers to a hypothesis or theory that predicts the relationship between two variables - the independent (predictor) and the dependent (predicted). 

Complex hypothesis

The term complex hypothesis refers to a model – either quantitative (mathematical) or qualitative . A complex hypothesis states the surmised relationship between two or more potentially related variables.

Directional hypothesis

When creating a statistical hypothesis, the directional hypothesis (the null hypothesis) states an assumption regarding one parameter of a population. Some academics call this the “one-sided” hypothesis. The alternative hypothesis indicates whether the researcher tests for a positive or negative effect by including either the greater than (">") or less than ("<") sign.

Non-directional hypothesis

We refer to the alternative hypothesis in a statistical research question as a non-directional hypothesis. It includes the not equal ("≠") sign to show that the research tests whether or not an effect exists without specifying the effect's direction (positive or negative).

Associative hypothesis

The term associative hypothesis assumes a link between two variables but stops short of stating that one variable impacts the other. Academic statistical literature asserts in this sense that correlation does not imply causation. So, although the hypothesis notes the correlation between two variables – the independent and dependent - it does not predict how the two interact.

Logical hypothesis

Typically used in philosophy rather than science, researchers can't test a logical hypothesis because the technology or data set doesn't yet exist. A logical hypothesis uses logic as the basis of its assumptions. 

In some cases, a logical hypothesis can become an empirical hypothesis once technology provides an opportunity for testing. Until that time, the question remains too expensive or complex to address. Note that a logical hypothesis is not a statistical hypothesis.

Empirical hypothesis

When we consider the opposite of a logical hypothesis, we call this an empirical or working hypothesis. This type of hypothesis considers a scientifically measurable question. A researcher can consider and test an empirical hypothesis through replicable tests, observations, and measurements.

Statistical hypothesis

The term statistical hypothesis refers to a test of a theory that uses representative statistical models to test relationships between variables to draw conclusions regarding a large population. This requires an existing large data set, commonly referred to as big data, or implementing a survey to obtain original statistical information to form a data set for the study. 

Testing this type of hypothesis requires the use of random samples. Note that the null and alternative hypotheses are used in statistical hypothesis testing.

Causal hypothesis

The term causal hypothesis refers to a research hypothesis that tests a cause-and-effect relationship. A causal hypothesis is utilized when conducting experimental or quasi-experimental research.

Descriptive hypothesis

The term descriptive hypothesis refers to a research hypothesis used in non-experimental research, specifying an influence in the relationship between two variables.

• What makes an effective research hypothesis?

An effective research hypothesis offers a clearly defined, specific statement, using simple wording that contains no assumptions or generalizations, and that you can test. A well-written hypothesis should predict the tested relationship and its outcome. It contains zero ambiguity and offers results you can observe and test. 

The research hypothesis should address a question relevant to a research area. Overall, your research hypothesis needs the following essentials:

Hypothesis Essential #1: Specificity & Clarity

Hypothesis Essential #2: Testability (Provability)

• How to develop a good research hypothesis

In developing your hypothesis statements, you must pre-plan some of your statistical analysis. Once you decide on your problem to examine, determine three aspects:

the parameter you'll test

the test's direction (left-tailed, right-tailed, or non-directional)

the hypothesized parameter value

Any quantitative research includes a hypothesized parameter value of a mean, a proportion, or the difference between two proportions. Here's how to note each parameter:

Single mean (μ)

Paired means (μd)

Single proportion (p)

Difference between two independent means (μ1−μ2)

Difference between two proportions (p1−p2)

Simple linear regression slope (β)

Correlation (ρ)

Defining these parameters and determining whether you want to test the mean, proportion, or differences helps you determine the statistical tests you'll conduct to analyze your data. When writing your hypothesis, you only need to decide which parameter to test and in what overarching way.

The null research hypothesis must include everyday language, in a single sentence, stating the problem you want to solve. Write it as an if-then statement with defined variables. Write an alternative research hypothesis that states the opposite.

• What is the correct format for writing a hypothesis?

The following example shows the proper format and textual content of a hypothesis. It follows commonly accepted academic standards.

Null hypothesis (H0): High school students who participate in varsity sports as opposed to those who do not, fail to score higher on leadership tests than students who do not participate.

Alternative hypothesis (H1): High school students who play a varsity sport as opposed to those who do not participate in team athletics will score higher on leadership tests than students who do not participate in athletics.

The research question tests the correlation between varsity sports participation and leadership qualities expressed as a score on leadership tests. It compares the population of athletes to non-athletes.

• What are the five steps of a hypothesis?

Once you decide on the specific problem or question you want to address, you can write your research hypothesis. Use this five-step system to hone your null hypothesis and generate your alternative hypothesis.

Step 1 : Create your research question. This topic should interest and excite you; answering it provides relevant information to an industry or academic area.

Step 2 : Conduct a literature review to gather essential existing research.

Step 3 : Write a clear, strong, simply worded sentence that explains your test parameter, test direction, and hypothesized parameter.

Step 4 : Read it a few times. Have others read it and ask them what they think it means. Refine your statement accordingly until it becomes understandable to everyone. While not everyone can or will comprehend every research study conducted, any person from the general population should be able to read your hypothesis and alternative hypothesis and understand the essential question you want to answer.

Step 5 : Re-write your null hypothesis until it reads simply and understandably. Write your alternative hypothesis.

What is the Red Queen hypothesis?

Some hypotheses are well-known, such as the Red Queen hypothesis. Choose your wording carefully, since you could become like the famed scientist Dr. Leigh Van Valen. In 1973, Dr. Van Valen proposed the Red Queen hypothesis to describe coevolutionary activity, specifically reciprocal evolutionary effects between species to explain extinction rates in the fossil record. 

Essentially, Van Valen theorized that to survive, each species remains in a constant state of adaptation, evolution, and proliferation, and constantly competes for survival alongside other species doing the same. Only by doing this can a species avoid extinction. Van Valen took the hypothesis title from the Lewis Carroll book, "Through the Looking Glass," which contains a key character named the Red Queen who explains to Alice that for all of her running, she's merely running in place.

• Getting started with your research

In conclusion, once you write your null hypothesis (H0) and an alternative hypothesis (Ha), you’ve essentially authored the elevator pitch of your research. These two one-sentence statements describe your topic in simple, understandable terms that both professionals and laymen can understand. They provide the starting point of your research project.

Get started today

Go from raw data to valuable insights with a flexible research platform

Editor’s picks

Last updated: 21 December 2023

Last updated: 16 December 2023

Last updated: 6 October 2023

Last updated: 17 February 2024

Last updated: 5 March 2024

Last updated: 19 November 2023

Last updated: 15 February 2024

Last updated: 11 March 2024

Last updated: 12 December 2023

Last updated: 6 March 2024

Last updated: 10 April 2023

Last updated: 20 December 2023

Latest articles

Related topics, log in or sign up.

Get started for free

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

How to Write a Great Hypothesis

Hypothesis Format, Examples, and Tips

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk,  "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis, operational definitions, types of hypotheses, hypotheses examples.

• Collecting Data

Frequently Asked Questions

A hypothesis is a tentative statement about the relationship between two or more  variables. It is a specific, testable prediction about what you expect to happen in a study.

One hypothesis example would be a study designed to look at the relationship between sleep deprivation and test performance might have a hypothesis that states: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

• Forming a question
• Performing background research
• Creating a hypothesis
• Designing an experiment
• Collecting data
• Analyzing the results
• Drawing conclusions
• Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. It is only at this point that researchers begin to develop a testable hypothesis. Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore a number of factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment  do not  support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk wisdom that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the  journal articles you read . Many authors will suggest questions that still need to be explored.

To form a hypothesis, you should take these steps:

• Collect as many observations about a topic or problem as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method ,  falsifiability is an important part of any valid hypothesis.   In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that  if  something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in a number of different ways. One of the basic principles of any type of scientific research is that the results must be replicable.   By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. How would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

In order to measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming other people. In this situation, the researcher might utilize a simulated task to measure aggressiveness.

Hypothesis Checklist

• Does your hypothesis focus on something that you can actually test?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate the variables?
• Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

• Simple hypothesis : This type of hypothesis suggests that there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type of hypothesis suggests a relationship between three or more variables, such as two independent variables and a dependent variable.
• Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
• Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
• Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative sample of the population and then generalizes the findings to the larger group.
• Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the  dependent variable  if you change the  independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

• "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
• Complex hypothesis: "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."​
• "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."

Examples of a complex hypothesis include:

• "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
• "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

• "Children who receive a new reading intervention will have scores different than students who do not receive the intervention."
• "There will be no difference in scores on a memory recall task between children and adults."

Examples of an alternative hypothesis:

• "Children who receive a new reading intervention will perform better than students who did not receive the intervention."
• "Adults will perform better on a memory task than children." 

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as  case studies ,  naturalistic observations , and surveys are often used when it would be impossible or difficult to  conduct an experiment . These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a correlational study can then be used to look at how the variables are related. This type of research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods  are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually  cause  another to change.

A Word From Verywell

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Some examples of how to write a hypothesis include:

• "Staying up late will lead to worse test performance the next day."
• "People who consume one apple each day will visit the doctor fewer times each year."
• "Breaking study sessions up into three 20-minute sessions will lead to better test results than a single 60-minute study session."

The four parts of a hypothesis are:

• The research question
• The independent variable (IV)
• The dependent variable (DV)
• The proposed relationship between the IV and DV

Castillo M. The scientific method: a need for something better? . AJNR Am J Neuroradiol. 2013;34(9):1669-71. doi:10.3174/ajnr.A3401

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

• Search Menu

A newer edition of this book is available.

• < Previous chapter
• Next chapter >

31 Writing Up Qualitative Research

Jane F. Gilgun, School of Social Work, University of Minnesota, Twin Cities

• Published: 04 August 2014
• Cite Icon Cite
• Permissions Icon Permissions

This chapter provides guidelines for writing journal articles based on qualitative approaches. The guidelines are part of the tradition of the Chicago School of Sociology and the author’s experience as a writer and reviewer. The guidelines include understanding experiences in context, immersion, interpretations grounded in accounts of informants’ lived experiences, and research as action-oriented. The chapter also covers writing articles that report findings based on ethnographies, autoethnographies, performances, poetry, and photography and other graphic media.

How researchers write up results for journal publications depends on the purposes of the research and the methodologies they use. Some topics are standard, such as statements about methods and methodologies, but how to represent other topics, like related research and theory, reflexivity, and informants’ accounts, may vary. For example, articles based on ethnographic research may be structured differently from writing up research whose purpose is theory development. Journal editors and reviewers often are familiar with variations in style of write-ups, but, when they are not, they may ask for modifications that violate the methodological principles of the research. A common reviewer request is for percentages, which has little meaning in almost all forms of qualitative research because the purpose of the research is to identify patterns of meanings and not distributions of variables. For example, Irvine’s (2013) ethnography of the meanings of pets to homeless people shows a variety of meaning without giving the number of participants from which she drew.

Authors sometimes move easily through the review process, but most often they do not, not only because reviewers might not “get it,” but also because authors have left out, underemphasized, or been less than clear about aspects of their research that reviewers and editors believe are important. Working with editors and reviewers frequently results in improved articles.

The purpose of this chapter is to provide guidelines for writing journal articles based on qualitative approaches. My intended audience is composed of researchers, reviewers for journals, and journal editors. Reviewers for funding agencies may also find this chapter useful. I use the terms “journal article” and “research report” as synonyms, even though some journal articles are not reports of research. I have derived the guidelines from ideas associated with the Chicago School of Sociology and my experience as an author and reviewer. Although the Chicago School was, as Becker (1999) wrote, “open to various ways of doing sociology” (p. 10), the ideas in this chapter are part of the tradition, but they are not representative of the entire tradition. Furthermore, the ideas are not fixed but are open-ended because they evolve over time. I have followed the principles of the Chicago School of Sociology throughout my career, augmented by updates to these ideas, experiments with other traditions, and the sense I make of my own experiences as researcher, author, and reviewer.

The ideas on which I draw include understanding experiences in context, immersion, interpretations grounded in accounts of informants’ lived experiences, and research as action-oriented ( Bulmer, 1984 ; Faris, 1967 ; Gilgun, 1999 d ; 2005 a ; 2012 a ; 2013 b ). To follow these principles, researchers do in-depth studies that take into account the multiple contextual factors that influence meanings and interpretations, seek multiple points of view, and often use multiple methods such as interviews, observations, and document analysis. Researchers do this style of research not only because what they learn is interesting, but because they want to do useful research; that is, research that leads to social actions and even transformations in policies, programs, and interventions. Authors and reviewers pay attention to these principles. Authors convey them in their write-ups, and reviewers look for them as they develop their appraisals.

Excellent writing up of qualitative research matches these principles. In other words, write-ups convey lived experience within multiple contexts, multiple points of view, and analyses that deepen understandings. In addition, if the research is applied, then authors write about how findings may contribute to quality of life. Qualitative researchers from other traditions may follow similar or different guidelines in their write-ups, and I sometimes note other styles of write-ups. Often these variations are related to terminology and not procedures. The reach of the Chicago School of Sociology is wide and deep.

Following these guidelines does not guarantee an easy review process, but this article will be helpful to researchers as they plan and craft their articles and as they respond to reviewers’ and editors’ comments. After almost thirty years of publishing research based on qualitative approaches, almost as many years as a reviewer, and the editing of three collections of qualitative research reports ( Gilgun, Daly, & Handel, 1992 ; Gilgun & Sussman, 1996 : Gilgun & Sands, 2012 ), I am positioned to offer helpful guidelines, not only to authors but also to reviewers and journal editors.

I begin this chapter with a discussion of general principles and then cover the content of typical sections of research reports. Some of the general material fits into various sections of reports, such as methods and findings. In those cases, I do not repeat material already covered and assume that my writing is clear enough so that readers know how the general material fits into particular sections of articles.

Although most of this chapter addresses the writing of conventional research reports, I also cover writing articles that report findings through ethnographies, autoethnographies, performances, poetry, and photography and other graphic media. Ethnographies are based on researchers’ immersion in the field, where they do extensive observations, interviews, and often document analysis (see Block, 2012 ). Geertz’s (1973) notion of “thick description” is associated with ethnographies. Thick description is characterized by research reports that show the matrix of meanings that researchers identify and attempt to represent in their reports. Autoethnographies are in-depth reflective accounts of individual lives that the narrators themselves write ( Ellis, 2009 ). Ethnographies and autoethnographies involve reflections on meanings, contexts, and other wider influences on individual lives. They are studies of intersections of individual lives and wider cultural themes and practices. Reports of these types of research can look different from conventional research reports in that they appear less formal; the usual sections of methods, literature review, findings, and analysis may have different names; and the sections may be in places that fit the logical flow of the research and not the typical structure of introductory material, methods, results, and discussion. Despite these superficial differences, researchers who write these kinds of articles seek to deepen understandings and hope to move audiences to action through conveying lived experience in context and through multiple points of view. They also typically seek transformations of persons and societies. Links between these forms of research and Chicago School traditions are self-evident.

Some General Principles

Research reports that have these characteristics depend on the quality of the data on which the reports are based, the quality of the analysis, and the skills of researchers in conveying the analysis concisely and with “grab” ( Glaser, 1978 ), which means writing that is vivid and memorable ( Gilgun, 2005 b ). Grab brings findings to life. With grab, human experiences jump off the page. Priority is given to the voices of research participants, whom I call informants, with citations and the wisdom of other researchers providing important contextual information. The voices and analyses of researchers do not dominate ( Gilgun, 2005 c ), except in some articles whose purpose is theory development or the presentation of a theory. Researcher analyses often are important, especially in putting forth social action recommendations that stem from the experiences of informants.

A well-done report shows consistency between research traditions and the writing-up of research. For example, reflexivity statements, writing with grab, and copious excerpts from fieldnotes, interviews, and documents of various sorts are consistent with phenomenological approaches whose emphasis is on lived experience and interpretations that informants make of their experiences. Researchers new to qualitative research, however, often mix their traditions without realizing it, which works when the traditions are compatible. When the traditions are not compatible, the write-ups can be confusing and even contradictory ( Gilgun, 2005 d ). Some authors may write in distanced, third-person styles while attempting to convey informants’ lived experiences. These scholars may, therefore, have difficulty getting their articles accepted. Hopefully, this chapter will facilitate the writing of research reports that show consistency across their many parts and save scholars from rejections of work over which they have taken much care.

Details on These General Principles

In this section, I provide more detail on writing up qualitative research. I begin with a discussion of the need for high-quality data, high-quality analysis, and grab. I then move on to the details of the report, such as the place of prior research and theory, contents of methods sections, organization of findings, and the balance between descriptive material and authors’ interpretations. Dilemmas abound. Writing up qualitative research is not for the faint of heart.

High-Quality Data

Since qualitative researchers seek to understand the subjective experiences of research informants in various contexts, high-quality data result in large part from the degree that researchers practice immersion and to the degree that both researchers and informants develop rapport and engage with each other. Through active engagement, informants share their experiences with the kind of detail that brings their experiences to life. How to develop rapport is beyond the scope of this article, but openness and acceptance of whatever informants say are fundamental to engagement. Interviewers do not have to agree with the values that informants’ accounts convey, as when I interview murderers and rapists ( Gilgun, 2008 ), but we do maintain a neutrality that allows the dialogue to continue ( Gilgun & Anderson, 2013 ). The content of interviews is not about us and our preferences, but about understanding informants.

Prolonged engagement can result in quality data. In interview research, prolonged engagement allows for informants’ multiple perspectives to emerge, including inconsistencies, contradictions, ambiguities, and ambivalences. In addition, prolonged engagement facilitates the kind of trust needed for informants to share personal, sensitive information in detail, which are the kinds of data that qualitative researchers seek. Prolonged engagement also gives researchers time to reflect on what they are learning and experiencing through the interviews. This provides opportunities to develop new understandings and test new understandings through subsequent research. Their understandings thus deepen and broaden. Informants, too, can reflect, reconsider, and deepen the accounts they share.

Prolonged engagement means in-depth interviews, typically multiple interviews of more than an hour each. As mentioned earlier, time between interviews allows researchers and informants to reflect on the previous interview and prepare for the next. Researchers can do background reading, discuss emerging ideas with others, and formulate pertinent new questions. Informants may retrieve long-forgotten memories and interpretations through interviews. If they have only one interview, they have no opportunity to share with researchers the material that arises after the single interview is concluded.

There are exceptions to multiple interviews as necessary for immersion and high-quality data. When researchers have expertise in interviewing and when the topic is focused, one interview of between ninety minutes to two hours could provide some depth. Even under these conditions, however, more than one interview is ideal. I did a study that involved one ninety-minute interview with perpetrators of child sexual abuse in order to understand the circumstances under which their abusive behaviors became known to law enforcement. Thus, the interview was focused. The interviewees were volunteers who had talked about the topic many times in the course of their involvement in sex abuse treatment programs. They shared their stories with depth and breadth. I, too, was well-prepared. By then, I had had about twenty-five years of experience interviewing people about personal, sensitive topics. The informants provided accounts not only because the topic was focused, but because they were willing to share and I was willing to listen and to ask questions about their sexually abusive behaviors. With one interview, however, I knew relatively little about their social histories and general worldviews. Thus, I did not have the specifics necessary to place their accounts into context. The material they provided remained valuable and resulted in one publication ( Sharma & Gilgun, 2008 ) and others in planning stages. I prefer two or more interviews because of the importance of contextual data.

In observational studies, prolonged engagement means that researchers do multiple observations over time to obtain the nuances and details that compose human actions. Observational studies often have interview components and also may have document analysis as well. In document analysis, prolonged engagement means researchers base their analyses on an ample storehouse of documents and not just flit in and out of the documents. The quality of document analysis depends on whether the analysis shows multiple perspectives, patterns, and variations within patterns. Ethnographies have these characteristics. Block’s (2012) ethnographic research on AIDS orphans in Lesotho, Africa, is an example of a well-done ethnography.

Sample Size

In principle, the size of the sample and the depth of the interview affect whether researchers can claim immersion. The more depth and breadth each case in a study has, the smaller the sample size can be. For example, researchers can engage in immersion through a single in-depth case study when they do multiple interviews and if multiple facets of the case are examined. Case studies are investigations of single units. The case can be composed of an individual, a couple, a family, a group, a nation, or a region. Single case studies are useful in the illustration, development, and testing of theories, as well as in in-depth descriptions.

The more focused the questions, the larger the sample will be. A study on long-term marriage would require a minimum of two or three interviews because the topic is complicated. The sample would include at least ten participants and up to twenty or thirty, depending on the number of interviews, to account for some of the many patterns that are likely to emerge in a study of a topic this complex. In the one-interview study I did of how sexual abuse came to the notice of law enforcement, one interview was adequate because of the tight focus of the question. Yet, I used a sample size of thirty-two to maximize the possibility of identifying a variety of patterns, which the study accomplished. As mentioned, the one interview, however, did not allow me to contextualize the stories the informants told. Fortunately, I have another large sample that involved multiple, in-depth interviews in which informants discussed multiple contexts over time. This other study was helpful to me in understanding the accounts from the single-interview study.

Recruitment can be difficult. When it is, researchers may not be able to obtain an adequate sample. For example, a sample of seven participants engaging in a single sixty- to ninety-minute interview may not provide enough data on which to base a credible analysis. In a similar vein, articles based on a single or even a few focus groups may not provide enough depth to be informative. Some depth is possible if, in a single-interview study of less than fifteen or twenty interviewees, researchers meet with informants a second time to go over what researchers understand about informants’ accounts. This sometimes is called member-checking , and it provides additional data on which to base the analysis. In summary, the more depth and breadth to a study, the smaller the sample size can be—even as small as one or two—depending on the questions and the complexity of the cases.

Quality of the Analysis

A quality analysis begins with initial planning of the research and continues until the article is accepted for publication. An excellent research report has transparency , meaning the write-up is clear in what researchers did, how they did it, and why. I often tell students they can do almost anything reasonable and ethical, as long as they make a clear account in the write-up.

During planning, some researchers identify those concepts that they can use as sensitizing concepts once in the field. Transparency about the sources of sensitizing concepts characterizes well-done reports. The sources are literature reviews and reflexivity statements. Most researchers, however, have only a limited awareness of the importance of being clear about the sources of sensitizing concepts and other notions that become part of research coding schemes. Sensitizing concepts are notions that researchers identify before beginning their research and that help researchers notice and name social processes that they might not have noticed otherwise ( Blumer, 1986 ). Other researchers wait until data analysis to begin to identify concepts that they may use as codes and that may also become core concepts that organize findings. Either approach is acceptable and depends on purpose and methodologies.

During data collection, researchers reflect on what they are learning, typically talk to other researchers about their emerging understandings, and read relevant research and theory to enlarge and deepen their understandings. Researchers also keep fieldnotes that are a form of reflection. Based on their various reflections, researchers can reformulate interview and research questions and formulate new ones, do within—and across—case comparisons while in the field, and develop new insights into the meanings of the material.

Also, while in the field, researchers identify promising patterns of meanings and identify tentative core concepts, sometimes called categories , which are ideas that organize the copious material that they amass. Once researchers identify tentative core concepts, they seek to test whether they hold up, and, when they do, they further develop the patterns and concepts. Sometimes researchers think they have “struck gold” when they identify a possible core concept or pattern, only to find that the data—or metaphorical vein of gold—peter out (Phyllis Stern, personal communication, November 2002). They then go on to identify and follow-up on other concepts and patterns that show promise of becoming viable.

Core concepts become viable when researchers are able to dimensionalize them ( Schatzman, 1991 ) through selective coding ( Corbin & Strauss, 2008 ). This means that researchers have found data that show the multiple facets of concepts, such as patterns and exceptions to any general patterns. Authors may use other terms to describe what they did, such as thematic analysis. What is important is to describe the processes and produces; and what researchers call them is of less importance.

Core concepts may begin as sensitizing concepts. Researchers sometimes identify, name, and code core concepts through notions that are part of their general stores of knowledge but were not part of the literature review or reflexivity statement. Glaser (1978) called the practice “theoretical sensitivity.” The names researchers choose may be words or phrases informants have used. However derived, core concepts are central to the organization of findings ( Gilgun, 2012 a ).

At some point, data collection stops, but analysis does not. Researchers carry analysis that occurred in the field into the next phases of the research. Immersion at this point means that researchers read and code transcripts of interviews, observations, and any documentary material they find useful. They carry forward the core concepts they identified in the field. An example of a core concept is “resilience,” which in my own research organized a great deal of interview material. The concept of resilience has been an organizing idea in several of the articles I have written and plan to write ( Gilgun, 1996 a ; 1996 b ; 2002 a ; 2002 b ; 2004 a ; 2004 b ; 2005 a ; 2006 , 2008 ; 2010 ; Gilgun & Abrams, 2005 ; Gilgun, Keskinen, Marti, & Rice, 1999 ; Gilgun, Klein, & Pranis, 2000 ).

Corbin and Strauss (2008) stated that selective coding helps researchers to decide if a concept can become a core concept, meaning it organizes a great deal of data that have multiple dimensions. An example of dimensionalization is a study of social workers in Australia whose clients were Aboriginal people. The researchers identified several core concepts, among them critical self-awareness ( Bennet, Zubrzycki, & Bacon, 2011 ). The dimensions of critical self-awareness included understanding motivations to work with Aboriginal people, fears of working with Aboriginal people, and personalization and internalization of the anger that some Aboriginal people express.

Like many other researchers, Bennet et al. (2011) were not working within an explicit Chicago School tradition. They therefore do not use terms such as core concepts, dimensionalization, and selective coding. Instead, they described their procedures as thematic analysis, conceptual mapping, and a search for meaning. However, they did use the term “saturation,” which is part of the Chicago School tradition.

A single core concept or multiple related core concepts compose research reports. The Bennet et al. (2011) article, for example, linked multiple core concepts. The authors showed how critical self-awareness leads to meaningful relationships that in turn connect to “acquiring Aboriginal knowledge” (p. 30).

With viable core concepts and rich data, researchers are positioned to present their findings in ways that are memorable and interesting; that is, with “grab” ( Glaser, 1978 ). “Grab” requires compelling descriptive material: excerpts from interviews, field notes, and various types of documents, as well as researchers’ paraphrases of these materials. An example of a research report with grab is Irvine’s (2013) account of her study of the meanings of pets to homeless people. She provided vivid descriptions of her interactions with the participants and compelling quotes that show what pets mean. Here, an example from Denise’s account of her relationship with her cat Ivy:

I have a history with depression up to suicide ideation, and Ivy, I refer to her as my suicide barrier. And I don’t say that in any light way. I would say, most days, she’s the reason why I keep going.... She is the only source of daily, steady affection and companionship that I have. (p. 19)

These and other quotes, as well as Irvine’s well-written, detailed descriptive material, show what grab means.

Grab equates with excellence in writing. Irvine’s (2013) article is an example. In terms of the grab of her article, her work is in the Chicago School tradition. She wrote in the first person. She told complete stories in which she quoted extensively from the interviews, described the persons she interviewed and the settings in which she interviewed them, and provided biographical sketches. Robert Park and Ernest Burgess, both of whom trained generations of graduate students in qualitative research at the University of Chicago in the first quarter of the twentieth century, held seminars on the use of literary techniques, such as those used in novels and autobiographies, in writing up research ( Bulmer, 1984 ; Gilgun, 1999 d ; 2012 a ). These educators wanted researchers to report on their “first-hand observation.” Park told a class of graduate students to

[g]o and sit in the lounges of the luxury hotels and on the doorsteps of the flophouses; sit on the Gold Coast settees and on the slum shakedowns; sit in the Orchestra Hall and in the Star and Garter Burlesk. In short, gentlemen [sic], go get the seat of your pants dirty. ( McKinney, 1966 , p. 71)

Park suggested to Pauline Young (1928 ; 1932) to “think and feel” like the residents of Russian Town, the subject of her dissertation, published in 1932 ( Faris, 1967 ). Irvine’s work shows these qualities. She immersed herself in the settings, she conducted in-depth interviews, and she conveyed her first-hand experiences in vivid terms.

The Chicago School also encouraged students to write in the first person. A good example is a report by Dollard (1937) , who was concerned about the racial practices of the Southern town where he was doing fieldwork. He said he was afraid that other white people watched as he talked to “Negroes” on his front porch, when he knew that custom regarding the “proper” place of “Negroes” was at the back door. He wrote

My Negro friend brought still another Negro up on the porch to meet me. Should we shake hands? Would he be insulted if I did not, or would he accept the situation? I kept my hands in pockets and did not do it, a device that was often useful in resolving such a situation. (p. 7)

This description is a portrait of a pivotal moment in Dollard’s fieldwork, and it is full of connotations about the racist practices of the time ( Gilgun, 1999 d ; 2012 a ).

Irvine (2013) also wrote in the first person. Here’s an example:

I met Trish on a cold December day in Boulder. She stood on the median at the exit of a busy shopping center with her Jack Russell Terrier bundled up in a dog bed beside her. She was “flying a sign,” or panhandling, with a piece of cardboard neatly lettered in black marker to read, “Sober. Doing the best I can. Please help.” (p. 14)

These two excerpts illustrate a methodological point Small (1916) made in his chapter on the first fifty years of sociological research in the United States: namely, the importance of going beyond “technical treatises” and providing first-person “frank judgments” that can help future generations interpret sociology. Without such contexts, “the historical significance of treatises will be misunderstood” (p. 722). Throughout his chapter, Small wrote in the first-person and provided his views—or frank judgments—on the events he narrated. From then until now, research reports in the Chicago tradition are vivid and contextual, conveying to the extent possible what it was like to be persons in situations.

There are many other examples of well-done research reports. Eck’s (2013) article on never-married men includes the basic elements that are present in almost all reports based on qualitative methods. It is transparent in its procedures, situated within scholarly traditions, well-organized, vivid, and instructive both for those new to qualitative research and for long-term researchers like me. The other articles I cite in this chapter also show many desirable qualities in research reports.

Research Report Sections

The main sections of standard reports based on qualitative methods are the same as for articles based on other types of methods: Introduction, Methods, Findings, and Discussion. The American Psychological Association (APA) manual (2009) provides information on what goes into each of these sections. Research reports in sociology journals follow a similar format, although the citation style is slightly different. The American Sociological Association uses first and last names in the reference section, a practice I support. In articles based on qualitative approaches, researchers sometimes change the names of sections, add or omit some, or reorder them. When changes are made, the general guideline is whether the changes make sense and are consistent with the purpose of the research. As Saldaña (2003) pointed out, researchers choose how to present their findings on the basis of credibility, vividness, and persuasive qualities and not for the sake of novelty. Because some articles report findings as fictionalized accounts, poetry, plays, songs, and performances (including plays), it makes sense that the sections on these findings vary from the standard format that I discuss here.

Although there are no rigid rules about how to write journal articles based on qualitative research, much depends on the methodological perspectives, purposes of the research, and the editorial guidelines of particular journals. For example, if researchers want to develop a theory, it is important to be clear from the beginning of the article to state this as the purpose of the research. The entire article should then focus on how the authors developed the theory. Research and theory cited in the literature review should have direct relevance to the substantive area on which the authors theorized. The methods section should explain what the researchers did to develop the theory. The findings section should begin with a statement of the theory that the researchers developed. The rest of the findings section should usually be composed of three parts. The first is composed of excerpts from those data that support the concepts of the theory. This is the grounding of the theory in something clear and concrete. The second is the authors’ thinking or interpretation of the meanings of each of the concepts. The third is an analysis of how the theory contributes to what is already known, such as how the findings elaborate on and call into question what is known. Thus, a research report on the development of a theory should contain a lot of scholarship that others have developed.

A report based on narrative principles or one based on an ethnography should contain copious excerpts from interviews, citing less scholarship than an article whose purpose is to develop theory. However, it is good practice to bring in related research and theory in the results section when this literature helps in interpretation, when findings have connections to other bodies of thought, and when findings are facets of a larger issue. In my now older publication on incest perpetrators ( Gilgun, 1995 ), the editors suggested that I show that when therapists engage in sexual relationships with clients, they are engaging in abuses of power similar to those of incest perpetrators. I was at first indignant that the editors wanted me to do even more work on the article, but I soon was glad they did. It is important to show that incest or any human phenomenon is not isolated from other phenomenon but is part of a larger picture. Doing so fit my purposes, which was to show how to do theory-testing/theory-guided qualitative research. Showing how findings fit into related research and theory is part of this type of research.

Whenever researchers are ready to submit an article for publication, it is wise to read recent issues of journals in which they would like to publish. If they can identify an article whose structure, methodologies, and general purpose are similar to theirs, they could study how those authors presented their material. If, for example, in a report on narrative research, the introductory material is relatively brief, and the findings and discussion sections compose most of the pages, researchers would do well to format their articles in similar ways. I study journals in which I have interest and model much of my own articles after those published in these journals. I make sure, however, that I cover topics that in my judgment are important to cover.

Prior Research and Theory

In my experience, something as simple as the place of prior research and theory can get complicated in the writing of reports based on qualitative research, even when the purpose of the article is primarily descriptive and is not to construct an explicit theory. In general, related research and theory literature can be presented at the beginning of a report as part of a review of pertinent research and theory, in the findings section when prior work helps in the interpretation and analysis of findings, or in the discussion section, where authors may reflect on how their findings add to, undermine, or correct what is known and even add something new.

Readers expect and journal editors typically want articles to begin with literature review, with some exceptions. A perusal of journals that publish qualitative studies shows this. Yet there are exceptions. Valásquez (2011) began her report on her encounter with scientology with an extended and rather meandering first-person narrative. Her literature review began toward the end of the article. She tailored the review to the report that preceded it. In this article and others, the literature review helped in the interpretation of findings and helped to situate the report in its scholarly contexts. In other articles, the literature review appears in the introductory section. This sets the scholarly context of the research, highlights the significance of topics, and identifies gaps in knowledge. Neither authors nor reviewers should have rigid expectations about where the scholarship of others belongs. It belongs where it makes the most sense and has the most impact.

For many, the placement of literature reviews seems self-evident. Yet, some well-known approaches, such as grounded theory, can set authors up for confusion about where the literature review belongs. This can result in delays in writing up their results. The procedures of grounded theory are open-ended and designed to find new aspects of phenomena—often underresearched—and then develop theories from the findings. At the outset of their work, researchers cannot anticipate what they will find. Therefore, teachers such as Strauss and Glaser advised students not to do literature reviews until they had identified basic social processes that become the focus of the research ( Covan, 2007 ; Glaser & Strauss, 1967 ).

How, then, do researchers write up research reports when they are doing an open-ended study that, by definition, will culminate in unanticipated findings? Do they write their reports as records on how they proceeded chronologically, or do they follow APA style and the dominant tradition that says the literature review comes first? For the most part, I follow the tradition, as, apparently, do most researchers. However, to structure reports in this way sometimes feels strained and artificial. I would prefer to write a more chronological account, in which I can share with readers the lines of inquiry and procedures I followed. The literature review at the beginning of the report, therefore, would be brief. The methods section is quite detailed in how I went about developing the theory. The findings section would have the three-part format I discussed earlier: statement of the theory, presentations of excerpts that support assertions that certain concepts compose the theory, my interpretation of the meanings of the concepts and the excerpts that support them, and then the use of related research and theory to further develop the theory and to situate it in its scholarly traditions.

In all but one of the research reports that I have published, I did the literature after I had identified findings. The one exception was research I did based on the method of analytic induction, in which researchers can use literature reviews to focus their research from the outset ( Gilgun, 1995 , 2007 ). In this research, I used concepts from theories on justice and care to analyze transcripts of interviews I had previously conducted on how perpetrators view child sexual abuse. Even though I was familiar with the transcripts, I found that the concepts of justice and care and their definitions sensitized me to see things in the material that I had not noticed as I did data collection and during previous analyses of the data.

Furthermore, in writing up the results, I brought in research that was not part of the literature review to help me to interpret findings and to show how findings fit with and added to what was already known. I did not place this material in the introductory literature review. Placing related research and theory as parts of the results and discussion sections is common and may be necessary in articles that are reporting on a theory that the authors developed. For descriptive studies whose purpose is not theory-building, such as ethnographies, some findings sections include the addition of research and theory not present in the introductory section. Often, however, authors do not follow this pattern. An example is found in Ahmed (2013) , who described how migrants experience settling into a new country. She presents excerpts from interviews and her interpretation of them, including organizing them into a typology, but she does not bring additional research and theory into her interpretations.

Tensions can arise between how much space to give to literature reviews and how much to allot to presentation of informants’ accounts/findings ( Gilgun, 2005 c ). This happened in the most recent article I co-wrote, which is on mothers’ perspectives on the signs of child sexual abuse ( Gilgun & Anderson, 2013 ). We believed the literature review was important because it not only set up our research but summarized a great deal of information that was important to our intended audience of social service professionals. We also wanted to anticipate the expectations of reviewers and the journal editor. Yet, we put much effort into making the literature review as concise as possible in order to have reasonable space for findings. We wrote the literature review before we did data analysis. When we wrote up the results, the first draft was probably three times longer than any journal article could be.

We had written case studies first to be sure that we understood each case in detail. We had wanted to share what the women said in the kind of detail that had helped us deepen our own understandings, so we cut back on the case material. The article was still too long. We decided to exclude the few instances we had in which women knew of the abuse but tried to handle it themselves or did not believe the children when told. We did more summarizing of the literature review. We eliminated many references.

After much effort, we finally had a manuscript that was the required length of twenty-two pages. It included a literature review that set up the research in good form, an adequate accounting of the method, and findings that conveyed with grab the complexities of the signs and lack of signs of child sexual abuse. We wove points made in the literature review into our interpretations, yet we had to leave out important patterns for the sake of space. The editor’s decision was a revise and resubmit, which we did. The main recommendation was to elaborate on applications. This was a great suggestion, and we dug deep to think about this. We are pleased with the results. We had to do further reading on topics we had not anticipated at the onset of our project, and we squeezed in a few new citations in the discussion section that related to implications of the research. This additional material greatly enhanced the meanings and usefulness of the research.

There is much more to say about qualitative research and literature reviews. Sometimes researchers get stuck, as I have more than once. I have research that I have not yet published because I have been unable to figure out how to do the multiple literature reviews I think I must show how my theory builds on, adds to, and challenges what is already known. I have written up this research as conference papers, where expectations about literature reviews are more relaxed ( Gilgun, 1996c , 1998 , 1999c , 2000 ). One of these. papers was on a comprehensive theory of interpersonal violence ( Gilgun, 2000 ). I wanted to write my theory first and then show how the findings contribute to what is already known. Doing so doesn’t seem so outlandish today, and I now can imagine writing it up exactly as I would want to. At the same time, I wonder if I would? I really don’t know if any journal that would publish a theory of violence would also accept an article that places a literature review after findings. Furthermore, my writing up of the theory would take so many pages that I would not have enough space to do a comprehensive literature review. As of today, the theory I am developing has links to sixteen or more bodies of literature. No way can I publish a journal-length article that will accommodate that much research and theory!

So, here I am, many years into the development of a comprehensive theory, still reflecting on how to create journal articles out of my analysis. I have published many articles in social media outlets exploring ideas that are the basis for the theory. I have put these articles into collections that are available on the internet ( Gilgun, 2012 b ; 2012 c ; 2013 a ). The theory is so complex that writing bits and pieces over the years and having a place to put them have been very helpful.

Finally, some articles may cite few if any related research and theory. This may fit articles whose purpose is to convey lived experience that stands on its own. These articles feature performances, plays, autoethnographies, fictionalized accounts, poetry, and song, among others. Egbe (2013) wrote two poems that she explained were accounts of her experiences of doing research in Nigeria with young smokers. She said she was “dazed by the vast opportunity this method gives a researcher to dig deep into a research problem and be submerged into the world of participants” (p. 353). Her two-page article is composed of two poems and her explanation. The article showed grab, evidence of immersion, experiences in contexts, and multiple perspectives. Her work, therefore, followed well-established guidelines for writing up qualitative research. Egbe not only omitted a literature review, but she did not write about how to use the results of her research, assuming that its uses are self-evident. Obviously, she thought a literature review unnecessary; the reviewers and journal editors agreed with her.

Reflexivity Statements

A growing number of journals encourage researchers to include reflexivity statements in research reports. Researchers may place these in the introductory material of an article, after the literature review and before the methods section; this probably is the most important place to put them because reflexivity statements often influence the focus and design of the research, including the choice of sensitizing concepts and codes. Reflexivity statements may also appear in the methods and findings and methods sections when important. Reflexivity statements are accounts of researchers’ experiences with the topic of research; accounts of their expectations regarding informant issues and their relationships to informants, especially in regard to power differentials and other ethical concerns; and accounts of their reflections on various issues related to possible experiences that informants may have had. They also may include the experience they had while participating in the research ( D’Cruz, Gillingham, & Melendez, 2007 ; Presser, 2005 ). My article on doing research on violence is an extended reflexivity statement ( Gilgun, 2008 ). There appears to be no standard content for reflexivity statements and no standard places for them to appear. Personal and professional experiences and reflections on power differentials may be the emergent standard. Whatever decisions researchers make about reflexivity statements, they alert audiences to researchers’ perspectives, which can be helpful to readers as they attempt to make sense of research reports.

An example of a reflexivity statement is found in Winter (2010) work. Winter is a practitioner turned researcher who had a previous relationship as a guardian ad litem with the children with whom she later conducted the research that she was reporting. Winter was reflexive about the implications of her prior relationship with these children. I imagine, based on my own experience, that she put only a fraction of her thinking into her article. Not only did she write in her reflexivity statement that she had a prior relationship with the children, but she also wrote about the ethical issues involved.

Ethical issues have a place in reflexivity statements. I have run into ethical questions over the course of my research career. One situation that stands out is the encounter I had with a mother and her eleven-year-old daughter who had participated in my dissertation research on child sexual abuse ( Gilgun, 1983 ). The mother cried and told her daughter how sorry she was that she had been unable to protect her from sexual abuse. The girl was touched but did not seem to know what to do. I suggested that she go stand by her mother. When she got close, the mother and daughter hugged each other and cried. This is a significant event with ethical implications that I included in the findings section of my dissertation and in a subsequent research report ( Gilgun, 1984 ). The ethical issue is, first, whether I should have stepped out of my role as detached researcher and guided the girl to go to her mother, and, second, whether I should have made my blurring of boundaries public by publishing them.

As far as the placement of reflexivity statements, the initial statement has a logical location after the literature review because the reflexivity statement contributes to the development of the research questions, the identification of sensitizing concepts, the interview schedule, and the overall design of research procedures. Accounts of ongoing reflexivity could be part the findings section and of the discussion section. Reflexivity statements are not a standard part of research reports, but they can contribute to readers’ understandings of the research.

Along with the literature review, reflexivity statements contribute to practical and applied significance statements and may also help to identify gaps in knowledge. Literature reviews and reflexivity statements contain key concepts. The concepts that researchers define at the end of introductory sections typically become codes during analysis, although researchers may not label the concepts as codes either in the introductory section or in the methods section. I am unsure why such labeling has not become routine. When concepts carry the label code , this clarifies where codes come from. Without naming codes and stating where they come from, much of analysis is mystified. Many reports read as if the codes appear out of nowhere during analysis. Even Glaser’s (1978) notion of theoretical sensitivity mystifies the origins of codes. How, for example, do researchers become theoretically sensitive? What if researchers are beginning their scholarly careers? How theoretically sensitive are they ( Covan, 2007 )? What are the implications for the quality of the analysis?

Research Questions, Hypotheses, and Definitions

The final part of the introductory section of a research report is devoted to research questions, hypotheses to be tested (if any), and definitions of core concepts. In general, in qualitative research, hypotheses are statements of relationships between concepts. Theories usually are composed of two or more hypotheses, although, at times, some researchers may use the term theory to designate a single hypothesis ( Gilgun, 2005 b ). Concepts are extractions from concrete data. Sometimes concepts are called second-order concepts and data first-order concepts .

Research questions may be absent. In their place are purpose statements that make the focus of the report clear. Hypotheses are rarely present in qualitative research. When they are, the purpose of the research is to test them and typically to develop them more fully. This type of research has in the past been called analytic induction ( Gilgun, 1995 e), whereas a more up-to-date version of qualitative hypothesis testing and theory-guided research is called deductive qualitative analysis ( Gilgun, 2005 d ; 2013 ). Analytic induction and deductive qualitative analysis are part of the Chicago School tradition.

Methods Section

Most methods sections for reports based on qualitative approaches have the same elements as any other research report. Descriptions of the sample, recruitment, interview schedule, and plans for data analysis are standard. The APA manual provides guidelines ( American Psychological Association, 2009 ) that fit many types of qualitative research reports. However, reports based on autoethnographies, poetry, and performances may have brief or no methods sections. As is clear by now, the report’s contents depend on the purposes and methodologies of the research and on the editorial requirements of journals.

Accounts of Methodologies

In writing up qualitative research, methods sections usually contain a brief overview of the research methodology, which is the set of principles that guided the research. The following is an account of the methodology used in a research report on cancer treatment in India:

For this project we drew upon interpretive traditions within qualitative research. This involved us taking an in-depth exploratory approach to data collection, aimed at documenting the subjective and complex experiences of the respondents. Our aim was to achieve a detailed understanding of the varying positions adhered to, and to locate those within a broader spectrum underlying beliefs and/or agendas. ( Broom & Doron, 2013 , p. 57)

Sometimes, statements of methodology are much more elaborate, but in research reports, such a statement is sufficient, again depending on the editorial policies of particular journals. A few citations, which this article had, round out an adequate statement of methodology.

However, many reports are written in a clear and straightforward way with scant or no account of methodologies. Examples are the work of Eck (2013) and Spermon, Darlington, and Gibney (2013) . These kinds of well-done write-ups might eventually be considered generic. Spermon et al. said their study was phenomenological, which sets up assumptions that the report will be primarily descriptive. In actuality, the intent was to develop theory. Such mixing of methodologies may be the wave of the future; in many ways, distinctions between phenomenological studies whose purposes are descriptive and those whose purposes are to build theory are blurred. Such blurring may have been the case for decades because it is possible and often desirable to build theories based on phenomenological perspectives; that is, in-depth descriptions of lived experience. However, authors are wise to state in one place what their methodologies are and how they put them to use, such as for descriptive purposes or for theory-building.

Description of Sample

Placing descriptions of sample size and the demographics of the sample in the methods sections is typical. As mentioned earlier, evaluation of sample size depends on the depth and breadth of the study. The more depth a study has, the smaller the number of cases can be. The more breadth and the sharper the focus, the larger sample sizes typically are. Samples on which a study is based must provide enough material on which to base a credible article. A sample size of one may be adequate if researchers show their work demonstrates the basic principles of almost all forms of qualitative research: perspectives of persons who participate in the research, researcher immersion into the settings or the life stories of persons interviewed, multiple perspectives, contextual information of various types, and applications. Autoethnographies often have an n of one, but joint autoethnographies are possible. Ethnographies may not give a sample size, as was the case in the performance ethnography of Valásquez (2011) who wrote in the first person about her experience with scientology. In her first-person ethnography, Irvine (2013) also did not mention sample size. She said that the narratives she used for the article were from a larger study on the meanings of animals to people who have no homes. She did not describe the usual demographics of age, gender, social class, and ethnicity.

Most articles describe the demographics of the sample. In a recently accepted article ( Gilgun & Anderson, 2013 ), I saw no relevance in mentioning the size of the larger sample from which we drew in order to tell the stories of how mothers responded to their learning that their husbands or life partners had sexually abused their children. We included an exact count of the larger sample because we assumed that it would be the journal’s expectations. We also gave particulars of the demographics. Except for social class and ethnicity, we saw little relevance for the other descriptors. These status variables were relevant to us because most of the sample was white and middle or upper class. This is important because much research on child sexual abuse is done with poor people, and there are stereotypes that poor families and families of color are more likely to experience incest than are white middle and upper class families. Overall, as with some other issues related to writing, the adequacy of the sample description depends on the methodological principles of the research and the journal’s editorial policies.

Recruitment

Accounts of recruitment procedures are important because researchers want to show that their work is ethical. Respect for the autonomy or freedom of choice of participants needs to be demonstrated. In addition, often the persons in whose lives we are interested have vulnerabilities. To show that the research procedures have not exploited these vulnerabilities is part of ethical considerations. Most articles have these accounts. Furthermore, when there are accounts of recruitment procedures, it becomes obvious why the sample is not randomly selected. Irvine’s (2013) account of recruitment is exemplary. She recruited through veterinary clinics that took care of the pets of homeless persons. She did not approach potential participants herself. Doing so risked making refusals difficult. The staff informed persons of the research and its purposes. If individuals said they were interested, they gave permission for the staff to give their names to researchers. The research interviews took place in the clinics.

The ethics of recruitment revolve around values, such as respect for autonomy, dignity, and worth. Other ethical issues that are important to mention in reports include the use of incentives for participation. Although many human subjects committees now require monetary incentives for participation, this has ethical implications. Irvine (2013) solved this by giving gift cards after the interviews were completed. Reports on ethical issues have a place in methods sections.

Data Collection and Analysis

Accounts of data collection and analysis are part of the methods section. Data collection procedures should be detailed for many reasons. Primary among them is the need for transparency in terms of the ethical standards the researchers followed, as well as the need to allow for replication of the study. Such details also provide guidelines for others who might be interested in using the methods. In addition, there are many different schools of thought and procedures for each of the methods used with the three general types of data collection: interviews, observations, and documents. It is helpful to state which particular data collection procedures the researchers used. Researchers often provide examples of the kinds of questions asked and procedures used for recording observations and excerpts from documents. Some researchers may omit such an accounting, as with some autoethnographies and articles that turn research material into performances.

How researchers analyzed data is part of the methods sections. As with data collection, there are so many types of analysis that researchers need to describe the particular forms that they used. For figuring out how to report on data analysis, researchers would do well to study articles in journals in which they want to publish. Irvine (2013) used a method of analysis I have never heard of called “personal narrative analysis” (p. 8). She gave enough detail to provide the general idea of what she did and a sufficient number of citations for additional information.

The level of detail can vary. In some sociology journals, for example, researchers may say little about analysis and sometimes little about data collection. This is because the journal editors, reviewers, and those who publish in and read the articles have assumptions that they for the most part take for granted. Even in these journals, however, researchers may want to account for their analytic procedures, especially if they are writing on topics outside of what is usual in such journals.

Other journals require a great deal of detail. In those instances, researchers first decide what they think is essential and then shape their accounts to fit what appears to be usual practice in the journal. The following paragraphs describe data analysis in a recently accepted article on signs of child sexual abuse in families ( Gilgun & Anderson, 2013 ).

Data Analysis

In the analysis of data, the first author read the transcripts multiple times and coded them for instances related to disclosures of child sexual abuse and associated signs of the abuse, such as how and when the women first learned of the abuse or suspected it was occurring in their families, their responses, and their reflections on the signs of abuse they might have missed, as well as child and perpetrator behaviors that they did not realize were related to child sexual abuse. Their initial and longer term responses and reflections were also coded. The second author independently read and coded about one-third of the transcripts using this coding scheme to arrive at a 100 percent agreement.

Sources of the codes were our professional experiences in the area of child sexual abuse, the review of research, and the first author’s familiarity with the content of the interviews because she had been the interviewer. These codes served as sensitizing concepts, which, as Blumer (1986) explained, are ideas that guide researchers to see aspects of phenomena that they might otherwise not notice. Although altering researchers’ ideas to what might be significant serves an obvious useful purpose, sensitizing concepts might also may blind researchers to other aspects of phenomena that might be important. Therefore, we also used negative case analysis, which is a procedure that guides researchers to look for aspects of phenomena that contradict or do not fit with emerging understandings. In this way, researchers are positioned to see patterns, variations within patterns, exceptions, and contradictions in findings ( Becker et al., 1961 ; Bogdan & Biklen, 2007 ; Cressey, 1953 ; Lindesmith, 1947 ).

As we wrote this section, we were aware of the limited space that we had to fill. Yet we were committed to accounting for where our codes came from for reviewers and editors who may be unfamiliar with pre-established codes. As discussed earlier, many reports are written as if codes appear by magic. We decided that, in this report, we would be as clear as possible about where our codes came from. We also reasoned that we would have to call on the authority of well-respected methodologists if reviewers and editors had questions about what we had done. Furthermore, we were aware of the dated nature of the references; we could do nothing about that because there has not been much written recently about pre-established codes. I have written about this quite a bit, but as one of the authors, I not only had to be anonymous during the review process, but I could not be the sole authority.

Generalizability

Many reviewers and editors have questions about the generalizability of the results of qualitative research. Authors themselves sometimes question the generalizability of their own findings. That’s why it remains important to provide clear guidelines in research reports about how the authors view the usefulness of their findings. The following ideas may be helpful to authors as they write their reports and to reviewers who are positioned as gatekeepers. The results of qualitative research are not meant to be generalized in a probabilistic sense. But because dropouts and refusals limit the randomness of samples, most forms of research can’t be generalized in a probabilistic sense.

Conversely, as Cronbach (1975) wrote almost forty years ago, the results of any form of research are working hypotheses that must be tested in local settings. Thus, the applicability of qualitative or any other kind of research can be demonstrated only through attempts at application. Do the findings illuminate other situations? Do the results provide researchers, policy makers, and direct practitioners with ideas on how to proceed? Those who apply the research expect to have to adjust findings to fit particular new situations. Many researchers and some journal editors and reviewers know through common sense and everyday experience how to use the results of qualitative research. Our personal lives are extended case studies. What we learn in one situation, we carry over into another. We know we have to test what we have learned in past situations for fit with new situations. If we do not, we impose our ideas on situations that may demand new perspectives. This common practice of applying results to all situations is disrespectful of local conditions and autonomy of persons. We want to avoid such disrespect in how we suggest readers use the results of our research.

Trustworthiness and Authenticity

Pointing out the trustworthiness of procedures and the findings that result from them sometimes are parts of methods sections. Related to trustworthiness are issues of authenticity ( Guba & Lincoln, 2005 ). Both trustworthiness and authenticity arise from immersion, seeking to understand the perspectives of others in context, reflexivity, and seeking multiple points of view. Researchers who have applied these principles will produce reports that are trustworthy and authentic. In addition, the reports will have grab. Extended discussions related to these issues are beyond the scope of this chapter and the scope of research reports as well.

I get more requests for revisions of methods sections, especially for accounts of data collection and analysis, than for any other parts of a manuscript. This is not surprising, given the multiple possible variations. I never know who the reviewers will be and what their expectations are. I rely first on my beliefs about what I want in the procedures section and then I study articles the journal has already publishes. I include what journal editors appear to expect, but I also add information that I think is important, even when it is not part of what I see in methods sections.

Findings Sections

Findings sections in research reports include both descriptive and conceptual material. Descriptive material is composed of researchers’ paraphrasing and summarizing of what they found and excerpts from interviews, fieldnotes, and documents. The descriptive material, at its best, is detailed and lively; it not only is informative, it has grab. This material contributes to understandings of human experiences in context. In addition, descriptive material is the basis of researchers’ theorizing and it also provides documentation and illustrations of assertions that researchers make.

Conceptual material comprises the analysis and is made up of inferences such as the general statements, concepts, and hypotheses that researchers develop from the material (data). One way to think about the relationship between descriptive and conceptual material is to think of descriptive material as composed of first-order concepts and conceptual material as composed of second-order concepts. Each type depends on the other. Credible conceptual material is based on descriptive material, some of which is contained in the article. Qualitative research yields mountains of data, a fraction of which can be placed into a published article.

As with other sections of research reports, findings sections have many possible variations that depend on the purpose of the research and the methodologies on which the research is based. Thus, the findings can range from heavily descriptive to heavily conceptual. Heavily conceptual research reports arise from research whose purpose is theoretical, in which researchers set out to test, refine, reformulate, or develop theory. Theoretical reports require some descriptive material to show the basis of theoretical statements, but they are often relatively short on descriptive material.

Reports that are primarily descriptive are composed of excerpts from data. Theoretical material appears in often subtle ways, such as in the form of concepts that organize findings. Irvine’s (2013) study of homeless people and their pets is largely descriptive, composed of excerpts from the interviews and Irvine’s paraphrases and narration of what she did, how, and when. The findings were narrative case studies based on interviews and observations. The details of the narratives were vivid and had the kind of grab that Glaser (1978) recommended. They showed multiples perspectives and variations on what it meant to homeless informants to have pets in their lives. The first three pages were a review of relevant literature and a presentation of method. The last five pages were a discussion of the findings.

As lengthy as the descriptive material is, conceptual material frames the entire report. In the literature review, Irvine introduced notions of positive identity, generativity, and redemption. She used them to analyze her data and organize findings, which were the narrative case studies. She used the concept of redemption as the core or organizing concept, going into some detail about how the research material supports the significance of this idea of pets as redemptive for homeless people.

This analysis is based squarely on the descriptive material. For instance, Irvine wrote that in the stories she presented in her article, “animals provide the vehicle for redemption.” She illustrated this point with a quote from one of the narratives and then reminded readers that the narratives “contain variations on the theme” of “ life is better because this animal is in it ” (p. 20; emphasis in original). Readers do not take this on faith because the basis of this general statement in presented multiple times in the case studies. Irvine has much more material on which she based these ideas, but there is not enough room in a journal-length article to show all of her evidence.

An example of an article that is theoretical in purpose and short on descriptive material is found in the work of Cordeau (2012) . She developed a grounded theory of the “transition from student to professional nurse” when student nurses work with “mannequins as simulated patients” (p. 90). Based on interviews, observations, and reports that the students wrote on their clinical experiences, the study was composed of about 10 percent descriptive material. This material included excerpts interviews and student reports. In the results section, she used this descriptive material to illustrate and possibly document the grounded theory she constructed. The theory’s “core category” was “linking,” which had four components, called properties. She documented the properties, primarily with her own thinking about her research material and also with excerpts from interviews, observations, and student reports.

Like Irvine’s (2013) study, the purpose of Cordeau’s (2012) work was applied where she wanted to build theory that would contribute to the development of clinical expertise in nursing students. She also devoted about one page of her study to applications.

Core Concepts

I’ve previously provided an extended discussion of core concepts. This section highlights some key points and illustrates them. Core concepts, often called core categories , organize findings. I prefer the term concept because concept is the term used in discussing theory, such as “concepts are the building blocks of theory,” and theory is one of several possible products of qualitative research. Researchers decide on which concepts are core in the course of analysis. Researchers are ready to write up their reports when they have settled on, named, and dimensionalized one or more core concepts. The terms “core concepts” and “core categories” are associated with grounded theory ( Charmaz, 2006 ; Corbin & Strauss, 2008 ), but they are useful in other types of qualitative research, such as interpretive phenomenology and narrative analysis. Core concepts both organize findings and, typically, bring together a great deal of information. The term “dimension” means that researchers account for as many aspects of the core concepts as they can in order to show the multiple perspectives and patterns that typically compose concepts.

In reporting on core concepts, I recommend that researchers name them, introduce them, describe them using excerpts from the research material, comment on them, and then situate each of the concepts and their commentaries within their scholarly contexts. As discussed earlier, this shows how the findings fit with what is already known, or add to, force modification of, or refute what is known. Although many researchers, do not situate findings in their scholarly contexts, they usually cover the other topics.

No matter how authors report findings, they should do so with grab. An example of a report exemplary for its grab is the work of Scott (2003) on what it means to be a professional with a physical disability. Scott began her article not with a literature review but with three reviewer comments on other articles she had written. She then stated that the present article was a response to these comments. She followed up with a description of three male students who waited to speak to her after class about her disability and the notion of embodiment that she discussed in class. She brought in related literature throughout the article. Through her own reflections, reports on how others have responded to her, reports on the accounts that three other women with disabilities gave to her as a person with cerebral palsy, and her literature review, Scott not only showed the meanings of disabilities to persons who have them, but also what others say about their own disabilities, what some people who are able-bodied say about women with disabilities, and how all of this connects to what is known about disabilities and to wide-spread beliefs about disabilities. Her article is full of grab, such as the header that read, “The Day I Became Human.” With the authors’ own experience as the centerpiece, this article exemplifies write-ups that demonstrate the meanings of lived experience in various contexts, immersion, grab, and implications for social action. The analysis she presented as part of her findings is exemplary.

In the production of quality research, no matter the type of write-up, there are no short cuts. Research reports based on poetry, for example, are held to the same standards as any other article: grab, immersion, lived experience in context, and implications for action. In addition, such research reports typically locate themselves within social and human sciences traditions. Furman’s (2007) reflections and analysis of poetry that he wrote over the course of many years provide an example of how poetry can be used in qualitative analysis. This kind of research is a type of document analysis. In performance studies, researchers create a theater production of informant’s accounts of their experiences whose purpose is to transform audiences and move them to action ( Saldaña, 2003 ). The performances are the equivalent of research reports and when they are effective, they have the four characteristics of qualitative research under discussion.

Discussion Sections

In traditional research reports, the discussion section follows the results section. In discussion sections, authors reflect on findings, including what the findings are, how findings contribute to understandings of phenomena of interest, the lines of inquiry the results open up, and implications for policy and practice. Other generic topics to consider are those related to the focus of the journal. For example, if the journal’s focus is related to health, then authors show how findings are related to health.

Discussion sections present the author with opportunities to advocate for how his or her research can be used. The applied purposes of Irvine’s (2013) research come through when she devoted an entire page to make observations about implications. She pointed out how her research contributes to a transformation of images of homeless persons as isolated to images of them as engaged in relationships not only with their pets but with other persons, too. She noted that rehousing homeless persons requires a change in policy that would allow them to have pets. Furthermore, she said that caring for a pet “can turn things around” (p. 24).

In the discussion section I wrote with Anderson ( Gilgun & Anderson, 2013 ), we addressed methodological issues, such as the probable existence of other patterns in addition to those we identified and the nonrandom nature of our sample. We also acknowledged the difficulties in working with families in which child sexual abuse has occurred. Since qualitative researchers want to understand lived experiences, we had to prepare ourselves to deal effectively in research areas that are difficult emotionally for us as researchers. Although we may acknowledge the emotional challenges of some topics in reflexivity statements, discussion sections are opportunities for authors to acknowledge the difficulties of using the results we produce. In the article I wrote with Anderson, we made such an acknowledgment, one that we hoped would facilitate more effective practice. We wrote

Practitioners themselves may experience shock, rage, and disgust. The practice of neutrality, in its therapeutic sense, is important in these cases ( Gil & Johnson, 1993 ; Rober, 2011 ). Neutrality means that practitioners maintain their analytic stances while at the same time they remain attuned not only to service users but also to themselves. When practicing neutrality, service providers regulate their own emotional responses in order to remain emotionally available to service users. Neutrality also means that service providers remain open-minded so that they can hear stories that they may not expect to hear; in other words, to make room for the unexpected ( Rober, 2011 ). Attunement to inner processes is a form of reflection that can facilitate the development of trust between service users and providers. When providers are reflective, they are less likely to tune out, close down, and otherwise stop listening to what services users express. When they listen and hear what service users say, they are more likely to facilitate the best possible outcomes in difficult situations ( Weingarten, 2012 ).

Doing research on lived experience can be difficult for informants and for researchers. Acknowledgment of the implications of these difficulties for users of the research has a place in discussion sections.

In summary, most articles are fairly straightforward in their write-ups: focused literature reviews, reflexivity statements in many cases, clear statements of purpose, clarity about sources of research questions and/or hypotheses, identification and definition of key concepts, identification of codes the researcher develops from literature reviews and reflexivity statements, succinct accounting of methods, and findings organized logically by core concepts around which the researcher organizes the multiple dimensions of those concepts. Excellent writing makes articles interesting and accessible. Some kinds of write-ups deviate from these components, but they are held to the same standards of immersion, experiences in context, multiple perspectives, and implications for action and other applications. When authors have the good fortune to have a recommendation to revise and resubmit, suggestions for revisions often improve the quality of the article.

The seemingly endless variations that are possible in the write-up of qualitative research makes writing and reviewing manuscripts challenging, especially when compared to traditions in which rigid rules prevail. However, it is important that approaches to qualitative research continue to evolve to meet with our ever-changing understandings of human phenomena. The clarity and transparency of reports are the fundamental guidelines for making judgments about quality. I often tell my students that the guidelines for doing qualitative research are flexible, and what is important is to be clear about what you did, why you did it, and what you came up with.

The notion of grab is central to write-up. Since qualitative research seeks to understand lived experiences, it is logical that findings report on the lived experiences in vivid terms, replete with quotes from data. This is not to undermine the importance of analysis, but grab is possible even in write-ups that require a great deal of analysis. Grab becomes possible because researchers must provide the evidence for the theories and concepts they develop.

When there are questions about priorities related to informants’ voices, researchers’ interpretations, and prior research, I hope that authors, reviewers, and editors remember that as important as analysis and previous work may be, the voices of informants bring these other important parts of manuscripts to life. Researchers make decisions about whose voices take priority.

There is no one way to respond to these dilemmas. Authors must make their own decisions about what is important to them and then search for journals that will welcome what they want to convey. It’s important to consider pushing the boundaries and writing an article in a way that the researcher thinks will best convey his or her findings.

The importance of quality data, quality analysis, and “grab” are foundational. I began this chapter with a discussion of the balance between description and analysis. I then considered core concepts as organizers of findings, the place of literature reviews, styles of presenting methods and methodologies, and the balance between the voices of informants and researchers. I concluded with the many variations in types of reports that result from the various purposes that qualitative research projects can have. There are many different types of qualitative research and many styles of write-ups. This chapter may sensitize readers to enduring issues in the writing of research reports. Like qualitative research itself, there are multiple points of view on how to write up qualitative research.

Ahmed, A. ( 2013 ). Structural narrative analysis: Understanding experiences of lifestyle migration through two plot typologies.   Qualitative Inquiry , 19 , 231–243.

Google Scholar

American Psychological Association. ( 2009 ). The publication manual of the American Psychological Association (6th ed.). Washington, DC: American Psychological Association.

Google Preview

Becker, H. S. ( 1999 ). The Chicago School, so-called.   Qualitative Sociology , 22 (1), 3–12.

Becker, H. S. , Geer, B. , Hughes, E. C. , & Strauss, A. L. ( 1961 ). Boys in white: Student culture in medical school . Chicago: University of Chicago Press.

Block, E. ( 2012 ). “That’s what I see:” Enhancing AIDS intervention research through deep ethnography.   Qualitative Social Work 14 ( 4 ), 379–394.

Bogdan, R. C. , & Biklen, S. K. ( 2007 ). Qualitative research for education: An introduction to theories and methods (5th ed.). Boston, MA: Allyn & Bacon.

Bennet, B. , Zubrzycki, J. , & Bacon, V. ( 2011 ). What do we know? The experiences of social workers working alongside aboriginal people.   Australian Social Work , 64 (1), 20–37.

Blumer, H. ( 1986 ). The methodological position of symbolic interactionism. In H. Blumer (Ed.), Symbolic interactionism: Perspective and method (pp. 1–60). Berkeley: University of California Press.

Bulmer, M. ( 1984 ). The Chicago School of Sociology: Institutionalization, diversity, and the rise of sociological research . Chicago: University of Chicago Press.

Broom, A. F. , & Doron, A. ( 2013 ). Traditional medicines, collective negotiation, and representations of risks in Indian cancer care.   Qualitative Health Research , 23 (1), 54–65.

Charmaz, K. ( 2006 ). Constructing Grounded Theory: A practical guide through qualitative analysis . London: Sage.

Corbin, J. , & Straus, A. ( 2008 ). Basics of qualitative research (3rd. ed.). Thousand Oaks, CA: Sage.

Cordeau, M. A. ( 2012 ). Linking the transition: A substantive theory of high stakes clinical simulation.   Advances in Nursing Science , 35 (3), E90–E102.

Covan, E. K. ( 2007 ). The discovery of grounded theory in practice: The legacy of multiple methods. In A. Bryant & K. Charmaz (Eds.), The Sage handbook of grounded theory (pp. 58–93). Thousand Oaks, CA: Sage.

Cressey, D. R. ( 1953 ). Other people’s money . Belmont, CA: Wadsworth.

Cronbach, L. ( 1975 ). Beyond the two disciplines of scientific psychology.   American Psychologist , 30 , 116–127.

D’Cruz, H. , Gillingham, P. , & Melendez, S. ( 2007 ). Reflexivity, its meanings and relevance for social work: A critical review of the literature.   British Journal of Social Work , 37 (1), 73–90.

Dollard, J. ( 1937 ). Caste and class in a southern town . New Haven, CT: Yale University Press.

Eck, B. ( 2013 ). How never-married men make sense of an unintended identity.   Journal of Contemporary Ethnography , 42 (1), 31–63.

Egbe, C. O. ( 2013 ). Descriptive poems on a qualitative research with young smokers in southern Nigeria (2013).   Qualitative Inquiry , 19 (5), 353–354.

Ellis, C. ( 2009 ). Revision: Autoethnographic reflections on life and work . Walnut Creek, CA: Left Coast Press.

Faris, R. E. L. ( 1967 ). Chicago sociology 1920-1932 . Chicago: University of Chicago Press.

Furman, R. ( 2007 ). Poetry and narrative as qualitative data: Explorations into existential theory.   The Indo-Pacific Journal of Phenomenology , 7 , 1–9.

Geertz, C. ( 1973 ). The interpretation of culture . New York: Basic.

Gil, E. , & Johnson, T. C. ( 1993 ). Sexualized children: Assessment and treatment of sexualized children and children who molest . Rockville, MD: Launch Press.

Gilgun, J. F. ( 1983 ). The sexual abuse of the young female in life course perspective. 3058 . Ann Arbor, MI: Dissertations Abstracts International.

Gilgun, J. F. (1984). A non-coercive method of helping children discuss their own sexual abuse. Part II: An example of intervention by multiple qualitative case studies. Scribd.com . Retrieved from http://www.scribd.com/doc/117051267/A-Non-Coercive-Method-of-Helping-Children-Discuss-Their-Own-Sexual-Abuse .

Gilgun, J. F. ( 1995 ). “We shared something special”: The moral discourse of incest perpetrators.   Journal of Marriage and the Family , 57 , 265–281.

Gilgun, J. F. ( 1996 a). Human development and adversity in ecological perspective: Part 1: A conceptual framework.   Families in Society , 77 , 395–402.

Gilgun, J. F. ( 1996 b). Human development and adversity in ecological perspective, Part 2: Three patterns.   Families in Society , 77 , 459–576.

Gilgun, Jane F. (l996c November). The phenomenology of family violence. Paper presented at the Preconference Workshop on Theory Construction and Research Methodology, National Council on Family Relations, Kansas City, MO, November 5.

Gilgun, J. F. (1998, November). A comprehensive theory of family violence. Paper presented at the 28th Preconference Workshop on Theory Construction and Research Methodology, National Council on Family Relations , Milwaukee, WI.

Gilgun, J. F. ( 1999 a). CASPARS: New tools for assessing client risks and strengths.   Families in Society , 80 (5), 450–459.

Gilgun, J. F. (1999c, November). In their own words: Men talk about their violence . Paper presented at the 29th Preconference Workshop on Theory Construction and Research Methodology, National Council on Family Relations , Irvine, CA.

Gilgun, Jane F. ( 1999 d ). Methodological pluralism and qualitative family research. In Suzanne K. Steinmetz , Marvin B. Sussman , and Gary W. Peterson (Eds.), Handbook of Marriage and the Family (2nd ed.) (pp. 219–261). New York: Plenum.

Gilgun, J. F. (2000, June 25–28). A comprehensive theory of interpersonal violence . Paper presented at the Victimization of Children and Youth: An International Research Conference, Durham, NH .

Gilgun, J. F. ( 2002 a). Completing the circle: American Indian medicine wheels and the promotion of resilience in children and youth in care.   Journal of Human Behavior and the Social Environment , 6 (2), 65–84.

Gilgun, J. F. ( 2002 b). Social work and the assessment of the potential for violence. In T. N. Tiong & I. Dodds (Eds.), Social work around the world II (pp. 58–74). Berne, Switzerland: International Federation of Social Workers.

Gilgun, J. F. ( 2004 a). A strengths-based approach to child and family assessment. In D. R. Catheral (Ed.), Handbook of stress, trauma and the family (pp. 307–324). New York: Bruner-Routledge.

Gilgun, J. F. ( 2004 b). The 4-D: Strengths-based assessments for youth who’ve experienced adversities.   Journal of Human Behavior in the Social Environment , 10 (4), 51–73 .

Gilgun, J. F. ( 2005 a). Evidence-based practice, descriptive research, and the resilience-schema-gender-brain (RSGB) assessment.   British Journal of Social Work , 35 (6), 843–862.

Gilgun, J. F. ( 2005 b). “ Grab” and good science: Writing up the results of qualitative research.   Qualitative Health Research , 15 (2), 256–262.

Gilgun, J. F. ( 2005 c). Lighten up! The citation dilemma in qualitative research.   Qualitative Health Research , 15 (5), 721–725.

Gilgun, J. F. ( 2005 d). Qualitative research and family psychology.   Journal of Family Psychology , 19 (1), 40–50.

Gilgun, J. F. ( 2006 ). Children and adolescents with problematic sexual behaviors: Lessons from research on resilience. In R. Longo & D. Prescott (Eds.), Current perspectives on working with sexually aggressive youth and youth with sexual behavior problems (pp. 383–394). Holyoke, MA: Neari Press.

Gilgun, Jane F. (2007, November). The legacy of the Chicago School of Sociology for family theory-building, Pre-Conference Workshop on Theory Construction and Research Methodology, National Council on Family Relation, Pittsburgh, PA, November 7.

Gilgun, J. F. ( 2008 ). Lived experience, reflexivity, and research on perpetrators of interpersonal violence.   Qualitative Social Work , 7 (2), 181–197.

Gilgun, J. F. ( 2010 ). Reflections on 25 years of research on violence.   Reflections: Narratives of Professional Helping , 16 (4), 50–59.

Gilgun, J. F. ( 2012 a). Enduring themes in qualitative family research.   Journal of Family Theory and Review , 4 , 80–95.

Gilgun, J. F. (2012b). School shootings are not senseless and other essays on violence . Amazon. http://www.amazon.com/s/ref=nb_sb_noss?url=search-alias%3Ddigital-text&field-keywords=school+shootings+are+not+senseless . Retrieved 2 January 2014.

Gilgun, J. F. (2012c). The thin blue line of police brutality & other essays . Amazon. http://www.amazon.com/s/ref=nb_sb_noss?url=search-alias%3Ddigital-text&field-keywords=the+thin+blue+line+of+police+brutality&rh=n%3A133140011%2Ck%3Athe+thin+blue+line+of+police+brutality . Retrieved 2 January 2014.

Gilgun, J. F. (2013a). The logic of murderous rampages & other essays on violence and its prevention (2nd ed.). Amazon. http://www.amazon.com/Murderous-Rampages-Essays-Violence-Prevention-ebook/dp/B00AYPR18A/ref=sr_1_2?s=digital-text&ie=UTF8&qid=1388681278&sr=1-2&keywords=the+logic+of+murderous+rampages . Retrieved 2 January 2014.

Gilgun, J. F. ( 2013 b). Qualitative family research: Enduring themes and contemporary variations. In G. F. Peterson & K. Bush (Eds.), Handbook of marriage and the family (3rd ed., pp. 91–119). New York: Plenum.

Gilgun, J. F. , & Abrams, L. S. ( 2005 ). Gendered adaptations, resilience, and the perpetration of violence. In M. Ungar (Ed.), Handbook for working with children and Youth: Pathways to resilience across cultures and context (pp. 57–70). Toronto: University of Toronto Press.

Gilgun, J. F. , & Anderson, G. ( 2013 ). Mothers’ perspectives on signs of child sexual abuse in their families.   Families in Society , 94 (4), 259–267.

Gilgun, J. F. , Daly, K. , & Handel, G. (Eds.). ( 1992 ). Qualitative methods in family research . Newbury Park, CA: SAGE Publications.

Gilgun, J. F. , Keskinen, S. , Marti, D. J. , & Rice, K. ( 1999 ). Clinical applications of the CASPARS instruments: Boys who act out sexually.   Families in Society , 80 (6), 629–641.

Gilgun, J. F. , Klein, C. , & Pranis, K. ( 2000 ). The significance of resources in models of risk.   Journal of Interpersonal Violence , 14 , 627–646.

Gilgun, J. F. , & Sands, R. G. (Eds.). ( 2012 ). Special issue: The contributions of qualitative approaches to developmental intervention research.   Qualitative Social Work: Research and Practice , 11 (4), 80–95.

Gilgun, J. F. , & Sussman, M. B. (Eds.). ( 1996 ). The methods and methodologies of qualitative family research . New York: Haworth. Also published as a special issue of Marriage and Family Review , 41 (1–2).

Glaser, B. ( 1978 ). Theoretical sensitivity . Mill Valley, CA: Sociology Press.

Glaser, B. , & Strauss, A. ( 1967 ). The discovery of grounded theory . Chicago: Aldine.

Guba, E. G. , & Lincoln, Y. S. ( 2005 ). Paradigmatic controversies, contradictions, and emerging confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (3rd ed.). Thousand Oaks, CA: Sage.

Irvine, L. ( 2013 ). Animals as lifechangers and lifesavers: Pets in the redemptive narratives of homeless people.   Journal of Contemporary Ethnography , 42 (1), 3–30.

Lindesmith, A. ( 1947 ). Opiate addictions . Bloomington, IN: Principia.

McKinney, J. C. ( 1966 ). Constructive typology and social theory . New York: Appleton-Century-Crofts.

Presser, L. ( 2005 ). Negotiating power and narrative in research: Implications for feminist methodology.   Signs: Journal of Women in Culture and Society , 30 (4), 2067–2090.

Rober, P. ( 2011 ). The therapist’s experiencing in family therapy practice.   Journal of Family Therapy , 33 , 233–255.

Saldaña, J. ( 2003 ). Dramatizing data: A primer.   Qualitative Inquiry , 9 , 218–236.

Schatzman, L. ( 1991 ). Dimensional analysis: Notes on an alternative approach to the grounding of theory in qualitative research. In D. R. Maines (Ed.), Social organizations and social process: Essays in honor of Anselm Strauss (pp. 303–314). New York: Aldine de Gruyter.

Scott, J. A. ( 2003 ). Problematizing a researcher’s performance of “insider status:” An autoethnography of “designer disabled” identity.   Qualitative Inquiry , 19 , 101–115.

Sharma, A. , & Gilgun, J. F. ( 2008 ). What perpetrators say about child sexual abuse.   Indian Journal of Social Work , 69 (3), 321–338.

Small, A. W. ( 1916 ). Fifty years of sociology in the United States, 1865–1915.   American Journal of Sociology , 21 , 712–864.

Spermon, D.   Darlington, Y , & Gibney, P. ( 2013 ). Complex posttraumatic stress disorder: Voice of healing.   Qualitative Health Research , 24 (1), 43–53.

Velásquez, G. ( 2011 ). Inside the Church of Scientology: An ethnographic performance script.   Qualitative Inquiry , 17 , 824–836.

Weingarten, K. ( 2012 ). Sorrow: A therapist’s reflection on the inevitable and the unknowable.   Family Process , 51 (4), 440–455.

Winter, K. ( 2010 ). The perspectives of young children in care.   Child and Family Social Work , 15 , 186–195.

Young, P. V. (l928). The reorganization of Jewish family life in America.   Social Forces , 7 , 238–243.

Young, P. V. (l932). The Pilgrims of Russian Town . Chicago: University of Chicago Press.

• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons
• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

2.3: Propositions and Hypotheses

• Last updated
• Save as PDF
• Page ID 26213

• Anol Bhattacherjee
• University of South Florida via Global Text Project

Figure 2.2 shows how theoretical constructs such as intelligence, effort, academic achievement, and earning potential are related to each other in a nomological network. Each of these relationships is called a proposition. In seeking explanations to a given phenomenon or behavior, it is not adequate just to identify key concepts and constructs underlying the target phenomenon or behavior. We must also identify and state patterns of relationships between these constructs. Such patterns of relationships are called propositions. A proposition is a tentative and conjectural relationship between constructs that is stated in a declarative form. An example of a proposition is: “An increase in student intelligence causes an increase in their academic achievement.” This declarative statement does not have to be true, but must be empirically testable using data, so that we can judge whether it is true or false. Propositions are generally derived based on logic (deduction) or empirical observations (induction).

Because propositions are associations between abstract constructs, they cannot be tested directly. Instead, they are tested indirectly by examining the relationship between corresponding measures (variables) of those constructs. The empirical formulation of propositions, stated as relationships between variables, is called hypotheses (see Figure 2.1). Since IQ scores and grade point average are operational measures of intelligence and academic achievement respectively, the above proposition can be specified in form of the hypothesis: “An increase in students’ IQ score causes an increase in their grade point average.” Propositions are specified in the theoretical plane, while hypotheses are specified in the empirical plane. Hence, hypotheses are empirically testable using observed data, and may be rejected if not supported by empirical observations. Of course, the goal of hypothesis testing is to infer whether the corresponding proposition is valid.

Hypotheses can be strong or weak. “Students’ IQ scores are related to their academic achievement” is an example of a weak hypothesis, since it indicates neither the directionality of the hypothesis (i.e., whether the relationship is positive or negative), nor its causality (i.e., whether intelligence causes academic achievement or academic achievement causes intelligence). A stronger hypothesis is “students’ IQ scores are positively related to their academic achievement”, which indicates the directionality but not the causality. A still better hypothesis is “students’ IQ scores have positive effects on their academic achievement”, which specifies both the directionality and the causality (i.e., intelligence causes academic achievement, and not the reverse). The signs in Figure 2.2 indicate the directionality of the respective hypotheses.

Also note that scientific hypotheses should clearly specify independent and dependent variables. In the hypothesis, “students’ IQ scores have positive effects on their academic achievement,” it is clear that intelligence is the independent variable (the “cause”) and academic achievement is the dependent variable (the “effect”). Further, it is also clear that this hypothesis can be evaluated as either true (if higher intelligence leads to higher academic achievement) or false (if higher intelligence has no effect on or leads to lower academic achievement). Later on in this book, we will examine how to empirically test such cause-effect relationships. Statements such as “students are generally intelligent” or “all students can achieve academic success” are not scientific hypotheses because they do not specify independent and dependent variables, nor do they specify a directional relationship that can be evaluated as true or false.

Chapter 1. Introduction

“Science is in danger, and for that reason it is becoming dangerous” -Pierre Bourdieu, Science of Science and Reflexivity

Why an Open Access Textbook on Qualitative Research Methods?

I have been teaching qualitative research methods to both undergraduates and graduate students for many years.  Although there are some excellent textbooks out there, they are often costly, and none of them, to my mind, properly introduces qualitative research methods to the beginning student (whether undergraduate or graduate student).  In contrast, this open-access textbook is designed as a (free) true introduction to the subject, with helpful, practical pointers on how to conduct research and how to access more advanced instruction.  

Textbooks are typically arranged in one of two ways: (1) by technique (each chapter covers one method used in qualitative research); or (2) by process (chapters advance from research design through publication).  But both of these approaches are necessary for the beginner student.  This textbook will have sections dedicated to the process as well as the techniques of qualitative research.  This is a true “comprehensive” book for the beginning student.  In addition to covering techniques of data collection and data analysis, it provides a road map of how to get started and how to keep going and where to go for advanced instruction.  It covers aspects of research design and research communication as well as methods employed.  Along the way, it includes examples from many different disciplines in the social sciences.

The primary goal has been to create a useful, accessible, engaging textbook for use across many disciplines.  And, let’s face it.  Textbooks can be boring.  I hope readers find this to be a little different.  I have tried to write in a practical and forthright manner, with many lively examples and references to good and intellectually creative qualitative research.  Woven throughout the text are short textual asides (in colored textboxes) by professional (academic) qualitative researchers in various disciplines.  These short accounts by practitioners should help inspire students.  So, let’s begin!

What is Research?

When we use the word research , what exactly do we mean by that?  This is one of those words that everyone thinks they understand, but it is worth beginning this textbook with a short explanation.  We use the term to refer to “empirical research,” which is actually a historically specific approach to understanding the world around us.  Think about how you know things about the world. [1] You might know your mother loves you because she’s told you she does.  Or because that is what “mothers” do by tradition.  Or you might know because you’ve looked for evidence that she does, like taking care of you when you are sick or reading to you in bed or working two jobs so you can have the things you need to do OK in life.  Maybe it seems churlish to look for evidence; you just take it “on faith” that you are loved.

Only one of the above comes close to what we mean by research.  Empirical research is research (investigation) based on evidence.  Conclusions can then be drawn from observable data.  This observable data can also be “tested” or checked.  If the data cannot be tested, that is a good indication that we are not doing research.  Note that we can never “prove” conclusively, through observable data, that our mothers love us.  We might have some “disconfirming evidence” (that time she didn’t show up to your graduation, for example) that could push you to question an original hypothesis , but no amount of “confirming evidence” will ever allow us to say with 100% certainty, “my mother loves me.”  Faith and tradition and authority work differently.  Our knowledge can be 100% certain using each of those alternative methods of knowledge, but our certainty in those cases will not be based on facts or evidence.

For many periods of history, those in power have been nervous about “science” because it uses evidence and facts as the primary source of understanding the world, and facts can be at odds with what power or authority or tradition want you to believe.  That is why I say that scientific empirical research is a historically specific approach to understand the world.  You are in college or university now partly to learn how to engage in this historically specific approach.

In the sixteenth and seventeenth centuries in Europe, there was a newfound respect for empirical research, some of which was seriously challenging to the established church.  Using observations and testing them, scientists found that the earth was not at the center of the universe, for example, but rather that it was but one planet of many which circled the sun. [2]   For the next two centuries, the science of astronomy, physics, biology, and chemistry emerged and became disciplines taught in universities.  All used the scientific method of observation and testing to advance knowledge.  Knowledge about people , however, and social institutions, however, was still left to faith, tradition, and authority.  Historians and philosophers and poets wrote about the human condition, but none of them used research to do so. [3]

It was not until the nineteenth century that “social science” really emerged, using the scientific method (empirical observation) to understand people and social institutions.  New fields of sociology, economics, political science, and anthropology emerged.  The first sociologists, people like Auguste Comte and Karl Marx, sought specifically to apply the scientific method of research to understand society, Engels famously claiming that Marx had done for the social world what Darwin did for the natural world, tracings its laws of development.  Today we tend to take for granted the naturalness of science here, but it is actually a pretty recent and radical development.

To return to the question, “does your mother love you?”  Well, this is actually not really how a researcher would frame the question, as it is too specific to your case.  It doesn’t tell us much about the world at large, even if it does tell us something about you and your relationship with your mother.  A social science researcher might ask, “do mothers love their children?”  Or maybe they would be more interested in how this loving relationship might change over time (e.g., “do mothers love their children more now than they did in the 18th century when so many children died before reaching adulthood?”) or perhaps they might be interested in measuring quality of love across cultures or time periods, or even establishing “what love looks like” using the mother/child relationship as a site of exploration.  All of these make good research questions because we can use observable data to answer them.

What is Qualitative Research?

“All we know is how to learn. How to study, how to listen, how to talk, how to tell.  If we don’t tell the world, we don’t know the world.  We’re lost in it, we die.” -Ursula LeGuin, The Telling

At its simplest, qualitative research is research about the social world that does not use numbers in its analyses.  All those who fear statistics can breathe a sigh of relief – there are no mathematical formulae or regression models in this book! But this definition is less about what qualitative research can be and more about what it is not.  To be honest, any simple statement will fail to capture the power and depth of qualitative research.  One way of contrasting qualitative research to quantitative research is to note that the focus of qualitative research is less about explaining and predicting relationships between variables and more about understanding the social world.  To use our mother love example, the question about “what love looks like” is a good question for the qualitative researcher while all questions measuring love or comparing incidences of love (both of which require measurement) are good questions for quantitative researchers. Patton writes,

Qualitative data describe.  They take us, as readers, into the time and place of the observation so that we know what it was like to have been there.  They capture and communicate someone else’s experience of the world in his or her own words.  Qualitative data tell a story. ( Patton 2002:47 )

Qualitative researchers are asking different questions about the world than their quantitative colleagues.  Even when researchers are employed in “mixed methods” research ( both quantitative and qualitative), they are using different methods to address different questions of the study.  I do a lot of research about first-generation and working-college college students.  Where a quantitative researcher might ask, how many first-generation college students graduate from college within four years? Or does first-generation college status predict high student debt loads?  A qualitative researcher might ask, how does the college experience differ for first-generation college students?  What is it like to carry a lot of debt, and how does this impact the ability to complete college on time?  Both sets of questions are important, but they can only be answered using specific tools tailored to those questions.  For the former, you need large numbers to make adequate comparisons.  For the latter, you need to talk to people, find out what they are thinking and feeling, and try to inhabit their shoes for a little while so you can make sense of their experiences and beliefs.

Examples of Qualitative Research

You have probably seen examples of qualitative research before, but you might not have paid particular attention to how they were produced or realized that the accounts you were reading were the result of hours, months, even years of research “in the field.”  A good qualitative researcher will present the product of their hours of work in such a way that it seems natural, even obvious, to the reader.  Because we are trying to convey what it is like answers, qualitative research is often presented as stories – stories about how people live their lives, go to work, raise their children, interact with one another.  In some ways, this can seem like reading particularly insightful novels.  But, unlike novels, there are very specific rules and guidelines that qualitative researchers follow to ensure that the “story” they are telling is accurate , a truthful rendition of what life is like for the people being studied.  Most of this textbook will be spent conveying those rules and guidelines.  Let’s take a look, first, however, at three examples of what the end product looks like.  I have chosen these three examples to showcase very different approaches to qualitative research, and I will return to these five examples throughout the book.  They were all published as whole books (not chapters or articles), and they are worth the long read, if you have the time.  I will also provide some information on how these books came to be and the length of time it takes to get them into book version.  It is important you know about this process, and the rest of this textbook will help explain why it takes so long to conduct good qualitative research!

Example 1 : The End Game (ethnography + interviews)

Corey Abramson is a sociologist who teaches at the University of Arizona.   In 2015 he published The End Game: How Inequality Shapes our Final Years ( 2015 ). This book was based on the research he did for his dissertation at the University of California-Berkeley in 2012.  Actually, the dissertation was completed in 2012 but the work that was produced that took several years.  The dissertation was entitled, “This is How We Live, This is How We Die: Social Stratification, Aging, and Health in Urban America” ( 2012 ).  You can see how the book version, which was written for a more general audience, has a more engaging sound to it, but that the dissertation version, which is what academic faculty read and evaluate, has a more descriptive title.  You can read the title and know that this is a study about aging and health and that the focus is going to be inequality and that the context (place) is going to be “urban America.”  It’s a study about “how” people do something – in this case, how they deal with aging and death.  This is the very first sentence of the dissertation, “From our first breath in the hospital to the day we die, we live in a society characterized by unequal opportunities for maintaining health and taking care of ourselves when ill.  These disparities reflect persistent racial, socio-economic, and gender-based inequalities and contribute to their persistence over time” ( 1 ).  What follows is a truthful account of how that is so.

Cory Abramson spent three years conducting his research in four different urban neighborhoods.  We call the type of research he conducted “comparative ethnographic” because he designed his study to compare groups of seniors as they went about their everyday business.  It’s comparative because he is comparing different groups (based on race, class, gender) and ethnographic because he is studying the culture/way of life of a group. [4]   He had an educated guess, rooted in what previous research had shown and what social theory would suggest, that people’s experiences of aging differ by race, class, and gender.  So, he set up a research design that would allow him to observe differences.  He chose two primarily middle-class (one was racially diverse and the other was predominantly White) and two primarily poor neighborhoods (one was racially diverse and the other was predominantly African American).  He hung out in senior centers and other places seniors congregated, watched them as they took the bus to get prescriptions filled, sat in doctor’s offices with them, and listened to their conversations with each other.  He also conducted more formal conversations, what we call in-depth interviews, with sixty seniors from each of the four neighborhoods.  As with a lot of fieldwork , as he got closer to the people involved, he both expanded and deepened his reach –

By the end of the project, I expanded my pool of general observations to include various settings frequented by seniors: apartment building common rooms, doctors’ offices, emergency rooms, pharmacies, senior centers, bars, parks, corner stores, shopping centers, pool halls, hair salons, coffee shops, and discount stores. Over the course of the three years of fieldwork, I observed hundreds of elders, and developed close relationships with a number of them. ( 2012:10 )

When Abramson rewrote the dissertation for a general audience and published his book in 2015, it got a lot of attention.  It is a beautifully written book and it provided insight into a common human experience that we surprisingly know very little about.  It won the Outstanding Publication Award by the American Sociological Association Section on Aging and the Life Course and was featured in the New York Times .  The book was about aging, and specifically how inequality shapes the aging process, but it was also about much more than that.  It helped show how inequality affects people’s everyday lives.  For example, by observing the difficulties the poor had in setting up appointments and getting to them using public transportation and then being made to wait to see a doctor, sometimes in standing-room-only situations, when they are unwell, and then being treated dismissively by hospital staff, Abramson allowed readers to feel the material reality of being poor in the US.  Comparing these examples with seniors with adequate supplemental insurance who have the resources to hire car services or have others assist them in arranging care when they need it, jolts the reader to understand and appreciate the difference money makes in the lives and circumstances of us all, and in a way that is different than simply reading a statistic (“80% of the poor do not keep regular doctor’s appointments”) does.  Qualitative research can reach into spaces and places that often go unexamined and then reports back to the rest of us what it is like in those spaces and places.

Example 2: Racing for Innocence (Interviews + Content Analysis + Fictional Stories)

Jennifer Pierce is a Professor of American Studies at the University of Minnesota.  Trained as a sociologist, she has written a number of books about gender, race, and power.  Her very first book, Gender Trials: Emotional Lives in Contemporary Law Firms, published in 1995, is a brilliant look at gender dynamics within two law firms.  Pierce was a participant observer, working as a paralegal, and she observed how female lawyers and female paralegals struggled to obtain parity with their male colleagues.

Fifteen years later, she reexamined the context of the law firm to include an examination of racial dynamics, particularly how elite white men working in these spaces created and maintained a culture that made it difficult for both female attorneys and attorneys of color to thrive. Her book, Racing for Innocence: Whiteness, Gender, and the Backlash Against Affirmative Action , published in 2012, is an interesting and creative blending of interviews with attorneys, content analyses of popular films during this period, and fictional accounts of racial discrimination and sexual harassment.  The law firm she chose to study had come under an affirmative action order and was in the process of implementing equitable policies and programs.  She wanted to understand how recipients of white privilege (the elite white male attorneys) come to deny the role they play in reproducing inequality.  Through interviews with attorneys who were present both before and during the affirmative action order, she creates a historical record of the “bad behavior” that necessitated new policies and procedures, but also, and more importantly , probed the participants ’ understanding of this behavior.  It should come as no surprise that most (but not all) of the white male attorneys saw little need for change, and that almost everyone else had accounts that were different if not sometimes downright harrowing.

I’ve used Pierce’s book in my qualitative research methods courses as an example of an interesting blend of techniques and presentation styles.  My students often have a very difficult time with the fictional accounts she includes.  But they serve an important communicative purpose here.  They are her attempts at presenting “both sides” to an objective reality – something happens (Pierce writes this something so it is very clear what it is), and the two participants to the thing that happened have very different understandings of what this means.  By including these stories, Pierce presents one of her key findings – people remember things differently and these different memories tend to support their own ideological positions.  I wonder what Pierce would have written had she studied the murder of George Floyd or the storming of the US Capitol on January 6 or any number of other historic events whose observers and participants record very different happenings.

This is not to say that qualitative researchers write fictional accounts.  In fact, the use of fiction in our work remains controversial.  When used, it must be clearly identified as a presentation device, as Pierce did.  I include Racing for Innocence here as an example of the multiple uses of methods and techniques and the way that these work together to produce better understandings by us, the readers, of what Pierce studied.  We readers come away with a better grasp of how and why advantaged people understate their own involvement in situations and structures that advantage them.  This is normal human behavior , in other words.  This case may have been about elite white men in law firms, but the general insights here can be transposed to other settings.  Indeed, Pierce argues that more research needs to be done about the role elites play in the reproduction of inequality in the workplace in general.

Example 3: Amplified Advantage (Mixed Methods: Survey Interviews + Focus Groups + Archives)

The final example comes from my own work with college students, particularly the ways in which class background affects the experience of college and outcomes for graduates.  I include it here as an example of mixed methods, and for the use of supplementary archival research.  I’ve done a lot of research over the years on first-generation, low-income, and working-class college students.  I am curious (and skeptical) about the possibility of social mobility today, particularly with the rising cost of college and growing inequality in general.  As one of the few people in my family to go to college, I didn’t grow up with a lot of examples of what college was like or how to make the most of it.  And when I entered graduate school, I realized with dismay that there were very few people like me there.  I worried about becoming too different from my family and friends back home.  And I wasn’t at all sure that I would ever be able to pay back the huge load of debt I was taking on.  And so I wrote my dissertation and first two books about working-class college students.  These books focused on experiences in college and the difficulties of navigating between family and school ( Hurst 2010a, 2012 ).  But even after all that research, I kept coming back to wondering if working-class students who made it through college had an equal chance at finding good jobs and happy lives,

What happens to students after college?  Do working-class students fare as well as their peers?  I knew from my own experience that barriers continued through graduate school and beyond, and that my debtload was higher than that of my peers, constraining some of the choices I made when I graduated.  To answer these questions, I designed a study of students attending small liberal arts colleges, the type of college that tried to equalize the experience of students by requiring all students to live on campus and offering small classes with lots of interaction with faculty.  These private colleges tend to have more money and resources so they can provide financial aid to low-income students.  They also attract some very wealthy students.  Because they enroll students across the class spectrum, I would be able to draw comparisons.  I ended up spending about four years collecting data, both a survey of more than 2000 students (which formed the basis for quantitative analyses) and qualitative data collection (interviews, focus groups, archival research, and participant observation).  This is what we call a “mixed methods” approach because we use both quantitative and qualitative data.  The survey gave me a large enough number of students that I could make comparisons of the how many kind, and to be able to say with some authority that there were in fact significant differences in experience and outcome by class (e.g., wealthier students earned more money and had little debt; working-class students often found jobs that were not in their chosen careers and were very affected by debt, upper-middle-class students were more likely to go to graduate school).  But the survey analyses could not explain why these differences existed.  For that, I needed to talk to people and ask them about their motivations and aspirations.  I needed to understand their perceptions of the world, and it is very hard to do this through a survey.

By interviewing students and recent graduates, I was able to discern particular patterns and pathways through college and beyond.  Specifically, I identified three versions of gameplay.  Upper-middle-class students, whose parents were themselves professionals (academics, lawyers, managers of non-profits), saw college as the first stage of their education and took classes and declared majors that would prepare them for graduate school.  They also spent a lot of time building their resumes, taking advantage of opportunities to help professors with their research, or study abroad.  This helped them gain admission to highly-ranked graduate schools and interesting jobs in the public sector.  In contrast, upper-class students, whose parents were wealthy and more likely to be engaged in business (as CEOs or other high-level directors), prioritized building social capital.  They did this by joining fraternities and sororities and playing club sports.  This helped them when they graduated as they called on friends and parents of friends to find them well-paying jobs.  Finally, low-income, first-generation, and working-class students were often adrift.  They took the classes that were recommended to them but without the knowledge of how to connect them to life beyond college.  They spent time working and studying rather than partying or building their resumes.  All three sets of students thought they were “doing college” the right way, the way that one was supposed to do college.   But these three versions of gameplay led to distinct outcomes that advantaged some students over others.  I titled my work “Amplified Advantage” to highlight this process.

These three examples, Cory Abramson’s The End Game , Jennifer Peirce’s Racing for Innocence, and my own Amplified Advantage, demonstrate the range of approaches and tools available to the qualitative researcher.  They also help explain why qualitative research is so important.  Numbers can tell us some things about the world, but they cannot get at the hearts and minds, motivations and beliefs of the people who make up the social worlds we inhabit.  For that, we need tools that allow us to listen and make sense of what people tell us and show us.  That is what good qualitative research offers us.

How Is This Book Organized?

This textbook is organized as a comprehensive introduction to the use of qualitative research methods.  The first half covers general topics (e.g., approaches to qualitative research, ethics) and research design (necessary steps for building a successful qualitative research study).  The second half reviews various data collection and data analysis techniques.  Of course, building a successful qualitative research study requires some knowledge of data collection and data analysis so the chapters in the first half and the chapters in the second half should be read in conversation with each other.  That said, each chapter can be read on its own for assistance with a particular narrow topic.  In addition to the chapters, a helpful glossary can be found in the back of the book.  Rummage around in the text as needed.

Chapter Descriptions

Chapter 2 provides an overview of the Research Design Process.  How does one begin a study? What is an appropriate research question?  How is the study to be done – with what methods ?  Involving what people and sites?  Although qualitative research studies can and often do change and develop over the course of data collection, it is important to have a good idea of what the aims and goals of your study are at the outset and a good plan of how to achieve those aims and goals.  Chapter 2 provides a road map of the process.

Chapter 3 describes and explains various ways of knowing the (social) world.  What is it possible for us to know about how other people think or why they behave the way they do?  What does it mean to say something is a “fact” or that it is “well-known” and understood?  Qualitative researchers are particularly interested in these questions because of the types of research questions we are interested in answering (the how questions rather than the how many questions of quantitative research).  Qualitative researchers have adopted various epistemological approaches.  Chapter 3 will explore these approaches, highlighting interpretivist approaches that acknowledge the subjective aspect of reality – in other words, reality and knowledge are not objective but rather influenced by (interpreted through) people.

Chapter 4 focuses on the practical matter of developing a research question and finding the right approach to data collection.  In any given study (think of Cory Abramson’s study of aging, for example), there may be years of collected data, thousands of observations , hundreds of pages of notes to read and review and make sense of.  If all you had was a general interest area (“aging”), it would be very difficult, nearly impossible, to make sense of all of that data.  The research question provides a helpful lens to refine and clarify (and simplify) everything you find and collect.  For that reason, it is important to pull out that lens (articulate the research question) before you get started.  In the case of the aging study, Cory Abramson was interested in how inequalities affected understandings and responses to aging.  It is for this reason he designed a study that would allow him to compare different groups of seniors (some middle-class, some poor).  Inevitably, he saw much more in the three years in the field than what made it into his book (or dissertation), but he was able to narrow down the complexity of the social world to provide us with this rich account linked to the original research question.  Developing a good research question is thus crucial to effective design and a successful outcome.  Chapter 4 will provide pointers on how to do this.  Chapter 4 also provides an overview of general approaches taken to doing qualitative research and various “traditions of inquiry.”

Chapter 5 explores sampling .  After you have developed a research question and have a general idea of how you will collect data (Observations?  Interviews?), how do you go about actually finding people and sites to study?  Although there is no “correct number” of people to interview , the sample should follow the research question and research design.  Unlike quantitative research, qualitative research involves nonprobability sampling.  Chapter 5 explains why this is so and what qualities instead make a good sample for qualitative research.

Chapter 6 addresses the importance of reflexivity in qualitative research.  Related to epistemological issues of how we know anything about the social world, qualitative researchers understand that we the researchers can never be truly neutral or outside the study we are conducting.  As observers, we see things that make sense to us and may entirely miss what is either too obvious to note or too different to comprehend.  As interviewers, as much as we would like to ask questions neutrally and remain in the background, interviews are a form of conversation, and the persons we interview are responding to us .  Therefore, it is important to reflect upon our social positions and the knowledges and expectations we bring to our work and to work through any blind spots that we may have.  Chapter 6 provides some examples of reflexivity in practice and exercises for thinking through one’s own biases.

Chapter 7 is a very important chapter and should not be overlooked.  As a practical matter, it should also be read closely with chapters 6 and 8.  Because qualitative researchers deal with people and the social world, it is imperative they develop and adhere to a strong ethical code for conducting research in a way that does not harm.  There are legal requirements and guidelines for doing so (see chapter 8), but these requirements should not be considered synonymous with the ethical code required of us.   Each researcher must constantly interrogate every aspect of their research, from research question to design to sample through analysis and presentation, to ensure that a minimum of harm (ideally, zero harm) is caused.  Because each research project is unique, the standards of care for each study are unique.  Part of being a professional researcher is carrying this code in one’s heart, being constantly attentive to what is required under particular circumstances.  Chapter 7 provides various research scenarios and asks readers to weigh in on the suitability and appropriateness of the research.  If done in a class setting, it will become obvious fairly quickly that there are often no absolutely correct answers, as different people find different aspects of the scenarios of greatest importance.  Minimizing the harm in one area may require possible harm in another.  Being attentive to all the ethical aspects of one’s research and making the best judgments one can, clearly and consciously, is an integral part of being a good researcher.

Chapter 8 , best to be read in conjunction with chapter 7, explains the role and importance of Institutional Review Boards (IRBs) .  Under federal guidelines, an IRB is an appropriately constituted group that has been formally designated to review and monitor research involving human subjects .  Every institution that receives funding from the federal government has an IRB.  IRBs have the authority to approve, require modifications to (to secure approval), or disapprove research.  This group review serves an important role in the protection of the rights and welfare of human research subjects.  Chapter 8 reviews the history of IRBs and the work they do but also argues that IRBs’ review of qualitative research is often both over-inclusive and under-inclusive.  Some aspects of qualitative research are not well understood by IRBs, given that they were developed to prevent abuses in biomedical research.  Thus, it is important not to rely on IRBs to identify all the potential ethical issues that emerge in our research (see chapter 7).

Chapter 9 provides help for getting started on formulating a research question based on gaps in the pre-existing literature.  Research is conducted as part of a community, even if particular studies are done by single individuals (or small teams).  What any of us finds and reports back becomes part of a much larger body of knowledge.  Thus, it is important that we look at the larger body of knowledge before we actually start our bit to see how we can best contribute.  When I first began interviewing working-class college students, there was only one other similar study I could find, and it hadn’t been published (it was a dissertation of students from poor backgrounds).  But there had been a lot published by professors who had grown up working class and made it through college despite the odds.  These accounts by “working-class academics” became an important inspiration for my study and helped me frame the questions I asked the students I interviewed.  Chapter 9 will provide some pointers on how to search for relevant literature and how to use this to refine your research question.

Chapter 10 serves as a bridge between the two parts of the textbook, by introducing techniques of data collection.  Qualitative research is often characterized by the form of data collection – for example, an ethnographic study is one that employs primarily observational data collection for the purpose of documenting and presenting a particular culture or ethnos.  Techniques can be effectively combined, depending on the research question and the aims and goals of the study.   Chapter 10 provides a general overview of all the various techniques and how they can be combined.

The second part of the textbook moves into the doing part of qualitative research once the research question has been articulated and the study designed.  Chapters 11 through 17 cover various data collection techniques and approaches.  Chapters 18 and 19 provide a very simple overview of basic data analysis.  Chapter 20 covers communication of the data to various audiences, and in various formats.

Chapter 11 begins our overview of data collection techniques with a focus on interviewing , the true heart of qualitative research.  This technique can serve as the primary and exclusive form of data collection, or it can be used to supplement other forms (observation, archival).  An interview is distinct from a survey, where questions are asked in a specific order and often with a range of predetermined responses available.  Interviews can be conversational and unstructured or, more conventionally, semistructured , where a general set of interview questions “guides” the conversation.  Chapter 11 covers the basics of interviews: how to create interview guides, how many people to interview, where to conduct the interview, what to watch out for (how to prepare against things going wrong), and how to get the most out of your interviews.

Chapter 12 covers an important variant of interviewing, the focus group.  Focus groups are semistructured interviews with a group of people moderated by a facilitator (the researcher or researcher’s assistant).  Focus groups explicitly use group interaction to assist in the data collection.  They are best used to collect data on a specific topic that is non-personal and shared among the group.  For example, asking a group of college students about a common experience such as taking classes by remote delivery during the pandemic year of 2020.  Chapter 12 covers the basics of focus groups: when to use them, how to create interview guides for them, and how to run them effectively.

Chapter 13 moves away from interviewing to the second major form of data collection unique to qualitative researchers – observation .  Qualitative research that employs observation can best be understood as falling on a continuum of “fly on the wall” observation (e.g., observing how strangers interact in a doctor’s waiting room) to “participant” observation, where the researcher is also an active participant of the activity being observed.  For example, an activist in the Black Lives Matter movement might want to study the movement, using her inside position to gain access to observe key meetings and interactions.  Chapter  13 covers the basics of participant observation studies: advantages and disadvantages, gaining access, ethical concerns related to insider/outsider status and entanglement, and recording techniques.

Chapter 14 takes a closer look at “deep ethnography” – immersion in the field of a particularly long duration for the purpose of gaining a deeper understanding and appreciation of a particular culture or social world.  Clifford Geertz called this “deep hanging out.”  Whereas participant observation is often combined with semistructured interview techniques, deep ethnography’s commitment to “living the life” or experiencing the situation as it really is demands more conversational and natural interactions with people.  These interactions and conversations may take place over months or even years.  As can be expected, there are some costs to this technique, as well as some very large rewards when done competently.  Chapter 14 provides some examples of deep ethnographies that will inspire some beginning researchers and intimidate others.

Chapter 15 moves in the opposite direction of deep ethnography, a technique that is the least positivist of all those discussed here, to mixed methods , a set of techniques that is arguably the most positivist .  A mixed methods approach combines both qualitative data collection and quantitative data collection, commonly by combining a survey that is analyzed statistically (e.g., cross-tabs or regression analyses of large number probability samples) with semi-structured interviews.  Although it is somewhat unconventional to discuss mixed methods in textbooks on qualitative research, I think it is important to recognize this often-employed approach here.  There are several advantages and some disadvantages to taking this route.  Chapter 16 will describe those advantages and disadvantages and provide some particular guidance on how to design a mixed methods study for maximum effectiveness.

Chapter 16 covers data collection that does not involve live human subjects at all – archival and historical research (chapter 17 will also cover data that does not involve interacting with human subjects).  Sometimes people are unavailable to us, either because they do not wish to be interviewed or observed (as is the case with many “elites”) or because they are too far away, in both place and time.  Fortunately, humans leave many traces and we can often answer questions we have by examining those traces.  Special collections and archives can be goldmines for social science research.  This chapter will explain how to access these places, for what purposes, and how to begin to make sense of what you find.

Chapter 17 covers another data collection area that does not involve face-to-face interaction with humans: content analysis .  Although content analysis may be understood more properly as a data analysis technique, the term is often used for the entire approach, which will be the case here.  Content analysis involves interpreting meaning from a body of text.  This body of text might be something found in historical records (see chapter 16) or something collected by the researcher, as in the case of comment posts on a popular blog post.  I once used the stories told by student loan debtors on the website studentloanjustice.org as the content I analyzed.  Content analysis is particularly useful when attempting to define and understand prevalent stories or communication about a topic of interest.  In other words, when we are less interested in what particular people (our defined sample) are doing or believing and more interested in what general narratives exist about a particular topic or issue.  This chapter will explore different approaches to content analysis and provide helpful tips on how to collect data, how to turn that data into codes for analysis, and how to go about presenting what is found through analysis.

Where chapter 17 has pushed us towards data analysis, chapters 18 and 19 are all about what to do with the data collected, whether that data be in the form of interview transcripts or fieldnotes from observations.  Chapter 18 introduces the basics of coding , the iterative process of assigning meaning to the data in order to both simplify and identify patterns.  What is a code and how does it work?  What are the different ways of coding data, and when should you use them?  What is a codebook, and why do you need one?  What does the process of data analysis look like?

Chapter 19 goes further into detail on codes and how to use them, particularly the later stages of coding in which our codes are refined, simplified, combined, and organized.  These later rounds of coding are essential to getting the most out of the data we’ve collected.  As students are often overwhelmed with the amount of data (a corpus of interview transcripts typically runs into the hundreds of pages; fieldnotes can easily top that), this chapter will also address time management and provide suggestions for dealing with chaos and reminders that feeling overwhelmed at the analysis stage is part of the process.  By the end of the chapter, you should understand how “findings” are actually found.

The book concludes with a chapter dedicated to the effective presentation of data results.  Chapter 20 covers the many ways that researchers communicate their studies to various audiences (academic, personal, political), what elements must be included in these various publications, and the hallmarks of excellent qualitative research that various audiences will be expecting.  Because qualitative researchers are motivated by understanding and conveying meaning , effective communication is not only an essential skill but a fundamental facet of the entire research project.  Ethnographers must be able to convey a certain sense of verisimilitude , the appearance of true reality.  Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them.  And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important.

The book concludes with a short chapter ( chapter 21 ) discussing the value of qualitative research. At the very end of this book, you will find a glossary of terms. I recommend you make frequent use of the glossary and add to each entry as you find examples. Although the entries are meant to be simple and clear, you may also want to paraphrase the definition—make it “make sense” to you, in other words. In addition to the standard reference list (all works cited here), you will find various recommendations for further reading at the end of many chapters. Some of these recommendations will be examples of excellent qualitative research, indicated with an asterisk (*) at the end of the entry. As they say, a picture is worth a thousand words. A good example of qualitative research can teach you more about conducting research than any textbook can (this one included). I highly recommend you select one to three examples from these lists and read them along with the textbook.

A final note on the choice of examples – you will note that many of the examples used in the text come from research on college students.  This is for two reasons.  First, as most of my research falls in this area, I am most familiar with this literature and have contacts with those who do research here and can call upon them to share their stories with you.  Second, and more importantly, my hope is that this textbook reaches a wide audience of beginning researchers who study widely and deeply across the range of what can be known about the social world (from marine resources management to public policy to nursing to political science to sexuality studies and beyond).  It is sometimes difficult to find examples that speak to all those research interests, however. A focus on college students is something that all readers can understand and, hopefully, appreciate, as we are all now or have been at some point a college student.

Recommended Reading: Other Qualitative Research Textbooks

I’ve included a brief list of some of my favorite qualitative research textbooks and guidebooks if you need more than what you will find in this introductory text.  For each, I’ve also indicated if these are for “beginning” or “advanced” (graduate-level) readers.  Many of these books have several editions that do not significantly vary; the edition recommended is merely the edition I have used in teaching and to whose page numbers any specific references made in the text agree.

Barbour, Rosaline. 2014. Introducing Qualitative Research: A Student’s Guide. Thousand Oaks, CA: SAGE.  A good introduction to qualitative research, with abundant examples (often from the discipline of health care) and clear definitions.  Includes quick summaries at the ends of each chapter.  However, some US students might find the British context distracting and can be a bit advanced in some places.  Beginning .

Bloomberg, Linda Dale, and Marie F. Volpe. 2012. Completing Your Qualitative Dissertation . 2nd ed. Thousand Oaks, CA: SAGE.  Specifically designed to guide graduate students through the research process. Advanced .

Creswell, John W., and Cheryl Poth. 2018 Qualitative Inquiry and Research Design: Choosing among Five Traditions .  4th ed. Thousand Oaks, CA: SAGE.  This is a classic and one of the go-to books I used myself as a graduate student.  One of the best things about this text is its clear presentation of five distinct traditions in qualitative research.  Despite the title, this reasonably sized book is about more than research design, including both data analysis and how to write about qualitative research.  Advanced .

Lareau, Annette. 2021. Listening to People: A Practical Guide to Interviewing, Participant Observation, Data Analysis, and Writing It All Up .  Chicago: University of Chicago Press. A readable and personal account of conducting qualitative research by an eminent sociologist, with a heavy emphasis on the kinds of participant-observation research conducted by the author.  Despite its reader-friendliness, this is really a book targeted to graduate students learning the craft.  Advanced .

Lune, Howard, and Bruce L. Berg. 2018. 9th edition.  Qualitative Research Methods for the Social Sciences.  Pearson . Although a good introduction to qualitative methods, the authors favor symbolic interactionist and dramaturgical approaches, which limits the appeal primarily to sociologists.  Beginning .

Marshall, Catherine, and Gretchen B. Rossman. 2016. 6th edition. Designing Qualitative Research. Thousand Oaks, CA: SAGE.  Very readable and accessible guide to research design by two educational scholars.  Although the presentation is sometimes fairly dry, personal vignettes and illustrations enliven the text.  Beginning .

Maxwell, Joseph A. 2013. Qualitative Research Design: An Interactive Approach .  3rd ed. Thousand Oaks, CA: SAGE. A short and accessible introduction to qualitative research design, particularly helpful for graduate students contemplating theses and dissertations. This has been a standard textbook in my graduate-level courses for years.  Advanced .

Patton, Michael Quinn. 2002. Qualitative Research and Evaluation Methods . Thousand Oaks, CA: SAGE.  This is a comprehensive text that served as my “go-to” reference when I was a graduate student.  It is particularly helpful for those involved in program evaluation and other forms of evaluation studies and uses examples from a wide range of disciplines.  Advanced .

Rubin, Ashley T. 2021. Rocking Qualitative Social Science: An Irreverent Guide to Rigorous Research. Stanford : Stanford University Press.  A delightful and personal read.  Rubin uses rock climbing as an extended metaphor for learning how to conduct qualitative research.  A bit slanted toward ethnographic and archival methods of data collection, with frequent examples from her own studies in criminology. Beginning .

Weis, Lois, and Michelle Fine. 2000. Speed Bumps: A Student-Friendly Guide to Qualitative Research . New York: Teachers College Press.  Readable and accessibly written in a quasi-conversational style.  Particularly strong in its discussion of ethical issues throughout the qualitative research process.  Not comprehensive, however, and very much tied to ethnographic research.  Although designed for graduate students, this is a recommended read for students of all levels.  Beginning .

Patton’s Ten Suggestions for Doing Qualitative Research

The following ten suggestions were made by Michael Quinn Patton in his massive textbooks Qualitative Research and Evaluations Methods . This book is highly recommended for those of you who want more than an introduction to qualitative methods. It is the book I relied on heavily when I was a graduate student, although it is much easier to “dip into” when necessary than to read through as a whole. Patton is asked for “just one bit of advice” for a graduate student considering using qualitative research methods for their dissertation.  Here are his top ten responses, in short form, heavily paraphrased, and with additional comments and emphases from me:

• Make sure that a qualitative approach fits the research question. The following are the kinds of questions that call out for qualitative methods or where qualitative methods are particularly appropriate: questions about people’s experiences or how they make sense of those experiences; studying a person in their natural environment; researching a phenomenon so unknown that it would be impossible to study it with standardized instruments or other forms of quantitative data collection.
• Study qualitative research by going to the original sources for the design and analysis appropriate to the particular approach you want to take (e.g., read Glaser and Straus if you are using grounded theory )
• Find a dissertation adviser who understands or at least who will support your use of qualitative research methods. You are asking for trouble if your entire committee is populated by quantitative researchers, even if they are all very knowledgeable about the subject or focus of your study (maybe even more so if they are!)
• Really work on design. Doing qualitative research effectively takes a lot of planning.  Even if things are more flexible than in quantitative research, a good design is absolutely essential when starting out.
• Practice data collection techniques, particularly interviewing and observing. There is definitely a set of learned skills here!  Do not expect your first interview to be perfect.  You will continue to grow as a researcher the more interviews you conduct, and you will probably come to understand yourself a bit more in the process, too.  This is not easy, despite what others who don’t work with qualitative methods may assume (and tell you!)
• Have a plan for analysis before you begin data collection. This is often a requirement in IRB protocols , although you can get away with writing something fairly simple.  And even if you are taking an approach, such as grounded theory, that pushes you to remain fairly open-minded during the data collection process, you still want to know what you will be doing with all the data collected – creating a codebook? Writing analytical memos? Comparing cases?  Having a plan in hand will also help prevent you from collecting too much extraneous data.
• Be prepared to confront controversies both within the qualitative research community and between qualitative research and quantitative research. Don’t be naïve about this – qualitative research, particularly some approaches, will be derided by many more “positivist” researchers and audiences.  For example, is an “n” of 1 really sufficient?  Yes!  But not everyone will agree.
• Do not make the mistake of using qualitative research methods because someone told you it was easier, or because you are intimidated by the math required of statistical analyses. Qualitative research is difficult in its own way (and many would claim much more time-consuming than quantitative research).  Do it because you are convinced it is right for your goals, aims, and research questions.
• Find a good support network. This could be a research mentor, or it could be a group of friends or colleagues who are also using qualitative research, or it could be just someone who will listen to you work through all of the issues you will confront out in the field and during the writing process.  Even though qualitative research often involves human subjects, it can be pretty lonely.  A lot of times you will feel like you are working without a net.  You have to create one for yourself.  Take care of yourself.
• And, finally, in the words of Patton, “Prepare to be changed. Looking deeply at other people’s lives will force you to look deeply at yourself.”
• We will actually spend an entire chapter ( chapter 3 ) looking at this question in much more detail! ↵
• Note that this might have been news to Europeans at the time, but many other societies around the world had also come to this conclusion through observation.  There is often a tendency to equate “the scientific revolution” with the European world in which it took place, but this is somewhat misleading. ↵
• Historians are a special case here.  Historians have scrupulously and rigorously investigated the social world, but not for the purpose of understanding general laws about how things work, which is the point of scientific empirical research.  History is often referred to as an idiographic field of study, meaning that it studies things that happened or are happening in themselves and not for general observations or conclusions. ↵
• Don’t worry, we’ll spend more time later in this book unpacking the meaning of ethnography and other terms that are important here.  Note the available glossary ↵

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter.  This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them.  Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

In contrast to methodology, methods are more simply the practices and tools used to collect and analyze data.  Examples of common methods in qualitative research are interviews , observations , and documentary analysis .  One’s methodology should connect to one’s choice of methods, of course, but they are distinguishable terms.  See also methodology .

A proposed explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.  The positing of a hypothesis is often the first step in quantitative research but not in qualitative research.  Even when qualitative researchers offer possible explanations in advance of conducting research, they will tend to not use the word “hypothesis” as it conjures up the kind of positivist research they are not conducting.

The foundational question to be addressed by the research study.  This will form the anchor of the research design, collection, and analysis.  Note that in qualitative research, the research question may, and probably will, alter or develop during the course of the research.

An approach to research that collects and analyzes numerical data for the purpose of finding patterns and averages, making predictions, testing causal relationships, and generalizing results to wider populations.  Contrast with qualitative research .

Data collection that takes place in real-world settings, referred to as “the field;” a key component of much Grounded Theory and ethnographic research.  Patton ( 2002 ) calls fieldwork “the central activity of qualitative inquiry” where “‘going into the field’ means having direct and personal contact with people under study in their own environments – getting close to people and situations being studied to personally understand the realities of minutiae of daily life” (48).

The people who are the subjects of a qualitative study.  In interview-based studies, they may be the respondents to the interviewer; for purposes of IRBs, they are often referred to as the human subjects of the research.

The branch of philosophy concerned with knowledge.  For researchers, it is important to recognize and adopt one of the many distinguishing epistemological perspectives as part of our understanding of what questions research can address or fully answer.  See, e.g., constructivism , subjectivism, and  objectivism .

An approach that refutes the possibility of neutrality in social science research.  All research is “guided by a set of beliefs and feelings about the world and how it should be understood and studied” (Denzin and Lincoln 2005: 13).  In contrast to positivism , interpretivism recognizes the social constructedness of reality, and researchers adopting this approach focus on capturing interpretations and understandings people have about the world rather than “the world” as it is (which is a chimera).

The cluster of data-collection tools and techniques that involve observing interactions between people, the behaviors, and practices of individuals (sometimes in contrast to what they say about how they act and behave), and cultures in context.  Observational methods are the key tools employed by ethnographers and Grounded Theory .

Research based on data collected and analyzed by the research (in contrast to secondary “library” research).

The process of selecting people or other units of analysis to represent a larger population. In quantitative research, this representation is taken quite literally, as statistically representative.  In qualitative research, in contrast, sample selection is often made based on potential to generate insight about a particular topic or phenomenon.

A method of data collection in which the researcher asks the participant questions; the answers to these questions are often recorded and transcribed verbatim. There are many different kinds of interviews - see also semistructured interview , structured interview , and unstructured interview .

The specific group of individuals that you will collect data from.  Contrast population.

The practice of being conscious of and reflective upon one’s own social location and presence when conducting research.  Because qualitative research often requires interaction with live humans, failing to take into account how one’s presence and prior expectations and social location affect the data collected and how analyzed may limit the reliability of the findings.  This remains true even when dealing with historical archives and other content.  Who we are matters when asking questions about how people experience the world because we, too, are a part of that world.

The science and practice of right conduct; in research, it is also the delineation of moral obligations towards research participants, communities to which we belong, and communities in which we conduct our research.

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Research, according to US federal guidelines, that involves “a living individual about whom an investigator (whether professional or student) conducting research:  (1) Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or  (2) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography. 

A form of interview that follows a standard guide of questions asked, although the order of the questions may change to match the particular needs of each individual interview subject, and probing “follow-up” questions are often added during the course of the interview.  The semi-structured interview is the primary form of interviewing used by qualitative researchers in the social sciences.  It is sometimes referred to as an “in-depth” interview.  See also interview and  interview guide .

A method of observational data collection taking place in a natural setting; a form of fieldwork .  The term encompasses a continuum of relative participation by the researcher (from full participant to “fly-on-the-wall” observer).  This is also sometimes referred to as ethnography , although the latter is characterized by a greater focus on the culture under observation.

A research design that employs both quantitative and qualitative methods, as in the case of a survey supplemented by interviews.

An epistemological perspective that posits the existence of reality through sensory experience similar to empiricism but goes further in denying any non-sensory basis of thought or consciousness.  In the social sciences, the term has roots in the proto-sociologist August Comte, who believed he could discern “laws” of society similar to the laws of natural science (e.g., gravity).  The term has come to mean the kinds of measurable and verifiable science conducted by quantitative researchers and is thus used pejoratively by some qualitative researchers interested in interpretation, consciousness, and human understanding.  Calling someone a “positivist” is often intended as an insult.  See also empiricism and objectivism.

A place or collection containing records, documents, or other materials of historical interest; most universities have an archive of material related to the university’s history, as well as other “special collections” that may be of interest to members of the community.

A method of both data collection and data analysis in which a given content (textual, visual, graphic) is examined systematically and rigorously to identify meanings, themes, patterns and assumptions.  Qualitative content analysis (QCA) is concerned with gathering and interpreting an existing body of material.    

A word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data (Saldaña 2021:5).

Usually a verbatim written record of an interview or focus group discussion.

The primary form of data for fieldwork , participant observation , and ethnography .  These notes, taken by the researcher either during the course of fieldwork or at day’s end, should include as many details as possible on what was observed and what was said.  They should include clear identifiers of date, time, setting, and names (or identifying characteristics) of participants.

The process of labeling and organizing qualitative data to identify different themes and the relationships between them; a way of simplifying data to allow better management and retrieval of key themes and illustrative passages.  See coding frame and  codebook.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

A detailed description of any proposed research that involves human subjects for review by IRB.  The protocol serves as the recipe for the conduct of the research activity.  It includes the scientific rationale to justify the conduct of the study, the information necessary to conduct the study, the plan for managing and analyzing the data, and a discussion of the research ethical issues relevant to the research.  Protocols for qualitative research often include interview guides, all documents related to recruitment, informed consent forms, very clear guidelines on the safekeeping of materials collected, and plans for de-identifying transcripts or other data that include personal identifying information.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

How do you write a hypothesis for qualitative research?

How to Formulate an Effective Research Hypothesis

• State the problem that you are trying to solve. Make sure that the hypothesis clearly defines the topic and the focus of the experiment.
• Try to write the hypothesis as an if-then statement. …
• Define the variables.

Why is a hypothesis inappropriate for a qualitative study?

People who argue that a hypothesis is inappropriate for a qualitative study do so because they believe that a hypothesis leads a researcher to approach the subject in a biased way. … This is because the researcher will get numerical data that will prove or disprove the hypothesis.

Does qualitative research require hypothesis?

What is Qualitative Research? In Qualitative Research: We do not test hypothesis or previous theories. happens in specific situations.

Is it possible to set hypothesis for qualitative theories?

It is certainly possible to start with a hypothesis and then design a way to test that hypothesis via qualitative methods — for example by predicting patterns that will or will not be present in the data.

What is a research hypothesis example?

Examples of Hypotheses Students who eat breakfast will perform better on a math exam than students who do not eat breakfast. Students who experience test anxiety prior to an English exam will get higher scores than students who do not experience test anxiety.

What is hypothesis example?

Examples of Hypothesis:

• If I replace the battery in my car, then my car will get better gas mileage.
• If I eat more vegetables, then I will lose weight faster.
• If I add fertilizer to my garden, then my plants will grow faster.
• If I brush my teeth every day, then I will not develop cavities.

What is used in qualitative research instead of hypothesis?

A qualitative research study would most likely employ the use of focus group discussions, case studies and in-depth interviews to find the answers to these questions; whereas in quantitative studies (especially the experimental ones), there is a tendency to control observations or assume them to be stable.

What is qualitative research examples?

A good example of a qualitative research method would be unstructured interviews which generate qualitative data through the use of open questions. This allows the respondent to talk in some depth, choosing their own words. … Photographs, videos, sound recordings and so on, can be considered qualitative data.

Is my research qualitative or quantitative?

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions. … The differences between quantitative and qualitative research.

Is there a theoretical framework in qualitative research?

Qualitative research designs may begin with a structured, or perhaps less structured theoretical framework to keep the researcher from forcing preconceptions on the findings. In the latter case, the theoretical framework often emerges in the data analysis phase.

Does qualitative research have variables?

Qualitative research has no variables. In qualitative research raw data are transformed into final description, or themes and categories.

How do we write a hypothesis?

Tips for Writing a Hypothesis

• Don’t just choose a topic randomly. Find something that interests you.
• Keep it clear and to the point.
• Use your research to guide you.
• Always clearly define your variables.
• Write it as an if-then statement. If this, then that is the expected outcome.

What are the three pillars of qualitative research?

Again, the three pillars of qualitative research are observation, you know, actually observing people behave. Focus groups, you know, and you’ve heard of what focus groups are.

Is qualitative research predictive?

Qualitative research is designed to reveal a target audience’s range of behavior and the perceptions that drive it with reference to specific topics or issues. … The results of qualitative research are descriptive rather than predictive.

Which is a method that is commonly used in qualitative research?

However, the three most commonly used qualitative research methods are in-depth interviews, focus group discussions (FGDs) and observation.

What is a good hypothesis example?

Here’s an example of a hypothesis: If you increase the duration of light, (then) corn plants will grow more each day. The hypothesis establishes two variables, length of light exposure, and the rate of plant growth. An experiment could be designed to test whether the rate of growth depends on the duration of light.

How do you write a research hypothesis example?

Which of the following is the best example of a hypothesis.

Answer: Dear if plants receives air, water, sunlight then it grows. FOR hypothesis, if a plant receives water, then it will grow.

What is simple hypothesis?

Simple hypotheses are ones which give probabilities to potential observations. The contrast here is with complex hypotheses, also known as models, which are sets of simple hypotheses such that knowing that some member of the set is true (but not which) is insufficient to specify probabilities of data points.

What makes a good hypothesis?

A good hypothesis posits an expected relationship between variables and clearly states a relationship between variables. … A hypothesis should be brief and to the point. You want the research hypothesis to describe the relationship between variables and to be as direct and explicit as possible.

How do you write a correlation hypothesis?

State the null hypothesis. The null hypothesis gives an exact value that implies there is no correlation between the two variables. If the results show a percentage equal to or lower than the value of the null hypothesis, then the variables are not proven to correlate.

What is the most commonly used instrument in research?

Questionnaire The two most commonly used research instruments in quantitative research studies include Questionnaire and Tests.

Does qualitative research use inductive or deductive reasoning?

Qualitative research is often said to employ inductive thinking or induction reasoning since it moves from specific observations about individual occurrences to broader generalizations and theories.

What is conceptual framework in qualitative research?

Your conceptual framework is the theory-based collection of principles that are relevant to your particular study. … The conceptual framework represents those research-based theories that 1) you used in creating your methods and 2) those that were relevant to your data analysis.

What are 5 examples of qualitative research?

5 Types of Qualitative Research Methods

• Ethnography. Ethnography, one of the most popular methods of qualitative research, involves the researcher embedding himself or herself into the daily life and routine of the subject or subjects. …
• Narrative. …
• Phenomenology. …
• Grounded Theory. …
• Case study.

What are examples of qualitative?

The hair colors of players on a football team, the color of cars in a parking lot, the letter grades of students in a classroom, the types of coins in a jar, and the shape of candies in a variety pack are all examples of qualitative data so long as a particular number is not assigned to any of these descriptions.

What are the 5 qualitative approaches?

The Five Qualitative approach is a method to framing Qualitative Research, focusing on the methodologies of five of the major traditions in qualitative research: biography, ethnography, phenomenology, grounded theory, and case study.

What are the two major types of research?

Types of research methods can be broadly divided into two quantitative and qualitative categories.

• Quantitative research describes, infers, and resolves problems using numbers. …
• Qualitative research, on the other hand, is based on words, feelings, emotions, sounds and other non-numerical and unquantifiable elements.

Why is qualitative research better than quantitative research?

Formulating hypotheses: Qualitative research helps you gather detailed information on a topic. … Finding general answers: Quantitative research usually has more respondents than qualitative research because it is easier to conduct a multiple-choice survey than a series of interviews or focus groups.

Why is qualitative research better?

Here are some of the main benefits: Qualitative techniques give you a unique depth of understanding which is difficult to gain from a closed question survey. Respondents are able to freely disclose their experiences, thoughts and feelings without constraint.

Graduated from ENSAT (national agronomic school of Toulouse) in plant sciences in 2018, I pursued a CIFRE doctorate under contract with Sun’Agri and INRAE ​​in Avignon between 2019 and 2022. My thesis aimed to study dynamic agrivoltaic systems, in my case in arboriculture. I love to write and share science related Stuff Here on my Website. I am currently continuing at Sun’Agri as an R&D engineer.

Related Posts

Where is photorhabdus luminescens, where is p. malariae found, how do you find p of a matrix, what does p mean in linear algebra, what does p mean in matrices, what is p-median model, what is p-toluidine used for, is toluene and methylbenzene are same, what is the structural formula of ethyl p nitrobenzoate, does p-nitrophenol absorb light, how does alkaline phosphatase affect p-nitrophenol, how many vdj combinations are possible, what is p nucleotide, what are p nucleotides, what is orbital wave function, what does the gibbs phase rule state, what is the adhesion of p pili, what does p pulmonale mean, what is the function of quinone, what are p and e selectins used for.

9 methodologies for a successful qualitative research assignment

Qualitative research is important in the educational and scientific domains. It enables a deeper understanding of phenomena, experiences, and context. Many researchers employ such research activities in the fields of history, sociology, and anthropology. For such researchers, learning quality analysis insights is crucial. This way, they can perform well throughout their research journey. Writing a qualitative research assignment is one such way to practice qualitative interpretations. When students address various qualitative questions in these projects, they become efficient in conducting these activities at a higher level, such as for a master’s or Ph.D. thesis.

The FormPlus highlights why researchers prefer qualitative research over quantitative research. It is faster, scientific, objective, focused, and acceptable. Researchers who don’t know what to expect from the research outcomes usually choose qualitative research. In this guide, we will discuss the top methodologies that students can employ while writing their qualitative research assignments. This way, you can write an appealing document that perfectly demonstrates your qualitative research skills.

However, being stressed with academic and daily life commitments, if you find it challenging to manage time exclusively for such projects, availing of assignment writing services can make it manageable. Instead of doing anything wrong in the hustle, get it done by the professionals specifically working to handle these academic write-ups. Now, let’s define quality research before we discuss the actual topic.

What is meant by qualitative research?

Quality research is a market research method that gathers data from conversational and open-ended communication. In simple words, it is about what people think and why they think so. It relates to the nature or standard of something rather than dealing with its quantity. Such researchers collect nonnumerical data to understand opinions, concepts, and ideas.

How do you write a qualitative research assignment? Top 9 methodologies

Writing an assignment requires your command of various tasks. Qualitative research assignment design involves research, writing, structuring, and providing citations of the resources used. Assignment writing plays a crucial role in upgrading your grades.

So, you must make it accurate and authentic. Write it with the utmost care without skipping any important aspects. Sometimes, it can be hard, but it becomes easy if you correctly use effective methodologies. This is why we have brought together some of the common methodologies you can use to write your qualitative research assignments.

1. Interviews

A qualitative interview is mostly used in projects that involve market research. In this study personal interaction is required to collect in-depth information of the participants. In qualitative research for assignment, consider the interview as a personal form of research agenda rather than a focused group study. A qualitative interview requires careful planning so that you can gather meaningful data.

Here are the simple steps to consider for its implementation in a qualitative research assignment:

• Define research objectives.
• Identify the target population.
• Obtain informed consent of participants.
• Make an interview guideline.
• Select a suitable location.
• Conduct the interview.
• Show respect for participant’s perspectives.
• Analyse the data.

2. Observation

In qualitative observation, the researcher gathers data from five senses: sight, hearing, touch, smell, and taste. It is a subject approach that depends on the sensory organ of the researcher. This method allows you to better understand the culture, process, and people under study. Some of its characteristics to consider for writing a qualitative research assignment include,

• It is a naturalistic inquiry of the participants in a natural environment.
• This approach is subjective and depends on the researcher’s observation.
• It does not seek a definite answer to a query.
• The researcher can recognise their own biases when compiling findings.

3. Questionnaires

In this type of survey, the researcher asks open-ended questions to participants. This way, they price the long written or typed document. In writing qualitative research assignments, these questions aim to reveal the participants’ narratives and experiences. Once you know what type of information you need, you can start curating your questionnaire form. The questions must be specific and clear enough that the participants can comprehend them.

Below are the main points that must be considered when creating qualitative research questionnaires.

• Avoid jargon and ambiguity in the questions.
• Each question should contribute to the research objectives.
• Use simple language.
• The questions should be neutral and unbiased.
• Be precise, as the complex questions can overwhelm the respondents.
• Always conduct a pilot test.
• Put yourself in the respondent’s shoes while asking questions.

4. Case Study

A case study is a detailed analysis of a person, place, thing, organisation, or phenomenon. This method is appropriate when you want to gain a contextual, concrete, and in-depth understanding of the real-world problem for writing your qualitative research assignment. This method is especially helpful when you need more time to conduct large-scale research activities.

The four crucial steps below can be followed up with this methodology.

• Select a case that has the potential to provide new and unexpected insights into the subject.
• Make a theoretical framework.
• Collect your data from various primary and secondary resources.
• Describe and analyse the case to provide a clear picture of the subject.

5. Focus Groups

Focused group research has some interesting properties. In this method, a planned interview is conducted within a small group. For this purpose, some of the participants are sampled from the study population to record data for writing a qualitative research assignment. Typically, a focused group has features like,

• At least four to ten participants must meet for up to two hours.
• There must be a facilitator who can guide the discussion by asking open-ended questions.
• The emphasis must be put on the group discussion rather than the discussion of the group members with the facilitator.
• The discussion should be recorded and transcribed by the researchers.

6. Ethnographic Research

It is the most in-depth research method that involves studying people in their natural environment. It requires the researcher to adopt the target audience environment. The environment can be anything from an organisation to a city or any remote location.

However, the geographical constraints can be a problem in this study. For students who are writing their qualitative research assignment, some of the features of ethnographic research to write in their document include,

• The researcher can get a more realistic picture of the study.
• It uncovers extremely valuable insights.
• Provides accurate predictions.
• You can extend the observation to create more in-depth data.
• You can interact with people within a particular context.

7. Record Keeping

This method is similar to going to the library to collect data from books. You consult various relayed books, note the important points, and take note of the referencing. So, the researcher uses already existing data rather than introducing new things in the field.

Later on, this data can be used to conduct new research. Yet, when faced with the vast resources available in your institution’s library, seeking assistance from UK-based assignment writing services is an excellent solution if you need help pinpointing the most relevant information for your topic. Proficient in data gathering and adept at structuring qualitative research assignments, these professionals can significantly elevate your academic results.

This method is mostly used by companies to understand a group of customers’ behaviour, characteristics, and motivation. It allows respondents to ask in-depth questions about their experience. In a business market, it helps you understand how your customers make decisions. The intent is to understand them at their level and make related changes in your setup. The researcher must ask generic and precise questions that have a clear purpose.

Consider the below examples of qualitative survey questions. It can be useful in recording data and writing qualitative research assignments.

• Why did you buy this skin care product?
• What is the overall narrative of this brand?
• How do you feel after buying this product?
• What sets this brand apart from others?
• How will this product fulfil your needs?
• What are the things that you expect from this brand to grant you?

9. Action Research

This method involves collaboration and empowerment of the participants. It is mostly appropriate for marginalised groups where there is no flexibility.

The primary characteristics of the action research that can be quoted in your qualitative research assignment include,

• It is action-oriented, and participants are actively involved in the research.
• There is a collaborative process between participants and researchers.
• The nature of action research is flexible to the changing situation.

However, the survey also accompanies some of the limitations, including,

• The researcher can misinterpret the open-ended questions.
• The data ownership between the researcher and participants needs to be negotiated.
• The ethical considerations must be kept.
• It is not considered a scientific method as it is fluid in data collection. Consequently, it may not attract the finding.

What is the difference between quantitative and qualitative research?

Both research types share the common aim of knowledge acquisition. In quantitative research, the use of numbers and objective measures is used. It seeks answers to questions like when and where.

On the other hand, in qualitative research, the researcher is concerned with subjective phenomena. Such data can’t be numerically measured. For example, you might conduct a survey to analyse how different people experience grief.

What are the 4 types of qualitative research?

There are various types of qualitative research. It may include,

● Phenomenological studies:

It examines the human experience via description provided by the people involved. These are the lived experiences of the people. It is usually used in research areas where little knowledge is known.

● Ethnographic studies:

It involves the analysis of data about cultural groups. In such analysis, the researcher mostly lives with different communities and becomes part of their culture to provide solid interpretations.

● Grounded theory studies:

In this qualitative approach, the researcher collects and analyses the data. Later on, a theory is developed that is grounded in the data. It used both inductive and deductive approaches for theory development.

● Historical studies:

It is concerned with the location, identification, evaluation, and synthesis of data from the past. These researchers are not concerned with discovering past events but with relating these events to the present happenings.

The Research Gate provides a flow chart illustrating various qualitative research methods.

What are The 7 characteristics of qualitative research?

The following are some of the distinct features of qualitative research. You can write about them in your qualitative research assignment, as they are collected from reliable sources.

• It can even capture the changing attitude within the target group.
• It is beyond the limitations associated with quantitative research
• It explains something that numbers alone can’t describe.
• It is a flexible approach to improve the outcomes.
• A researcher is not supposed to become more speculative about the results.
• This approach is more targeted.
• It keeps the cost of data collection down.

What are the advantages and disadvantages of qualitative research?

The pros of qualitative research can’t be denied. However, some cons are also associated with this research.

• Explore attitudes and behaviours in depth.
• It encourages discussions for better results.
• Generate descriptive data that can formulate new theories.
• The small sample size can be a problem.
• Bias in the sample collection.
• Lack of privacy if you are covering a sensitive topic.

Qualitative research assignment examples

The Afe Babalola University ePortal provides an example of a qualitative assignment. Here is the description of quality questions and related answers. You can get an idea about how to handle your quality research assignment project with this sample.

The questions asked in the paper are displayed below.

The Slide Team presents a template for further compressing other details, such as the qualitative research assignment template. You can use it to make your presentation look professional.

Writing a qualitative research assignment is crucial, especially if you want to engage in research activities for your master’s thesis. Most researchers choose this method because of the associated credibility and reliability of the results. In the above guide, we have discussed some of the prominent features of this method. All of the given data can help you in writing your assignments. We have discussed the benefits of each methodology and a brief account of how you can carry it.

However, even after going through this whole guideline, if the concepts of the Qualitative Research methods assignment seem ambiguous and you think you can’t write a good project, then ask professional to “ write my assignment .” These experts can consult the best sources for the data collection of your project. Consequently, they will deliver you the winning document that can stand out among other write-ups.