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Formulation of Hypothesis
- Addiction Treatment Theories
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Children who spend more time playing outside are more likely to be imaginative. What do you think this statement is an example of in terms of scientific research? If you guessed a hypothesis, then you'd be correct. The formulation of hypotheses is a fundamental step in psychology research.
- First, we will discuss the importance of hypotheses in research.
- We will then cover formulating hypotheses in research, including the steps in the formulation of hypotheses in research methodology.
- We will provide examples of hypotheses in research throughout the explanation.
- Finally, we will delve into the different types of hypotheses in research.
What is a Hypothesis?
The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research. To be classed as scientific research, it must be observable, valid, reliable and follow a standardised procedure.
One of the important steps in scientific research is to formulate a hypothesis before starting the study procedure.
The hypothesis is a predictive, testable statement predicting the outcome and the results the researcher expects to find.
The hypothesis provides a summary of what direction, if any, is taken to investigate a theory.
In scientific research, there is a criterion that hypotheses need to be met to be regarded as acceptable.
If a hypothesis is disregarded, the research may be rejected by the community of psychology researchers.
Importance of Hypothesis in Research
The purpose of including hypotheses in psychology research is:
- To provide a summary of the research, how it will be investigated, and what is expected to be found.
- To provide an answer to the research question.
When carrying out research, researchers first investigate the research area they are interested in. From this, researchers are required to identify a gap in the literature.
Filling the gap essentially means finding what previous work has not been explained yet, investigated to a sufficient degree, or simply expanding or further investigating a theory if doubt exists.
The researcher then forms a research question that the researcher will attempt to answer in their study.
Remember, the hypothesis is a predictive statement of what is expected to happen when testing the research question.
The hypothesis can be used for later data analysis. This includes inferential tests such as hypothesis testing and identifying if statistical findings are significant.

Steps in the Formulation of Hypothesis in Research Methodology
Researchers must follow certain steps to formulate testable hypotheses when conducting research.
Overall, the researcher has to consider the direction of the research, i.e. will it be looking for a difference caused by independent variables? Or will it be more concerned with the correlation between variables?
All researchers will likely complete the following.
- Investigating background research in the area of interest.
- Formulating or investigating a theory.
- Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works.
The above steps are used to formulate testable hypotheses.
The Formulation of Testable Hypotheses
The hypothesis is important in research as it indicates what and how a variable will be investigated.
The hypothesis essentially summarises what and how something will be investigated. This is important as it ensures that the researcher has carefully planned how the research will be done, as the researchers have to follow a set procedure to conduct research.
This is known as the scientific method.
Formulating Hypotheses in Research
When formulating hypotheses, things that researchers should consider are:
Types of Hypotheses in Research
Researchers can propose different types of hypotheses when carrying out research.
The following research scenario will be discussed to show examples of each type of hypothesis that the researchers could use. "A research team was investigating whether memory performance is affected by depression."
The identified independent variable is the severity of depression scores, and the dependent variable is the scores from a memory performance task.
The null hypothesis predicts that the results will show no or little effect. The null hypothesis is a predictive statement that researchers use when it is thought that the IV will not influence the DV.
In this case, the null hypothesis would be there will be no difference in memory scores on the MMSE test of those who are diagnosed with depression and those who are not.
An alternative hypothesis is a predictive statement used when it is thought that the IV will influence the DV. The alternative hypothesis is also called a non-directional, two-tailed hypothesis, as it predicts the results can go either way, e.g. increase or decrease.
The example in this scenario is there will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.
The directional alternative hypothesis states how the IV will influence the DV, identifying a specific direction, such as if there will be an increase or decrease in the observed results.
The example in this scenario is people with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.
Example Hypothesis in Research
To summarise, let's look at an example of a straightforward hypothesis that indicates the relationship between two variables : the independent and the dependent.
If you stay up late, you will feel tired the following day; the more caffeine you drink, the harder you find it to fall asleep, or the more sunlight plants get, the taller they will grow.
Formulation of Hypothesis - Key Takeaways
- The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research . One of the important steps in scientific research is to create a hypothesis.
- The hypothesis is a predictive, testable statement concerning the outcome/results that the researcher expects to find.
- Hypotheses are needed in research to provide a summary of what the research is, how to investigate a theory and what is expected to be found, and to provide an answer to the research question so that the hypothesis can be used for later data analysis.
- There are requirements for the formulation of testable hypotheses. The hypotheses should identify and operationalise the IV and DV. In addition, they should describe the nature of the relationship between the IV and DV.
- There are different types of hypotheses: Null hypothesis, Alternative hypothesis (this is also known as the non-directional, two-tailed hypothesis), and Directional hypothesis (this is also known as the one-tailed hypothesis).
Frequently Asked Questions about Formulation of Hypothesis
--> what are the 3 types of hypotheses.
The three types of hypotheses are:
- Null hypothesis
- Alternative hypothesis
- Directional/non-directional hypothesis
--> What is an example of a hypothesis in psychology?
An example of a null hypothesis in psychology is, there will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.
--> What are the steps in formulating a hypothesis?
All researchers will likely complete the following
- Investigating background research in the area of interest
- Formulating or investigating a theory
- Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works
--> What is formulation of hypothesis in research?
The formulation of a hypothesis in research is when the researcher formulates a predictive statement of what is expected to happen when testing the research question based on background research.
--> How to formulate null and alternative hypothesis?
When formulating a null hypothesis the researcher would state a prediction that they expect to see no difference in the dependent variable when the independent variable changes or is manipulated. Whereas, when using an alternative hypothesis then it would be predicted that there will be a change in the dependent variable. The researcher can state in which direction they expect the results to go.
Final Formulation of Hypothesis Quiz
Formulation of hypothesis quiz - teste dein wissen.
What type of hypothesis matches the following definition. A predictive statement that researchers use when it is thought that the IV will not influence the DV.
Show answer
Null hypothesis
Show question
What type of hypothesis matches the following definition. A hypothesis that states that the IV will influence the DV. But, the hypothesis does not state how the IV will influence the DV.
Alternative hypothesis
What type of hypothesis matches the following definition. A hypothesis that states that the IV will influence the DV, and states how it will influence the DV.
Directional, alternative hypothesis
Which type of hypothesis is also known as a two-tailed hypothesis?
What type of hypothesis is the following example. There will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.
What type of hypothesis is the following example. There will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.
What type of hypothesis is the following example. People with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.
What is a hypothesis?
The hypothesis is a predictive, testable statement concerning the outcome/ results the researcher expects to find.
What method states that a hypothesis needs to be formulated to produce good research?
The scientific method states that researchers need to formulate a good hypothesis before starting the research.
What steps do researchers need to take when formulating a testable hypothesis?
- Investigating background research in the area of interest
- Formulating or investigating a theory
- Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works
Why are hypotheses needed in research?
Hypotheses are needed in research:
- to provide a summary of what the researcher is and how investigating a theory and what is expected to be found
- to provide an answer to the research question
- so that the hypothesis can be used for later data analysis
What type of data analysis may hypotheses be needed for?
Hypotheses are needed when doing inferential tests such as hypothesis testing. In addition, identifying if research findings are statistically significant.
What are the requirements of a good hypothesis?
A good hypothesis should:
- identify and operationalise the independent and dependent variable
- be testable
- be falsifiable
- predictive statements
Is the following example a falsifiable hypothesis, "leprechauns always find the pot of gold at the end of the rainbow".
Is memory an operationalised variable that could be used in a good hypothesis?
What is an operationalised variable?
An operationalised variable is when the researcher describes how a variable (independent or dependent variable) will be measured. The operationalisation of variables also needs to be defined. For example, memory may be operationalised by stating performance in memory tasks such as the Mini-Mental Status Examination.
What happens if a hypothesis is regarded as not meeting the standards of scientific research?
If a hypothesis is disregarded, the research may be rejected by the community of psychology researchers.
What is a hypothesis predicting?
The hypothesis predicts the nature of the relationship between the independent and dependent variables. For instance, if the dependent variable changes due to changes/ manipulation of the independent variable.
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Entries a-z, subject index.
- Hypothesis Formulation
- By: YoungJu Shin & Yu Lu
- In: The SAGE Encyclopedia of Communication Research Methods
- Chapter DOI: https:// doi. org/10.4135/9781483381411
- Subject: Communication and Media Studies , Sociology
- Show page numbers Hide page numbers
A hypothesis is used to explain a phenomenon or predict a relationship in communication research. There are four evaluation criteria that a hypothesis must meet. First, it must state an expected relationship between variables. Second, it must be testable and falsifiable; researchers must be able to test whether a hypothesis is truth or false. Third, it should be consistent with the existing body of knowledge. Finally, it should be stated as simply and concisely as possible.
Formulating a hypothesis requires a specific, testable, and predictable statement driven by theoretical guidance and/or prior evidence. A hypothesis can be formulated in various research designs. In experimental settings, researchers compare two or more groups of research participants to investigate the differences of the research outcomes. These ...
Human–Computer Interaction
- Hypothesis Testing, Logic of
- Authoring: Telling a Research Story
- Body Image and Eating Disorders
- Methodology, Selection of
- Program Assessment
- Research Ideas, Sources of
- Research Project, Planning of
- Research Question Formulation
- Research Topic, Definition of
- Research, Inspiration for
- Social Media: Blogs, Microblogs, and Twitter
- Testability
- Acknowledging the Contribution of Others
- Activism and Social Justice
- Anonymous Source of Data
- Authorship Bias
- Authorship Credit
- Confidentiality and Anonymity of Participants
- Conflict of Interest in Research
- Controversial Experiments
- Copyright Issues in Research
- Cultural Sensitivity in Research
- Data Security
- Debriefing of Participants
- Deception in Research
- Ethical Issues, International Research
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- Fraudulent and Misleading Data
- Funding Research
- Health Care Disparities
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- Peer Review
- Plagiarism, Self-
- Privacy of Information
- Privacy of Participants
- Public Behavior, Recording of
- Reliability, Unitizing
- Research Ethics and Social Values
- Researcher-Participant Relationships
- Social Implications of Research
- Archive Searching for Research
- Bibliographic Research
- Databases, Academic
- Foundation and Government Research Collections
- Library Research
- Literature Review, The
- Literature Reviews, Foundational
- Literature Reviews, Resources for
- Literature Reviews, Strategies for
- Literature Sources, Skeptical and Critical Stance Toward
- Literature, Determining Quality of
- Literature, Determining Relevance of
- Meta-Analysis
- Publications, Scholarly
- Search Engines for Literature Search
- Vote Counting Literature Review Methods
- Abstract or Executive Summary
- Academic Journals
- Alternative Conference Presentation Formats
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- Archiving Data
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- Citations to Research
- Evidence-Based Policy Making
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- Narrative Literature Review
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- Title of Manuscript, Selection of
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- Writer’s Block
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- Coding of Data
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- Conversation Analysis
- Critical Analysis
- Discourse Analysis
- Interaction Analysis, Quantitative
- Intercoder Reliability
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- Intercoder Reliability Standards: Reproducibility
- Intercoder Reliability Standards: Stability
- Intercoder Reliability Techniques: Cohen’s Kappa
- Intercoder Reliability Techniques: Fleiss System
- Intercoder Reliability Techniques: Holsti Method
- Intercoder Reliability Techniques: Krippendorf Alpha
- Intercoder Reliability Techniques: Percent Agreement
- Intercoder Reliability Techniques: Scott’s Pi
- Metrics for Analysis, Selection of
- Narrative Analysis
- Observational Research Methods
- Observational Research, Advantages and Disadvantages
- Observer Reliability
- Rhetorical and Dramatism Analysis
- Unobtrusive Analysis
- Association of Internet Researchers (AoIR)
- Computer-Mediated Communication (CMC)
- Internet as Cultural Context
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- Factor Analysis
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- Implicit Measures
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- Observational Measurement: Face Features
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- Organizational Identification
- Outlier Analysis
- Physiological Measurement
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- Physiological Measurement: Pupillary Response
- Physiological Measurement: Skin Conductance
- Reaction Time
- Reliability of Measurement
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- Scales, Forced Choice
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- Standard Score
- Time Series Notation
- Validity, Concurrent
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- Validity, Face and Content
- Validity, Halo Effect
- Validity, Measurement of
- Validity, Predictive
- Variables, Conceptualization
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- Z Transformation
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- Generalization
- Imagined Interactions
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- Matched Groups
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- Random Assignment of Participants
- Respondents
- Response Style
- Treatment Groups
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- Experience Sampling Method
- Sample Versus Population
- Sampling Decisions
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- Sampling, Internet
- Sampling, Methodological Issues in
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- Sampling, Nonprobability
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- Survey: Questionnaire
- Survey: Sampling Issues
- Survey: Structural Questions
- Surveys, Advantages and Disadvantages of
- Surveys, Using Others’
- Under-represented Group
- Alternative News Media
- Analytic Induction
- Archival Analysis
- Artifact Selection
- Autoethnography
- Axial Coding
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- Close Reading
- Coding, Fixed
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- Post Hoc Tests: Tukey Honestly Significance Difference Test
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- Blocking Variable
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- Counterbalancing
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- Degrees of Freedom
- Delayed Measurement
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- Median Split of Sample
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- Multitrial Design
- Null Hypothesis
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- Orthogonality
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- Pilot Study
- Population/Sample
- Power Curves
- Quantitative Research, Purpose of
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- Quasi-Experimental Design
- Random Assignment
- Replication
- Research Proposal
- Sampling Theory
- Sampling, Determining Size
- Solomon Four-Group Design
- Stimulus Pre-test
- Two-Group Pretest–Posttest Design
- Two-Group Random Assignment Pretest–Posttest Design
- Variables, Control
- Variables, Dependent
- Variables, Independent
- Variables, Latent
- Variables, Marker
- Variables, Mediating Types
- Variables, Moderating Types
- Within-Subjects Design
- Analysis of Residuals
- Bivariate Statistics
- Bootstrapping
- Confidence Interval
- Conjoint Analysis
- Contrast Analysis
- Correlation, Pearson
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- Covariance/Variance Matrix
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- Discriminant Analysis
- Kendall’s Tau
- Kruskal-Wallis Test
- Linear Regression
- Linear Versus Nonlinear Relationships
- Multicollinearity
- Multiple Regression
- Multiple Regression: Block Analysis
- Multiple Regression: Covariates in Multiple Regression
- Multiple Regression: Multiple R
- Multiple Regression: Standardized Regression Coefficient
- Partial Correlation
- Phi Coefficient
- Semi-Partial r
- Simple Bivariate Correlation
- Categorization
- Cluster Analysis
- Data Transformation
- Errors of Measurement
- Errors of Measurement: Attenuation
- Errors of Measurement: Ceiling and Floor Effects
- Errors of Measurement: Dichotomization of a Continuous Variable
- Errors of Measurement: Range Restriction
- Errors of Measurement: Regression Toward the Mean
- Frequency Distributions
- Heterogeneity of Variance
- Heteroskedasticity
- Homogeneity of Variance
- Intraclass Correlation
- Mean, Arithmetic
- Mean, Geometric
- Mean, Harmonic
- Measures of Central Tendency
- Mortality in Sample
- Normal Curve Distribution
- Relationships Between Variables
- Sensitivity Analysis
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- Simple Descriptive Statistics
- Standard Deviation and Variance
- Standard Error
- Standard Error, Mean
- Statistical Power Analysis
- Type I error
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- Univariate Statistics
- Variables, Categorical
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- Variables, Defining
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- Autoregressive, Integrative, Moving Average (ARIMA) Models
- Binomial Effect Size Display
- Cloze Procedure
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- Cross-Lagged Panel Analysis
- Curvilinear Relationship
- Effect Sizes
- Hierarchical Linear Modeling
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- Margin of Error
- Markov Analysis
- Maximum Likelihood Estimation
- Meta-Analysis: Estimation of Average Effect
- Meta-Analysis: Fixed Effects Analysis
- Meta-Analysis: Literature Search Issues
- Meta-Analysis: Model Testing
- Meta-Analysis: Random Effects Analysis
- Meta-Analysis: Statistical Conversion to Common Metric
- Multivariate Analysis of Variance (MANOVA)
- Multivariate Statistics
- Ordinary Least Squares
- Path Analysis
- Probit Analysis
- Structural Equation Modeling
- Time-Series Analysis
- Acculturation
- African American Communication and Culture
- Agenda Setting
- Applied Communication
- Argumentation Theory
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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).

Essential 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 an effective 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
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.

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
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How to Write a Great Hypothesis
Hypothesis Format, Examples, and Tips
Kendra Cherry, MS, is an author and educational consultant focused on helping students learn about psychology.
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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 Kendra Cherry, MS, is an author and educational consultant focused on helping students learn about psychology.
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The formulation of a hypothesis in research is when the researcher formulates a predictive statement of what is expected to happen when testing the research
Before formulating your research hypothesis, read about the topic of interest to you. From your reading, which may include articles, books and/or cases
Formulating a hypothesis requires a specific, testable, and predictable statement driven by theoretical guidance and/or prior evidence. A hypothesis can be
It is a precise, testable statement of what the researchers predict will be outcome of the study. Hypothesis usually involves proposing a relationship between
A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet
A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe
When formulating the hypothesis(es) for your study, there are a few things you need to keep ... A research hypothesis is a statement of expectation or.
Formulating a Hypothesis ... You have a question and now you need to turn it into a hypothesis. A hypothesis is an educated prediction that
Clearly state the prediction you are proposing. Make sure that the hypothesis clearly defines the topic and the focus of the study. · Aim to write the hypothesis
A hypothesis is a statement that introduces your research question and suggests the results you might find. It is an educated guess. You start by posing an