what makes an hypothesis testable

• Science, Tech, Math ›
• Chemistry ›
• Scientific Method ›

What Is a Testable Hypothesis?

• Scientific Method
• Chemical Laws
• Periodic Table
• Projects & Experiments
• Biochemistry
• Physical Chemistry
• Medical Chemistry
• Chemistry In Everyday Life
• Famous Chemists
• Activities for Kids
• Abbreviations & Acronyms
• Weather & Climate
• Ph.D., Biomedical Sciences, University of Tennessee at Knoxville
• B.A., Physics and Mathematics, Hastings College

A hypothesis is a tentative answer to a scientific question. A testable hypothesis is a  hypothesis that can be proved or disproved as a result of testing, data collection, or experience. Only testable hypotheses can be used to conceive and perform an experiment using the scientific method .

Requirements for a Testable Hypothesis

In order to be considered testable, two criteria must be met:

• It must be possible to prove that the hypothesis is true.
• It must be possible to prove that the hypothesis is false.
• It must be possible to reproduce the results of the hypothesis.

Examples of a Testable Hypothesis

All the following hypotheses are testable. It's important, however, to note that while it's possible to say that the hypothesis is correct, much more research would be required to answer the question " why is this hypothesis correct?" 

• Students who attend class have higher grades than students who skip class.  This is testable because it is possible to compare the grades of students who do and do not skip class and then analyze the resulting data. Another person could conduct the same research and come up with the same results.
• People exposed to high levels of ultraviolet light have a higher incidence of cancer than the norm.  This is testable because it is possible to find a group of people who have been exposed to high levels of ultraviolet light and compare their cancer rates to the average.
• If you put people in a dark room, then they will be unable to tell when an infrared light turns on.  This hypothesis is testable because it is possible to put a group of people into a dark room, turn on an infrared light, and ask the people in the room whether or not an infrared light has been turned on.

Examples of a Hypothesis Not Written in a Testable Form

• It doesn't matter whether or not you skip class.  This hypothesis can't be tested because it doesn't make any actual claim regarding the outcome of skipping class. "It doesn't matter" doesn't have any specific meaning, so it can't be tested.
• Ultraviolet light could cause cancer.  The word "could" makes a hypothesis extremely difficult to test because it is very vague. There "could," for example, be UFOs watching us at every moment, even though it's impossible to prove that they are there!
• Goldfish make better pets than guinea pigs.  This is not a hypothesis; it's a matter of opinion. There is no agreed-upon definition of what a "better" pet is, so while it is possible to argue the point, there is no way to prove it.

How to Propose a Testable Hypothesis

Now that you know what a testable hypothesis is, here are tips for proposing one.

• Try to write the hypothesis as an if-then statement. If you take an action, then a certain outcome is expected.
• Identify the independent and dependent variable in the hypothesis. The independent variable is what you are controlling or changing. You measure the effect this has on the dependent variable.
• Write the hypothesis in such a way that you can prove or disprove it. For example, a person has skin cancer, you can't prove they got it from being out in the sun. However, you can demonstrate a relationship between exposure to ultraviolet light and increased risk of skin cancer.
• Make sure you are proposing a hypothesis you can test with reproducible results. If your face breaks out, you can't prove the breakout was caused by the french fries you had for dinner last night. However, you can measure whether or not eating french fries is associated with breaking out. It's a matter of gathering enough data to be able to reproduce results and draw a conclusion.
• What Are Examples of a Hypothesis?
• What Is a Hypothesis? (Science)
• What Are the Elements of a Good Hypothesis?
• Scientific Method Flow Chart
• Null Hypothesis Examples
• Scientific Hypothesis Examples
• Understanding Simple vs Controlled Experiments
• Six Steps of the Scientific Method
• Scientific Method Vocabulary Terms
• Scientific Variable
• What Is an Experimental Constant?
• What Is a Controlled Experiment?
• What Is the Difference Between a Control Variable and Control Group?
• DRY MIX Experiment Variables Acronym
• Random Error vs. Systematic Error
• The Role of a Controlled Variable in an Experiment

• Thesis Action Plan New
• Academic Project Planner

Literature Navigator

Thesis dialogue blueprint, writing wizard's template, research proposal compass.

• See Success Stories
• Access Free Resources
• Why we are different
• All Products
• Coming Soon

What Makes a Good Hypothesis? Essential Criteria and Examples

A well-formulated hypothesis is a cornerstone of scientific research, providing direction and focus for investigations. It serves as a bridge between theory and experiment, guiding researchers in their quest to explore, test, and validate scientific phenomena. In this article, we will delve into what makes a good hypothesis by examining its essential criteria and providing illustrative examples.

Key Takeaways

• A good hypothesis should be clear and precise, avoiding vague language and ambiguity.
• It must be testable and falsifiable, meaning it can be supported or refuted through experimentation.
• Grounding in existing knowledge is crucial; a hypothesis should be based on prior research or established theories.
• Formulating a hypothesis involves identifying variables and constructing if-then statements to define cause-and-effect relationships.
• Common pitfalls in hypothesis development include vagueness, double-barreled hypotheses, and lack of relevance to research objectives.

Defining a Hypothesis in Research

A hypothesis is a foundational element in scientific research, serving as a proposed explanation for a phenomenon that can be tested through experimentation and observation. It is a precise, testable statement predicting the outcome of a study, typically involving a relationship between an independent variable (what the researcher changes) and a dependent variable (what the researcher measures).

Essential Characteristics of a Good Hypothesis

A well-crafted hypothesis is fundamental to any research endeavor. It serves as a guiding framework for your study, ensuring that your research is focused and meaningful. Here are the essential characteristics that define a good hypothesis:

Formulating a Testable Hypothesis

Creating a testable hypothesis is a crucial step in the research process. A well-formulated hypothesis should be specific and measurable , allowing for clear and definitive testing. This section will guide you through the essential steps to ensure your hypothesis is both testable and meaningful.

Common Pitfalls to Avoid in Hypothesis Development

Avoiding vagueness.

One of the most frequent mistakes in hypothesis development is formulating vague or ambiguous hypotheses . A well-defined hypothesis should be clear and specific , leaving no room for multiple interpretations. For instance, instead of saying, "There is a relationship between study habits and academic performance," specify the type of study habits and the metrics for academic performance.

Steering Clear of Double-Barreled Hypotheses

A double-barreled hypothesis combines two or more variables in a single statement, making it difficult to test each variable independently. For example, "Increased exercise and a balanced diet improve mental health" is problematic because it conflates two distinct variables. Instead, separate the hypotheses: "Increased exercise improves mental health" and "A balanced diet improves mental health."

Ensuring Relevance to Research Objectives

Your hypothesis must align with your research objectives. Irrelevant hypotheses can lead to wasted resources and time. Ensure that your hypothesis directly addresses the core question of your research. For example, if your research focuses on the impact of social media on teenage self-esteem , a hypothesis about social media's effect on adult self-esteem would be misaligned.

By avoiding these common pitfalls, you can develop a robust and testable hypothesis that will significantly enhance the validity of your research.

Examples of Effective Hypotheses

Hypotheses in social sciences.

In social sciences, hypotheses often explore relationships between variables such as behavior, attitudes, and social structures. For instance, a hypothesis might state, "Individuals who participate in community service are more likely to report higher levels of life satisfaction." This hypothesis is clear and specific , making it testable through surveys or observational studies.

Hypotheses in Natural Sciences

Natural sciences frequently involve hypotheses that predict natural phenomena or biological processes. An example could be, "Plants exposed to classical music will grow taller than those that are not." This hypothesis is grounded in existing knowledge about the effects of sound on plant growth and can be tested through controlled experiments.

Hypotheses in Applied Research

Applied research often aims to solve practical problems, leading to hypotheses like, "Implementing a four-day workweek will increase employee productivity." This hypothesis is relevant to organizational studies and can be tested by comparing productivity metrics before and after the implementation of the new work schedule.

Evaluating and Refining Hypotheses

Peer review and feedback.

Engaging in peer review is crucial for refining your hypothesis. Soliciting feedback from colleagues or mentors can provide new perspectives and identify potential weaknesses. This collaborative approach ensures that your hypothesis is robust and well-grounded in targeted research .

Iterative Refinement

Hypothesis development is an iterative process. After initial feedback, you should revisit and revise your hypothesis. This may involve adjusting variables, rephrasing for clarity, or incorporating new data. The goal is to enhance the testability and precision of your hypothesis.

Aligning with Research Design

Your hypothesis must align with your overall research design. Ensure that it is compatible with your methodology, data collection techniques, and analysis plan. This alignment is essential for the hypothesis to be effectively tested and validated within the context of your study.

Evaluating and refining hypotheses is a crucial step in any research process. It allows you to test your assumptions and improve the accuracy of your findings. If you're struggling with this phase, our step-by-step Thesis Action Plan can guide you through it with ease. Visit our website to learn more and claim your special offer now!

In conclusion, crafting a good hypothesis is a fundamental step in the scientific method and essential for conducting meaningful research. A well-formulated hypothesis should be clear, concise, and testable, providing a predictive statement that can be empirically evaluated. By ensuring that your hypothesis is grounded in existing literature and theory, you enhance its validity and relevance. The examples and criteria discussed in this article serve as a guide to help researchers develop robust hypotheses that can withstand rigorous testing and contribute valuable insights to their respective fields. Ultimately, a strong hypothesis not only guides the direction of your research but also lays the foundation for scientific discovery and advancement.

Frequently Asked Questions

What is a hypothesis in research.

A hypothesis is a testable prediction about the relationship between two or more variables. It serves as a foundation for scientific inquiry, guiding the research process and helping to formulate experiments.

What are the essential characteristics of a good hypothesis?

A good hypothesis should be clear and precise, testable and falsifiable, and grounded in existing knowledge. It should also include an if-then statement that defines the relationship between variables.

How do you formulate a testable hypothesis?

To formulate a testable hypothesis, identify the variables involved, construct an if-then statement, and ensure that the hypothesis is measurable. This process helps in designing experiments that can validate or refute the hypothesis.

What are common pitfalls to avoid when developing a hypothesis?

Common pitfalls include vagueness, double-barreled hypotheses (addressing more than one issue at a time), and lack of relevance to the research objectives. Avoiding these pitfalls ensures that the hypothesis is clear and focused.

Can you provide examples of effective hypotheses?

Effective hypotheses can be found in various fields. For example, in social sciences: 'If social media usage increases, then levels of anxiety among teenagers will increase.' In natural sciences: 'If the temperature of water increases, then the solubility of salt will increase.'

How can hypotheses be evaluated and refined?

Hypotheses can be evaluated and refined through peer review and feedback, iterative refinement, and alignment with the overall research design. This process helps in improving the clarity and testability of the hypothesis.

Discovering Statistics Using IBM SPSS Statistics: A Fun and Informative Guide

Unlocking the Power of Data: A Review of 'Essentials of Modern Business Statistics with Microsoft Excel'

Discovering Statistics Using SAS: A Comprehensive Review

Why AI is the Key to Unlocking Your Full Research Potential

Master’s Thesis Research Overload? How to Find the Best Sources—Fast

Abstract vs. Introduction: Which One Sets the Tone for Your Thesis?

Thesis Action Plan

• Rebels Blog
• Blog Articles
• Affiliate Program
• Terms and Conditions
• Payment and Shipping Terms
• Privacy Policy
• Return Policy

© 2024 Research Rebels, All rights reserved.

Your cart is currently empty.

Research Hypothesis In Psychology: Types, & Examples

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

A research hypothesis, in its plural form “hypotheses,” is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method .

Hypotheses connect theory to data and guide the research process towards expanding scientific understanding

Some key points about hypotheses:

• A hypothesis expresses an expected pattern or relationship. It connects the variables under investigation.
• It is stated in clear, precise terms before any data collection or analysis occurs. This makes the hypothesis testable.
• A hypothesis must be falsifiable. It should be possible, even if unlikely in practice, to collect data that disconfirms rather than supports the hypothesis.
• Hypotheses guide research. Scientists design studies to explicitly evaluate hypotheses about how nature works.
• For a hypothesis to be valid, it must be testable against empirical evidence. The evidence can then confirm or disprove the testable predictions.
• Hypotheses are informed by background knowledge and observation, but go beyond what is already known to propose an explanation of how or why something occurs.

Predictions typically arise from a thorough knowledge of the research literature, curiosity about real-world problems or implications, and integrating this to advance theory. They build on existing literature while providing new insight.

Types of Research Hypotheses

Alternative hypothesis.

The research hypothesis is often called the alternative or experimental hypothesis in experimental research.

It typically suggests a potential relationship between two key variables: the independent variable, which the researcher manipulates, and the dependent variable, which is measured based on those changes.

The alternative hypothesis states a relationship exists between the two variables being studied (one variable affects the other).

A hypothesis is a testable statement or prediction about the relationship between two or more variables. It is a key component of the scientific method. Some key points about hypotheses:

• Important hypotheses lead to predictions that can be tested empirically. The evidence can then confirm or disprove the testable predictions.

In summary, a hypothesis is a precise, testable statement of what researchers expect to happen in a study and why. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.

An experimental hypothesis predicts what change(s) will occur in the dependent variable when the independent variable is manipulated.

It states that the results are not due to chance and are significant in supporting the theory being investigated.

The alternative hypothesis can be directional, indicating a specific direction of the effect, or non-directional, suggesting a difference without specifying its nature. It’s what researchers aim to support or demonstrate through their study.

Null Hypothesis

The null hypothesis states no relationship exists between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to manipulating the independent variable.

It states results are due to chance and are not significant in supporting the idea being investigated.

The null hypothesis, positing no effect or relationship, is a foundational contrast to the research hypothesis in scientific inquiry. It establishes a baseline for statistical testing, promoting objectivity by initiating research from a neutral stance.

Many statistical methods are tailored to test the null hypothesis, determining the likelihood of observed results if no true effect exists.

This dual-hypothesis approach provides clarity, ensuring that research intentions are explicit, and fosters consistency across scientific studies, enhancing the standardization and interpretability of research outcomes.

Nondirectional Hypothesis

A non-directional hypothesis, also known as a two-tailed hypothesis, predicts that there is a difference or relationship between two variables but does not specify the direction of this relationship.

It merely indicates that a change or effect will occur without predicting which group will have higher or lower values.

For example, “There is a difference in performance between Group A and Group B” is a non-directional hypothesis.

Directional Hypothesis

A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e., greater, smaller, less, more)

It specifies whether one variable is greater, lesser, or different from another, rather than just indicating that there’s a difference without specifying its nature.

For example, “Exercise increases weight loss” is a directional hypothesis.

Falsifiability

The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory or hypothesis to be considered scientific, it must be testable and irrefutable.

Falsifiability emphasizes that scientific claims shouldn’t just be confirmable but should also have the potential to be proven wrong.

It means that there should exist some potential evidence or experiment that could prove the proposition false.

However many confirming instances exist for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.

For Popper, science should attempt to disprove a theory rather than attempt to continually provide evidence to support a research hypothesis.

Can a Hypothesis be Proven?

Hypotheses make probabilistic predictions. They state the expected outcome if a particular relationship exists. However, a study result supporting a hypothesis does not definitively prove it is true.

All studies have limitations. There may be unknown confounding factors or issues that limit the certainty of conclusions. Additional studies may yield different results.

In science, hypotheses can realistically only be supported with some degree of confidence, not proven. The process of science is to incrementally accumulate evidence for and against hypothesized relationships in an ongoing pursuit of better models and explanations that best fit the empirical data. But hypotheses remain open to revision and rejection if that is where the evidence leads.

• Disproving a hypothesis is definitive. Solid disconfirmatory evidence will falsify a hypothesis and require altering or discarding it based on the evidence.
• However, confirming evidence is always open to revision. Other explanations may account for the same results, and additional or contradictory evidence may emerge over time.

We can never 100% prove the alternative hypothesis. Instead, we see if we can disprove, or reject the null hypothesis.

If we reject the null hypothesis, this doesn’t mean that our alternative hypothesis is correct but does support the alternative/experimental hypothesis.

Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.

How to Write a Hypothesis

• Identify variables . The researcher manipulates the independent variable and the dependent variable is the measured outcome.
• Operationalized the variables being investigated . Operationalization of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression, you might count the number of punches given by participants.
• Decide on a direction for your prediction . If there is evidence in the literature to support a specific effect of the independent variable on the dependent variable, write a directional (one-tailed) hypothesis. If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
• Make it Testable : Ensure your hypothesis can be tested through experimentation or observation. It should be possible to prove it false (principle of falsifiability).
• Clear & concise language . A strong hypothesis is concise (typically one to two sentences long), and formulated using clear and straightforward language, ensuring it’s easily understood and testable.

Consider a hypothesis many teachers might subscribe to: students work better on Monday morning than on Friday afternoon (IV=Day, DV= Standard of work).

Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and a Friday afternoon and then measuring their immediate recall of the material covered in each session, we would end up with the following:

• The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
• The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.

More Examples

• Memory : Participants exposed to classical music during study sessions will recall more items from a list than those who studied in silence.
• Social Psychology : Individuals who frequently engage in social media use will report higher levels of perceived social isolation compared to those who use it infrequently.
• Developmental Psychology : Children who engage in regular imaginative play have better problem-solving skills than those who don’t.
• Clinical Psychology : Cognitive-behavioral therapy will be more effective in reducing symptoms of anxiety over a 6-month period compared to traditional talk therapy.
• Cognitive Psychology : Individuals who multitask between various electronic devices will have shorter attention spans on focused tasks than those who single-task.
• Health Psychology : Patients who practice mindfulness meditation will experience lower levels of chronic pain compared to those who don’t meditate.
• Organizational Psychology : Employees in open-plan offices will report higher levels of stress than those in private offices.
• Behavioral Psychology : Rats rewarded with food after pressing a lever will press it more frequently than rats who receive no reward.

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 21 October 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.