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• 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 .

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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

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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.

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Research Methodology for Allied Health Professionals pp 19–22 Cite as

Formulating Research Hypothesis and Objective

• Animesh Hazari 2  
• First Online: 01 March 2024

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Formulating a research hypothesis and objectives is the first and foremost step in any research process as they provide a clear direction and purpose for your study. In this chapter, we shall learn about formulating an ideal research hypothesis and objectives. Formulation and development of the hypothesis and objectives take place under the following key steps:

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Hazari, A. (2023). Formulating Research Hypothesis and Objective. In: Research Methodology for Allied Health Professionals. Springer, Singapore. https://doi.org/10.1007/978-981-99-8925-6_4

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TESTING HYPOTHESIS IN RESEARCH

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Formulating Hypotheses - PowerPoint PPT Presentation

Formulating Hypotheses

An hypothesis is really a temporary explanation, a kind of educated guess about ... he or she predicts that carbon dioxide can be detected as an organism digests food. ... – powerpoint ppt presentation.

• Science advances by formulating and testing hypotheses. An hypothesis is really a temporary explanation, a kind of educated guess about what will happen under certain conditions.
• A hypothesis usually begins as an answer to a question.
• Question Do plants need light to grow?
• Ex. If green plants need light to grow, then only plants kept in light will display growth.
• Most times it is an If then statement.
• But ALWAYS is a statement that has a definitive answer, or one that can be answered yes or no.
• Do living things give off CO2 when they digest food?
• A scientist thinks that living things give off carbon dioxide gas as they break down food. He or she predicts that carbon dioxide can be detected as an organism digests food.
• Some students were investigating what made their classmates get colds. One student believed that those who took vitamin C every day got fewer colds than the rest of the students.
• Another student was interested in raising tropical fish. She believed that fish that were given Phillip Chons Formula 1 food would produce more offspring than those fed Kaitlyn Gortners Golden Flakes.
• You can prove them to be untrue, but you cannot prove them to be true.
• This means you can only support your hypothesis.
• The more a hypothesis is supported, the greater its power to explain the phenomenon.
• Bacteria are microscopic creatures found almost everywhere. They are useful to biologists in many different kinds of experiments. For each of the following problems involving bacteria, form an hypothesis to make a prediction.
• Does the temperature at which bacteria are grown affect their rate of reproduction?
• Does using up the nutrients they are feeding on affect the rate of reproduction of bacteria?
• Some bacteria require certain vitamins in the material in which they are grown. Does bacterium X require vitamin B12 for reproduction?
• Does aspirin inhibit the reproduction of bacteria?
• The questions and hypotheses you develop must be typed.
• I do not accept hand-written hypotheses.
• STD LAB set up follows.
• Tomorrow we will be mating with each other. You will have five partners that you will share bodily fluids with (one at a time). One individual in class will be contaminated with an STD at the start of the experiment.
• What question(s) could be asked about the spread of the disease in class? Choose one question to answer. Next, write a testable hypothesis that predicts the results (a best guess answer to the question).
• Your hypothesis must be signed off by me before you can begin the lab.

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Formulating the Hypothesis

Jun 28, 2013

1.16k likes | 4.01k Views

Formulating the Hypothesis. The null hypothesis is a statement about the population value that will be tested. The null hypothesis will be rejected only if the sample data provide substantial contradictory evidence. Formulating the Hypothesis.

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• decision rule figure
• critical value
• tailed hypothesis tests
• maximum probability
• test statistic

Presentation Transcript

Formulating the Hypothesis The null hypothesis is a statement about the population value that will be tested. The null hypothesis will be rejected only if the sample data provide substantial contradictory evidence.

Formulating the Hypothesis The alternativehypothesis is the hypothesis that includes all population values not covered by the null hypothesis. The alternative hypothesis is deemed to be true if the null hypothesis is rejected.

Formulating the Hypothesis The research hypothesis (usually the alternativehypothesis): Decision maker attempts to demonstrate it to be true. Deemed to be the most important to the decision maker. Not declared true unless the sample data strongly indicates that it is true.

Types of Statistical Errors • Type I Error - This type of statistical error occurs when the null hypothesis is true and is rejected. • Type II Error - This type of statistical error occurs when the null hypothesis is false and is not rejected.

Types of Statistical Errors

Establishing the Decision Rule The critical value is Determined by the significance level. The cutoff value for a test statistic that leads to either rejecting or not rejecting the null hypothesis.

Establishing the Decision Rule The significance level is the maximum probability of committing a Type I statistical error. The probability is denoted by the symbol .

Establishing the Decision Rule(Figure 8-3) Sampling Distribution Maximum probability of committing a Type I error =  Do not reject H0 Reject H0

Establishing the Critical Value as a z -Value From the standard normal table Then Rejection region  = 0.10 0.5 0.4 0

Establishing the Decision Rule The test statistic is a function of the sampled observations that provides a basis for testing a statistical hypothesis.

Test Statistic in the Rejection Region Rejection region  = 0.10 0.5 0.4 0

Establishing the Decision Rule The p-value is The probability of obtaining a test statistic at least as extreme as the test statistic we calculated from the sample. Also known as the observed significance level.

Relationship Between the p-Value and the Rejection Region Rejection region  = 0.10 p-value = 0.0036 0.5 0.4 0

Using the p-Value to Conduct the Hypothesis Test • If the p-value is less than or equal to a, reject the null hypothesis. • If the p-value is greater than a, do not reject the null hypothesis. Example: For a = 0.05 with the p-value = 0.02 for a particular test, then the null hypothesis is rejected.

One-Tailed Hypothesis Tests A one-tailed hypothesis test is a test in which the entire rejection region is located in one tail of the test statistic’s distribution.

Two-Tailed Hypothesis Tests A two-tailed hypothesis test is a test in which the rejection region is split between the two tails of the test statistic’s distribution.

Two-Tailed Hypothesis Tests (Figure 8-7) 0

When s Is Unknown • The sample standard deviation is used. • The test statistic is calculated as • The critical value is found from the t-table (Appendix F) using n-1 degrees of freedom.

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