How to Write a Hypothesis: A Guide

If you are doing research, developing a hypothesis is one of the most challenging elements. However, it is also the most essential since the experiments you conduct are built entirely around the research hypothesis (H1) and null hypothesis (H0). Any mistake could leave the entire project invalid. 

It goes without saying that if you do not know how to write a hypothesis properly, things can get very overwhelming. But have no fear. While a lot of students consider this to be the most challenging stage of the scientific method, you do not have to struggle if you follow the suggestions in this article. It is all just a matter of thinking up the right questions and properly writing your hypothesis statements. Once you master this, the process becomes so much easier! 


Develop a Hypothesis in Easy Steps

After undertaking all of that research and study, isolating a testable hypothesis can be a hard thing to do. The most effective strategy is to utilize a three-step hypothesis. This will help you to pare things down and is the strategy that seasoned researchers employ.

The first step is to come up with a broad hypothesis based on whatever it is you discovered and examined as you were collecting information during the research design phase. This is the point where you develop the research program.

A Hypothesis Example

A student notices that when he gets at least 9 hours of sleep, he scores 10% better on his tests than if he gets 8 hours. His research leads him to believe that the more sleep he gets, the better he is at answering exam questions. He proposes a general hypothesis.

“The number of sleeping hours affects test performance.”

This sounds okay, but it does nothing to provide guidance as it relates to designing the research. It is necessary to refine the hypothesis in order to provide more direction. This is a good hypothesis, however; it does not give any guide on how to design the experiment. The hypothesis must be refined to give a little direction.

“Test results will improve if a student sleeps longer.”

This provides the research with better direction, but it is still too general. Therefore, it needs to be worked on further in order to be tested.

“A student performs better on tests with 9 hours of sleep versus 8 because it leaves him/her feeling more refreshed.”

This is a hypothesis that can be tested because it includes variables that can be measured – the amount of sleep, while eliminating other controlled variables, such as the difficulty of the test. The student would be able to determine whether there is a correlation between additional sleep and test scores. By looking deeper into a question, you will be able to understand how to write a hypothesis effectively.

Why a Hypothesis Needs to Be Testable

It goes without saying that you cannot perform an experience according to the proper scientific method if you cannot test the hypothesis. For it to be testable, the following must be true:

  1. It must be possible to prove that the hypothesis is true.
  2. It must be possible to prove that the hypothesis is false.
  3. Other researchers should manage to reproduce the results.

In the absence of these criteria, the hypothesis and results will lack clarity. Therefore, the experiment itself will be meaningless. 

How to Create a Good Hypothesis

When it comes to creating the hypothesis, it cannot just be any kind of statement. It has to be clear and carefully designed so that the reader understands the experiment, its purpose and what could happen. As you think up a good hypothesis, make sure to do the following:

  • State the problem that you are investigating. The hypothesis should make clear the purpose of the experience and it should inform the reader about the topic.
  • Approach the hypothesis as an if…then. Imagine it this way: If one thing takes place, then this is what could happen.
  • Identify the variables. In scientific experiments, the purpose of the hypothesis is to explore the relationship between the dependent and independent variables. The impact on the dependent variable depends on what happens when the independent variable is changed. 

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For instance, consider this hypothesis:

More cups of coffee (independent variable) leads to higher blood pressure (dependent variable). If you change the independent variable (drinking more coffee), it will change the dependent variable (the blood pressure level).

It is impossible to discount how important the above steps are. Whether your experiment and its results are valid depends on a hypothesis that can be tested. If you come up with a strong hypothesis that is easy to test, it allows the researcher to truly appreciate the implications and to predict findings in an accurate way based on previous research. 

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Questions to Consider

As you think about how to write a hypothesis, you should determine whether it is truly testable. In order to achieve this, you should ask yourself the following questions: 

  1. Is the word usage focused easy to understand?
  2. Does the hypothesis give the reader a clear idea about the research topic?
  3. Does the hypothesis include both dependent and an independent variable? Are they clearly identified?
  4. Is it possible to test the hypothesis through experimentation?
  5. Does the hypothesis discuss what you anticipate will happen?

Use these questions to make a checklist. It is an effective way to find out any issues/weaknesses in your hypothesis and gives you a chance to make appropriate changes. As you go about developing a hypothesis, how do you feel about the process? What were some of the difficulties? What steps do you think you can take to make the process easier? Pondering these questions will make it easier for you to develop hypotheses in future research work.

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Final Stage – How to Use the Hypothesis

Now that you have a hypothesis, you can proceed to designing the experiment, analyzing the statistical data, and giving you a chance to test this hypothesis.  Through statistical analysis, you can now reject either (H1) or (H0). If you end up rejecting your research hypothesis, it does not mean the experiment was a total failure. Instead, you should seek to determine why the results ended up being what they were, and go back and design a better research experiment idea.

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