How to Write a Hypothesis

This fundamental statement/formula should be familiar to you because it is the starting point for almost every scientific project or paper. It’s a hypothesis – a statement that describes what you “believe” will happen during an experiment. This assumption is based on what you already know, facts, and data.

How should a hypothesis be written? If you understand the proper structure, you should not have too much trouble creating one. However, you may find it difficult if you’ve never written a hypothesis before. This article will teach you everything you need to know about hypotheses, their different types, and practical writing tips.


Hypothesis Definition

According to the definition, a hypothesis is an assumption based on prior knowledge. More specifically, it is a statement that translates the initial research question into a logical prediction based on the facts and evidence available. To solve a specific problem, one must first identify the research problem (research question), conduct preliminary research, and then answer the given question by conducting experiments and observing the results. However, before moving on to the experimental part of the research, one must first determine what they expect to see in terms of results. At this point, a scientist makes an educated guess and writes a hypothesis, which they will prove or refute during their research.

A hypothesis can also be viewed as a form of knowledge development. A well-founded assumption is advanced to clarify the properties and causes of the phenomena under investigation.

A hypothesis is typically formed based on several observations and examples that confirm it. This way, it appears plausible because some general information supports it. The hypothesis is then proven or refuted (for instance, by pointing out a counterexample), allowing it to fall into the category of false statements.

As a student, you may be required to write a hypothesis statement as part of an academic paper. Hypothesis-based approaches are commonly used in scientific literary works such as research papers, theses, and dissertations.

It’s worth noting that a hypothesis statement is referred to as a thesis statement in some fields. However, its essence and purpose remain the same – this statement aims to assume the investigation’s outcomes that will either be proven or refuted.


Characteristics and Sources of a Hypothesis

Now that you understand what a hypothesis is in a nutshell, let’s take a look at the key characteristics that define it:

  • It must be clear and accurate to appear trustworthy.
  • It must be precise.
  • There should be room for additional research and experiments.
  • A hypothesis should be explained in simple terms while maintaining its importance.
  • Variables and their relationship are two essential elements to include when developing a relational hypothesis.

The following are the primary sources of a hypothesis:

  • Scientific hypotheses.
  • Observations gleaned from previous research and current experiences
  • The similarity of various phenomena.
  • Patterns that affect people’s thinking processes in general.


Types of Hypothesis

There are two types of scientific hypotheses: alternative and null.


Alternative Hypothesis

This type of hypothesis is commonly referred to as H1. This statement identifies the anticipated outcome of your research. This type of hypothesis, according to the alternative hypothesis definition, can be further subdivided into two subcategories:

  • Directional — a statement that explains the expected outcome’s direction. This hypothesis is sometimes used to investigate the relationship between variables rather than comparing groups.
  • Non-directional — Unlike alternative directional hypotheses, non-directional hypotheses do not imply a specific direction of expected outcomes.


Null Hypothesis

This type of hypothesis is commonly referred to as H0. This statement is the polar opposite of what you expect or predict will occur during your research—that is, it is the polar opposite of your alternative hypothesis. Simply put, a null hypothesis asserts that no exact or actual correlation exists between the variables specified in the hypothesis.


Associative and Causal Hypothesis — An associative hypothesis is a statement that indicates the correlation between variables in the scenario where a change in one variable changes the other variable. A causal hypothesis is a statement that emphasizes the relationship between variables’ causes and effects.


Hypothesis vs. Prediction

Another term that comes to mind when discussing hypotheses is prediction. These two terms are frequently used interchangeably, which can be perplexing. Although both a hypothesis and a prediction are commonly defined as “guesses” and can be easily confused, they are not the same thing. The primary distinction between a hypothesis and a prediction is that the former is more commonly used in science, whereas the latter is more widely used outside of science.

Simply put, a hypothesis is a well-thought-out assumption. It is a guess about the nature of an unknown (or less known) phenomenon based on existing knowledge, studies, and a series of experiments otherwise supported by valid facts. A hypothesis’ primary purpose is to use available points to create a logical relationship between variables to provide a more precise scientific explanation. Furthermore, hypotheses are statements that can be tested with additional experiments. It is a presumption you make about your research study’s direction and outcome(s).

On the other hand, a prediction is a wild guess that frequently lacks foundation. Although a prediction can be scientific in theory, it is more often than not fictitious—a rough guess based on current knowledge and facts. Predictions are typically associated with foretelling events that may or may not occur in the future. A person who makes predictions frequently has little or no actual knowledge of the subject matter about which they make the assumption.

Another significant distinction between these terms is the methodology used to prove each. A prediction can be confirmed only once. Only the occurrence or non-occurrence of the predicted event can determine whether it is correct or incorrect. On the other hand, a hypothesis allows for additional testing and experiments. Furthermore, a hypothesis can be proven in stages. This means that a single hypothesis can be proven or refuted multiple times by different scientists using various scientific tools and methods.


The following key takeaways stand out:

  • As opposed to a prediction, a hypothesis is a more informed assumption based on facts.
  • Existing variables are defined by hypotheses, which analyze the relationship(s).
  • Predictions are frequently fictitious and lack foundation.
  • A prediction is most commonly used to forecast future events.
  • A prediction can only be proven once – when the predicted event happens or does not happen.
  • Even if one scientist has already proven or disproven a hypothesis, it can still be considered. Other scientists may achieve different results by employing different methods and tools.


How to Write a Hypothesis

You’re probably wondering how to state a hypothesis now that you’ve learned what it is, what types of hypotheses exist, and how it differs from a prediction. In this section, we will walk you through the main stages of developing a reasonable hypothesis, as well as provide helpful tips and examples to help you overcome this challenge:


Establish Your Research Question

Here’s one thing to remember: no matter what paper or project you’re working on, the process should always begin with asking the right research question. A perfect research question is specific, clear, focused (not too broad), and manageable.


Conduct Your Initial Basic Research

As you may know, a hypothesis is an educated guess of the expected results and outcomes of an investigation. As a result, it is critical to gather some information before making this assumption.

Based on what has already been discovered, you should be able to answer your research question at this point. Look for facts, previous studies, theories, and so on. You should be able to make a logical and intelligent guess based on your information.


Create a Hypothesis

Based on your preliminary research, you should have a good idea of what you might discover during your investigation. Make use of this knowledge to develop a clear and concise hypothesis.

You can restate your hypothesis in various ways depending on the type of project you’re working on and the type of hypothesis you intend to use.


Improve Your Hypothesis

Finally, the final step in developing a reasonable hypothesis is to refine what you’ve got. During this stage, you must determine whether your hypothesis:

  • Has distinct and pertinent variables;
  • identifies the relationship between its variables;
  • Is particular and testable;
  • Suggest a possible outcome of the investigation or experiment.


Hypothesis Examples

You should be able to create reasonable hypotheses with ease if you follow a step-by-step guide and the tips in this article. To help you get started, we’ve compiled a list of different research questions, each with one hypothesis and one null hypothesis example:


Research Question: How does stress affect undergraduate students’ academic performance?

Hypothesis: Undergraduate students’ academic performance will suffer as their stress levels rise.

Null Hypothesis: Stress levels among undergraduate students will not rise, which will have no effect on academic performance.


Research Question: How does frequent use of social media affect users under the age of 16’s attention span?

Hypothesis: The frequency of social media use and the attention span of users under the age of 16 have a negative relationship.

Null Hypothesis: There is no relationship between the amount of time spent on social media and the attention span of users under the age of 16.


Research Question: How does improved work-life balance affect employee productivity at work?

Hypothesis: Employees who have a better work-life balance will be more productive than those who do not have an excellent work-life balance.

Null Hypothesis: There is no link between work-life balance and workplace productivity.