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Think about something strange and unexplainable in your life. Maybe you get a headache right before it rains, or maybe you think your favorite sports team wins when you wear a certain color. If you wanted to see whether these are just coincidences or scientific fact, you would form a hypothesis, then create an experiment to see whether that hypothesis is true or not.

But what is a hypothesis, anyway? If you’re not sure about what a hypothesis is--or how to test for one!--you’re in the right place. This article will teach you everything you need to know about hypotheses, including: 

  • Defining the term “hypothesis” 
  • Providing hypothesis examples 
  • Giving you tips for how to write your own hypothesis

So let’s get started!

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What Is a Hypothesis?

Merriam Webster defines a hypothesis as “an assumption or concession made for the sake of argument.” In other words, a hypothesis is an educated guess . Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it’s true or not. Keep in mind that in science, a hypothesis should be testable. You have to be able to design an experiment that tests your hypothesis in order for it to be valid. 

As you could assume from that statement, it’s easy to make a bad hypothesis. But when you’re holding an experiment, it’s even more important that your guesses be good...after all, you’re spending time (and maybe money!) to figure out more about your observation. That’s why we refer to a hypothesis as an educated guess--good hypotheses are based on existing data and research to make them as sound as possible.

Hypotheses are one part of what’s called the scientific method .  Every (good) experiment or study is based in the scientific method. The scientific method gives order and structure to experiments and ensures that interference from scientists or outside influences does not skew the results. It’s important that you understand the concepts of the scientific method before holding your own experiment. Though it may vary among scientists, the scientific method is generally made up of six steps (in order):

  • Observation
  • Asking questions
  • Forming a hypothesis
  • Analyze the data
  • Communicate your results

You’ll notice that the hypothesis comes pretty early on when conducting an experiment. That’s because experiments work best when they’re trying to answer one specific question. And you can’t conduct an experiment until you know what you’re trying to prove!

Independent and Dependent Variables 

After doing your research, you’re ready for another important step in forming your hypothesis: identifying variables. Variables are basically any factor that could influence the outcome of your experiment . Variables have to be measurable and related to the topic being studied.

There are two types of variables:  independent variables and dependent variables. I ndependent variables remain constant . For example, age is an independent variable; it will stay the same, and researchers can look at different ages to see if it has an effect on the dependent variable. 

Speaking of dependent variables... dependent variables are subject to the influence of the independent variable , meaning that they are not constant. Let’s say you want to test whether a person’s age affects how much sleep they need. In that case, the independent variable is age (like we mentioned above), and the dependent variable is how much sleep a person gets. 

Variables will be crucial in writing your hypothesis. You need to be able to identify which variable is which, as both the independent and dependent variables will be written into your hypothesis. For instance, in a study about exercise, the independent variable might be the speed at which the respondents walk for thirty minutes, and the dependent variable would be their heart rate. In your study and in your hypothesis, you’re trying to understand the relationship between the two variables.

Elements of a Good Hypothesis

The best hypotheses start by asking the right questions . For instance, if you’ve observed that the grass is greener when it rains twice a week, you could ask what kind of grass it is, what elevation it’s at, and if the grass across the street responds to rain in the same way. Any of these questions could become the backbone of experiments to test why the grass gets greener when it rains fairly frequently.

As you’re asking more questions about your first observation, make sure you’re also making more observations . If it doesn’t rain for two weeks and the grass still looks green, that’s an important observation that could influence your hypothesis. You'll continue observing all throughout your experiment, but until the hypothesis is finalized, every observation should be noted.

Finally, you should consult secondary research before writing your hypothesis . Secondary research is comprised of results found and published by other people. You can usually find this information online or at your library. Additionally, m ake sure the research you find is credible and related to your topic. If you’re studying the correlation between rain and grass growth, it would help you to research rain patterns over the past twenty years for your county, published by a local agricultural association. You should also research the types of grass common in your area, the type of grass in your lawn, and whether anyone else has conducted experiments about your hypothesis. Also be sure you’re checking the quality of your research . Research done by a middle school student about what minerals can be found in rainwater would be less useful than an article published by a local university.

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Writing Your Hypothesis

Once you’ve considered all of the factors above, you’re ready to start writing your hypothesis. Hypotheses usually take a certain form when they’re written out in a research report.

When you boil down your hypothesis statement, you are writing down your best guess and not the question at hand . This means that your statement should be written as if it is fact already, even though you are simply testing it.

The reason for this is that, after you have completed your study, you'll either accept or reject your if-then or your null hypothesis. All hypothesis testing examples should be measurable and able to be confirmed or denied. You cannot confirm a question, only a statement! 

In fact, you come up with hypothesis examples all the time! For instance, when you guess on the outcome of a basketball game, you don’t say, “Will the Miami Heat beat the Boston Celtics?” but instead, “I think the Miami Heat will beat the Boston Celtics.” You state it as if it is already true, even if it turns out you’re wrong. You do the same thing when writing your hypothesis.

Additionally, keep in mind that hypotheses can range from very specific to very broad.  These hypotheses can be specific, but if your hypothesis testing examples involve a broad range of causes and effects, your hypothesis can also be broad.  

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The Two Types of Hypotheses

Now that you understand what goes into a hypothesis, it’s time to look more closely at the two most common types of hypothesis: the if-then hypothesis and the null hypothesis.

#1: If-Then Hypotheses

First of all, if-then hypotheses typically follow this formula:

If ____ happens, then ____ will happen.

The goal of this type of hypothesis is to test the causal relationship between the independent and dependent variable. It’s fairly simple, and each hypothesis can vary in how detailed it can be. We create if-then hypotheses all the time with our daily predictions. Here are some examples of hypotheses that use an if-then structure from daily life: 

  • If I get enough sleep, I’ll be able to get more work done tomorrow.
  • If the bus is on time, I can make it to my friend’s birthday party. 
  • If I study every night this week, I’ll get a better grade on my exam. 

In each of these situations, you’re making a guess on how an independent variable (sleep, time, or studying) will affect a dependent variable (the amount of work you can do, making it to a party on time, or getting better grades). 

You may still be asking, “What is an example of a hypothesis used in scientific research?” Take one of the hypothesis examples from a real-world study on whether using technology before bed affects children’s sleep patterns. The hypothesis read s:

“We hypothesized that increased hours of tablet- and phone-based screen time at bedtime would be inversely correlated with sleep quality and child attention.”

It might not look like it, but this is an if-then statement. The researchers basically said, “If children have more screen usage at bedtime, then their quality of sleep and attention will be worse.” The sleep quality and attention are the dependent variables and the screen usage is the independent variable. (Usually, the independent variable comes after the “if” and the dependent variable comes after the “then,” as it is the independent variable that affects the dependent variable.) This is an excellent example of how flexible hypothesis statements can be, as long as the general idea of “if-then” and the independent and dependent variables are present.

#2: Null Hypotheses

Your if-then hypothesis is not the only one needed to complete a successful experiment, however. You also need a null hypothesis to test it against. In its most basic form, the null hypothesis is the opposite of your if-then hypothesis . When you write your null hypothesis, you are writing a hypothesis that suggests that your guess is not true, and that the independent and dependent variables have no relationship .

One null hypothesis for the cell phone and sleep study from the last section might say: 

“If children have more screen usage at bedtime, their quality of sleep and attention will not be worse.” 

In this case, this is a null hypothesis because it’s asking the opposite of the original thesis! 

Conversely, if your if-then hypothesis suggests that your two variables have no relationship, then your null hypothesis would suggest that there is one. So, pretend that there is a study that is asking the question, “Does the amount of followers on Instagram influence how long people spend on the app?” The independent variable is the amount of followers, and the dependent variable is the time spent. But if you, as the researcher, don’t think there is a relationship between the number of followers and time spent, you might write an if-then hypothesis that reads:

“If people have many followers on Instagram, they will not spend more time on the app than people who have less.”

In this case, the if-then suggests there isn’t a relationship between the variables. In that case, one of the null hypothesis examples might say:

“If people have many followers on Instagram, they will spend more time on the app than people who have less.”

You then test both the if-then and the null hypothesis to gauge if there is a relationship between the variables, and if so, how much of a relationship. 

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4 Tips to Write the Best Hypothesis

If you’re going to take the time to hold an experiment, whether in school or by yourself, you’re also going to want to take the time to make sure your hypothesis is a good one. The best hypotheses have four major elements in common: plausibility, defined concepts, observability, and general explanation.

#1: Plausibility

At first glance, this quality of a hypothesis might seem obvious. When your hypothesis is plausible, that means it’s possible given what we know about science and general common sense. However, improbable hypotheses are more common than you might think. 

Imagine you’re studying weight gain and television watching habits. If you hypothesize that people who watch more than  twenty hours of television a week will gain two hundred pounds or more over the course of a year, this might be improbable (though it’s potentially possible). Consequently, c ommon sense can tell us the results of the study before the study even begins.

Improbable hypotheses generally go against  science, as well. Take this hypothesis example: 

“If a person smokes one cigarette a day, then they will have lungs just as healthy as the average person’s.” 

This hypothesis is obviously untrue, as studies have shown again and again that cigarettes negatively affect lung health. You must be careful that your hypotheses do not reflect your own personal opinion more than they do scientifically-supported findings. This plausibility points to the necessity of research before the hypothesis is written to make sure that your hypothesis has not already been disproven.

#2: Defined Concepts

The more advanced you are in your studies, the more likely that the terms you’re using in your hypothesis are specific to a limited set of knowledge. One of the hypothesis testing examples might include the readability of printed text in newspapers, where you might use words like “kerning” and “x-height.” Unless your readers have a background in graphic design, it’s likely that they won’t know what you mean by these terms. Thus, it’s important to either write what they mean in the hypothesis itself or in the report before the hypothesis.

Here’s what we mean. Which of the following sentences makes more sense to the common person?

If the kerning is greater than average, more words will be read per minute.

If the space between letters is greater than average, more words will be read per minute.

For people reading your report that are not experts in typography, simply adding a few more words will be helpful in clarifying exactly what the experiment is all about. It’s always a good idea to make your research and findings as accessible as possible. 

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Good hypotheses ensure that you can observe the results. 

#3: Observability

In order to measure the truth or falsity of your hypothesis, you must be able to see your variables and the way they interact. For instance, if your hypothesis is that the flight patterns of satellites affect the strength of certain television signals, yet you don’t have a telescope to view the satellites or a television to monitor the signal strength, you cannot properly observe your hypothesis and thus cannot continue your study.

Some variables may seem easy to observe, but if you do not have a system of measurement in place, you cannot observe your hypothesis properly. Here’s an example: if you’re experimenting on the effect of healthy food on overall happiness, but you don’t have a way to monitor and measure what “overall happiness” means, your results will not reflect the truth. Monitoring how often someone smiles for a whole day is not reasonably observable, but having the participants state how happy they feel on a scale of one to ten is more observable. 

In writing your hypothesis, always keep in mind how you'll execute the experiment.

#4: Generalizability 

Perhaps you’d like to study what color your best friend wears the most often by observing and documenting the colors she wears each day of the week. This might be fun information for her and you to know, but beyond you two, there aren’t many people who could benefit from this experiment. When you start an experiment, you should note how generalizable your findings may be if they are confirmed. Generalizability is basically how common a particular phenomenon is to other people’s everyday life.

Let’s say you’re asking a question about the health benefits of eating an apple for one day only, you need to realize that the experiment may be too specific to be helpful. It does not help to explain a phenomenon that many people experience. If you find yourself with too specific of a hypothesis, go back to asking the big question: what is it that you want to know, and what do you think will happen between your two variables?

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Hypothesis Testing Examples

We know it can be hard to write a good hypothesis unless you’ve seen some good hypothesis examples. We’ve included four hypothesis examples based on some made-up experiments. Use these as templates or launch pads for coming up with your own hypotheses.

Experiment #1: Students Studying Outside (Writing a Hypothesis)

You are a student at PrepScholar University. When you walk around campus, you notice that, when the temperature is above 60 degrees, more students study in the quad. You want to know when your fellow students are more likely to study outside. With this information, how do you make the best hypothesis possible?

You must remember to make additional observations and do secondary research before writing your hypothesis. In doing so, you notice that no one studies outside when it’s 75 degrees and raining, so this should be included in your experiment. Also, studies done on the topic beforehand suggested that students are more likely to study in temperatures less than 85 degrees. With this in mind, you feel confident that you can identify your variables and write your hypotheses:

If-then: “If the temperature in Fahrenheit is less than 60 degrees, significantly fewer students will study outside.”

Null: “If the temperature in Fahrenheit is less than 60 degrees, the same number of students will study outside as when it is more than 60 degrees.”

These hypotheses are plausible, as the temperatures are reasonably within the bounds of what is possible. The number of people in the quad is also easily observable. It is also not a phenomenon specific to only one person or at one time, but instead can explain a phenomenon for a broader group of people.

To complete this experiment, you pick the month of October to observe the quad. Every day (except on the days where it’s raining)from 3 to 4 PM, when most classes have released for the day, you observe how many people are on the quad. You measure how many people come  and how many leave. You also write down the temperature on the hour. 

After writing down all of your observations and putting them on a graph, you find that the most students study on the quad when it is 70 degrees outside, and that the number of students drops a lot once the temperature reaches 60 degrees or below. In this case, your research report would state that you accept or “failed to reject” your first hypothesis with your findings.

Experiment #2: The Cupcake Store (Forming a Simple Experiment)

Let’s say that you work at a bakery. You specialize in cupcakes, and you make only two colors of frosting: yellow and purple. You want to know what kind of customers are more likely to buy what kind of cupcake, so you set up an experiment. Your independent variable is the customer’s gender, and the dependent variable is the color of the frosting. What is an example of a hypothesis that might answer the question of this study?

Here’s what your hypotheses might look like: 

If-then: “If customers’ gender is female, then they will buy more yellow cupcakes than purple cupcakes.”

Null: “If customers’ gender is female, then they will be just as likely to buy purple cupcakes as yellow cupcakes.”

This is a pretty simple experiment! It passes the test of plausibility (there could easily be a difference), defined concepts (there’s nothing complicated about cupcakes!), observability (both color and gender can be easily observed), and general explanation ( this would potentially help you make better business decisions ).

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Experiment #3: Backyard Bird Feeders (Integrating Multiple Variables and Rejecting the If-Then Hypothesis)

While watching your backyard bird feeder, you realized that different birds come on the days when you change the types of seeds. You decide that you want to see more cardinals in your backyard, so you decide to see what type of food they like the best and set up an experiment. 

However, one morning, you notice that, while some cardinals are present, blue jays are eating out of your backyard feeder filled with millet. You decide that, of all of the other birds, you would like to see the blue jays the least. This means you'll have more than one variable in your hypothesis. Your new hypotheses might look like this: 

If-then: “If sunflower seeds are placed in the bird feeders, then more cardinals will come than blue jays. If millet is placed in the bird feeders, then more blue jays will come than cardinals.”

Null: “If either sunflower seeds or millet are placed in the bird, equal numbers of cardinals and blue jays will come.”

Through simple observation, you actually find that cardinals come as often as blue jays when sunflower seeds or millet is in the bird feeder. In this case, you would reject your “if-then” hypothesis and “fail to reject” your null hypothesis . You cannot accept your first hypothesis, because it’s clearly not true. Instead you found that there was actually no relation between your different variables. Consequently, you would need to run more experiments with different variables to see if the new variables impact the results.

Experiment #4: In-Class Survey (Including an Alternative Hypothesis)

You’re about to give a speech in one of your classes about the importance of paying attention. You want to take this opportunity to test a hypothesis you’ve had for a while: 

If-then: If students sit in the first two rows of the classroom, then they will listen better than students who do not.

Null: If students sit in the first two rows of the classroom, then they will not listen better or worse than students who do not.

You give your speech and then ask your teacher if you can hand out a short survey to the class. On the survey, you’ve included questions about some of the topics you talked about. When you get back the results, you’re surprised to see that not only do the students in the first two rows not pay better attention, but they also scored worse than students in other parts of the classroom! Here, both your if-then and your null hypotheses are not representative of your findings. What do you do?

This is when you reject both your if-then and null hypotheses and instead create an alternative hypothesis . This type of hypothesis is used in the rare circumstance that neither of your hypotheses is able to capture your findings . Now you can use what you’ve learned to draft new hypotheses and test again! 

Key Takeaways: Hypothesis Writing

The more comfortable you become with writing hypotheses, the better they will become. The structure of hypotheses is flexible and may need to be changed depending on what topic you are studying. The most important thing to remember is the purpose of your hypothesis and the difference between the if-then and the null . From there, in forming your hypothesis, you should constantly be asking questions, making observations, doing secondary research, and considering your variables. After you have written your hypothesis, be sure to edit it so that it is plausible, clearly defined, observable, and helpful in explaining a general phenomenon.

Writing a hypothesis is something that everyone, from elementary school children competing in a science fair to professional scientists in a lab, needs to know how to do. Hypotheses are vital in experiments and in properly executing the scientific method . When done correctly, hypotheses will set up your studies for success and help you to understand the world a little better, one experiment at a time.

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What’s Next?

If you’re studying for the science portion of the ACT, there’s definitely a lot you need to know. We’ve got the tools to help, though! Start by checking out our ultimate study guide for the ACT Science subject test. Once you read through that, be sure to download our recommended ACT Science practice tests , since they’re one of the most foolproof ways to improve your score. (And don’t forget to check out our expert guide book , too.)

If you love science and want to major in a scientific field, you should start preparing in high school . Here are the science classes you should take to set yourself up for success.

If you’re trying to think of science experiments you can do for class (or for a science fair!), here’s a list of 37 awesome science experiments you can do at home

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Ashley Sufflé Robinson has a Ph.D. in 19th Century English Literature. As a content writer for PrepScholar, Ashley is passionate about giving college-bound students the in-depth information they need to get into the school of their dreams.

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  • 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 .

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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 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.

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Published by Nicolas at January 16th, 2024 , Revised On January 23, 2024

How To Write A Hypotheses – Guide For Students

The word “hypothesis” might conjure up images of scientists in white coats, but crafting a solid hypothesis is a crucial skill for students in any field. Whether you are analyzing Shakespeare’s sonnets or conducting a science experiment, a well-defined research hypothesis sets the stage for your dissertation or thesis and fuels your investigation. 

Table of Contents

Writing a hypothesis is a crucial step in the research process. A hypothesis serves as the foundation of your research paper because it guides the direction of your study and provides a clear framework for investigation. But how to write a hypothesis? This blog will help you craft one. Let’s get started.

What Is A Hypothesis

A hypothesis is a clear and testable thesis statement or prediction that serves as the foundation of a research study. It is formulated based on existing knowledge, observations, and theoretical frameworks. 

A hypothesis articulates the researcher’s expectations regarding the relationship between variables in a study.

Hypothesis Example

Students exposed to multimedia-enhanced teaching methods will demonstrate higher retention of information compared to those taught using traditional methods.

The formulation of a hypothesis is crucial for guiding the research process and providing a clear direction for data collection and analysis. A well-crafted research hypothesis not only makes the research purpose explicit but also sets the stage for drawing meaningful conclusions from the study’s findings.

What Is A Null Hypothesis And Alternative Hypothesis

There are two main types of hypotheses: the null hypothesis (H0) and the alternative hypothesis (H1 or Ha). 

The null hypothesis posits that there is no significant effect or relationship, while the alternative hypothesis suggests the presence of a significant effect or relationship.

For example, in a study investigating the effect of a new drug on blood pressure, the null hypothesis might state that there is no difference in blood pressure between the control group (not receiving the drug) and the experimental group (receiving the drug). The alternative hypothesis, on the other hand, would propose that there is a significant difference in blood pressure between the two groups.

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How To Write A Good Research Hypothesis

Writing a hypothesis involves a systematic process that guides your research and provides a clear and testable statement about the expected relationship between variables. Go through the MLA vs. APA guidelines before writing. Here are the steps to help you how to write a hypothesis:

Step 1: Identify The Research Topic

Clearly define the research topic or question that you want to investigate. Ensure that your research question is specific and focused, providing a clear direction for your study.

Step 2: Conduct A Literature Review

Review existing literature related to your research topic. A thorough literature review helps you understand what is already known in the field, identify gaps, and build a foundation for formulating your hypothesis.

Step 3: Define Variables

Identify the variables involved in your study. The independent variable is the factor you manipulate, and the dependent variable is the one you measure. Clearly define the characteristics or conditions you are studying.

Step 4: Establish The Relationship

Determine the expected relationship between the independent and dependent variables. Will a change in the independent variable lead to a change in the dependent variable? Specify whether you anticipate a positive, negative, or no relationship.

Step 5: Formulate The Null Hypothesis (H0)

The null hypothesis represents the default position, suggesting that there is no significant effect or relationship between the variables you are studying. It serves as the baseline to be tested against. The null hypothesis is often denoted as H0.

Step 6: Formulate The Alternative Hypothesis (H1 or Ha)

The alternative hypothesis articulates the researcher’s expectation about the existence of a significant effect or relationship. It is what you aim to support with your research paper . The alternative hypothesis is denoted as H1 or Ha.

For example, if your research topic is about the effect of a new fertilizer on plant growth:

  • Null Hypothesis (H0): There is no significant difference in plant growth between plants treated with the traditional fertilizer and those treated with the new fertilizer.
  • Alternative Hypothesis (H1): There is a significant difference in plant growth between plants treated with the traditional fertilizer and those treated with the new fertilizer.

Step 7: Ensure Testability And Specificity

Confirm that your research hypothesis is testable and can be empirically investigated. Ensure that it is specific, providing a clear and measurable statement that can be validated or refuted through data collection and analysis.

Hypothesis Examples

What makes a good hypothesis.

  • Clear Statement: A hypothesis should be stated clearly and precisely. It should be easily understandable and convey the expected relationship between variables.
  • Testability: A hypothesis must be testable through empirical observation or experimentation. This means that there should be a feasible way to collect data and assess whether the expected relationship holds true.
  • Specificity: The research hypothesis should be specific in terms of the variables involved and the nature of the expected relationship. Vague or ambiguous hypotheses can lead to unclear research outcomes.
  • Measurability: Variables in a hypothesis should be measurable, meaning they can be quantified or observed objectively. This ensures that the research can be conducted with precision.
  • Falsifiability: A good research hypothesis should be falsifiable, meaning there should be a possibility of proving it wrong. This concept is fundamental to the scientific method, as hypotheses that cannot be tested or disproven lack scientific validity.

Frequently Asked Questions

How to write a hypothesis.

  • Clearly state the research question.
  • Identify the variables involved.
  • Formulate a clear and testable prediction.
  • Use specific and measurable terms.
  • Align the hypothesis with the research question.
  • Distinguish between the null hypothesis (no effect) and alternative hypothesis (expected effect).
  • Ensure the hypothesis is falsifiable and subject to empirical testing.

How to write a hypothesis for a lab?

  • Identify the purpose of the lab.
  • Clearly state the relationship between variables.
  • Use concise language and specific terms.
  • Make the hypothesis testable through experimentation.
  • Align with the lab’s objectives.
  • Include an if-then statement to express the expected outcome.
  • Ensure clarity and relevance to the experimental setup.

What Is A Null Hypothesis?

A null hypothesis is a statement suggesting no effect or relationship between variables in a research study. It serves as the default assumption, stating that any observed differences or effects are due to chance. Researchers aim to reject the null hypothesis based on statistical evidence to support their alternative hypothesis.

How to write a null hypothesis?

  • State there is no effect, difference, or relationship between variables.
  • Use clear and specific language.
  • Frame it in a testable manner.
  • Align with the research question.
  • Specify parameters for statistical testing.
  • Consider it as the default assumption to be tested and potentially rejected in favour of the alternative hypothesis.

What is the p-value of a hypothesis test?

The p-value in a hypothesis test represents the probability of obtaining observed results, or more extreme ones, if the null hypothesis is true. A lower p-value suggests stronger evidence against the null hypothesis, often leading to its rejection. Common significance thresholds include 0.05 or 0.01.

How to write a hypothesis in science?

  • Clearly state the research question
  • Identify the variables and their relationship.
  • Formulate a testable and falsifiable prediction.
  • Use specific, measurable terms.
  • Distinguish between the null and alternative hypotheses.
  • Ensure clarity and relevance to the scientific investigation.

How to write a hypothesis for a research proposal?

  • Clearly define the research question.
  • Identify variables and their expected relationship.
  • Formulate a specific, testable hypothesis.
  • Align the hypothesis with the proposal’s objectives.
  • Clearly articulate the null hypothesis.
  • Use concise language and measurable terms.
  • Ensure the hypothesis aligns with the proposed research methodology.

How to write a good hypothesis psychology?

  • Formulate a specific and testable prediction.
  • Use precise and measurable terms.
  • Align the hypothesis with psychological theories.
  • Articulate the null hypothesis.
  • Ensure the hypothesis guides empirical testing in psychological research.

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What is and How to Write a Good Hypothesis in Research?

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One of the most important aspects of conducting research is constructing a strong hypothesis. But what makes a hypothesis in research effective? In this article, we’ll look at the difference between a hypothesis and a research question, as well as the elements of a good hypothesis in research. We’ll also include some examples of effective hypotheses, and what pitfalls to avoid.

What is a Hypothesis in Research?

Simply put, a hypothesis is a research question that also includes the predicted or expected result of the research. Without a hypothesis, there can be no basis for a scientific or research experiment. As such, it is critical that you carefully construct your hypothesis by being deliberate and thorough, even before you set pen to paper. Unless your hypothesis is clearly and carefully constructed, any flaw can have an adverse, and even grave, effect on the quality of your experiment and its subsequent results.

Research Question vs Hypothesis

It’s easy to confuse research questions with hypotheses, and vice versa. While they’re both critical to the Scientific Method, they have very specific differences. Primarily, a research question, just like a hypothesis, is focused and concise. But a hypothesis includes a prediction based on the proposed research, and is designed to forecast the relationship of and between two (or more) variables. Research questions are open-ended, and invite debate and discussion, while hypotheses are closed, e.g. “The relationship between A and B will be C.”

A hypothesis is generally used if your research topic is fairly well established, and you are relatively certain about the relationship between the variables that will be presented in your research. Since a hypothesis is ideally suited for experimental studies, it will, by its very existence, affect the design of your experiment. The research question is typically used for new topics that have not yet been researched extensively. Here, the relationship between different variables is less known. There is no prediction made, but there may be variables explored. The research question can be casual in nature, simply trying to understand if a relationship even exists, descriptive or comparative.

How to Write Hypothesis in Research

Writing an effective hypothesis starts before you even begin to type. Like any task, preparation is key, so you start first by conducting research yourself, and reading all you can about the topic that you plan to research. From there, you’ll gain the knowledge you need to understand where your focus within the topic will lie.

Remember that a hypothesis is a prediction of the relationship that exists between two or more variables. Your job is to write a hypothesis, and design the research, to “prove” whether or not your prediction is correct. A common pitfall is to use judgments that are subjective and inappropriate for the construction of a hypothesis. It’s important to keep the focus and language of your hypothesis objective.

An effective hypothesis in research is clearly and concisely written, and any terms or definitions clarified and defined. Specific language must also be used to avoid any generalities or assumptions.

Use the following points as a checklist to evaluate the effectiveness of your research hypothesis:

  • Predicts the relationship and outcome
  • Simple and concise – avoid wordiness
  • Clear with no ambiguity or assumptions about the readers’ knowledge
  • Observable and testable results
  • Relevant and specific to the research question or problem

Research Hypothesis Example

Perhaps the best way to evaluate whether or not your hypothesis is effective is to compare it to those of your colleagues in the field. There is no need to reinvent the wheel when it comes to writing a powerful research hypothesis. As you’re reading and preparing your hypothesis, you’ll also read other hypotheses. These can help guide you on what works, and what doesn’t, when it comes to writing a strong research hypothesis.

Here are a few generic examples to get you started.

Eating an apple each day, after the age of 60, will result in a reduction of frequency of physician visits.

Budget airlines are more likely to receive more customer complaints. A budget airline is defined as an airline that offers lower fares and fewer amenities than a traditional full-service airline. (Note that the term “budget airline” is included in the hypothesis.

Workplaces that offer flexible working hours report higher levels of employee job satisfaction than workplaces with fixed hours.

Each of the above examples are specific, observable and measurable, and the statement of prediction can be verified or shown to be false by utilizing standard experimental practices. It should be noted, however, that often your hypothesis will change as your research progresses.

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Writing Beginner

How to Write a Hypothesis [31 Tips + Examples]

Writing hypotheses can seem tricky, but it’s essential for a solid scientific inquiry.

Here is a quick summary of how to write a hypothesis:

Write a hypothesis by clearly defining your research question, identifying independent and dependent variables, formulating a measurable prediction, and ensuring it can be tested through experimentation. Include an “if…then” statement for clarity.

I’ve crafted dozens in my research, from basic biology experiments to business marketing strategies.

Let me walk you through how to write a solid hypothesis, step by step.

Writing a Hypothesis: The Basics

Notebook and scientific diagrams glow amidst dramatic lighting -- How to Write a Hypothesis

Table of Contents

A hypothesis is a statement predicting the relationship between variables based on observations and existing knowledge. To craft a good hypothesis:

  • Identify variables – Determine the independent and dependent variables involved.
  • Predict relationships – Predict the interaction between these variables.
  • Test the statement – Ensure the hypothesis is testable and falsifiable.

A solid hypothesis guides your research and sets the foundation for your experiment.

31 Tips for Writing a Hypothesis

There are at least 31 tips to write a good hypothesis.

Keep reading to learn every tip plus three examples to make sure that you can instantly apply it to your writing.

Tip 1: Start with a Clear Research Question

A clear research question ensures your hypothesis is targeted.

  • Identify the broad topic you’re curious about, then refine it to a specific question.
  • Use guiding questions like “What impact does variable X have on variable Y?”
  • How does fertilizer affect plant growth?
  • Does social media influence mental health in teens?
  • Can personalized ads increase customer engagement?

Tip 2: Do Background Research

Research helps you understand current knowledge and any existing gaps.

  • Review scholarly articles, reputable websites, and textbooks.
  • Focus on understanding the relationships between variables in existing research.
  • Academic journals like ScienceDirect or JSTOR.
  • Google Scholar.
  • Reputable news articles.

Tip 3: Identify Independent and Dependent Variables

The independent variable is what you change or control. The dependent variable is what you measure.

  • Clearly define these variables to make your hypothesis precise.
  • Think of different factors that could be influencing your dependent variable.
  • Type of fertilizer (independent) and plant growth (dependent).
  • Amount of screen time (independent) and anxiety levels (dependent).
  • Marketing strategies (independent) and customer engagement (dependent).

Tip 4: Make Your Hypothesis Testable

A hypothesis must be measurable and falsifiable.

  • Ensure your hypothesis can be supported or refuted through data collection.
  • Include numerical variables or qualitative changes to ensure measurability.
  • “Increasing screen time will increase anxiety levels in teenagers.”
  • “Using fertilizer X will yield higher crop productivity.”
  • “A/B testing marketing strategies will show higher engagement with personalized ads.”

Tip 5: Be Specific and Concise

Keep your hypothesis straightforward and to the point.

  • Avoid vague terms that could mislead or cause confusion.
  • Clearly outline what you’re measuring and how the variables interact.
  • “Replacing chemical fertilizers with organic ones will result in slower plant growth.”
  • “A social media break will decrease anxiety in high school students.”
  • “Ads targeting user preferences will boost click-through rates by 10%.”

Tip 6: Choose Simple Language

Use simple, understandable language to ensure clarity.

  • Avoid jargon and overly complex terms that could confuse readers.
  • Make the hypothesis comprehensible to non-experts in the field.
  • “Organic fertilizer will reduce plant growth.”
  • “High schoolers will feel less anxious after a social media detox.”
  • “Targeted ads will increase customer engagement.”

Tip 7: Formulate a Null Hypothesis

A null hypothesis assumes no relationship between variables.

  • Create a counterpoint to your main hypothesis, asserting that there is no effect.
  • This allows you to compare results directly and identify statistical significance.
  • “Fertilizer type will not affect plant growth.”
  • “Social media use will not influence anxiety.”
  • “Targeted ads will not affect customer engagement.”

Tip 8: State Alternative Hypotheses

Provide alternative hypotheses to explore other plausible relationships.

  • They offer a contingency plan if your primary hypothesis is not supported.
  • These should still align with your research question and measurable variables.
  • “Fertilizer X will only affect plant growth if used in specific soil types.”
  • “Social media might impact anxiety only in certain age groups.”
  • “Customer engagement might only improve with highly personalized ads.”

Tip 9: Use “If…Then” Statements

“If…then” statements simplify the cause-and-effect structure.

  • The “if” clause identifies the independent variable, while “then” identifies the dependent.
  • It makes your hypothesis easier to understand and directly testable.
  • “If plants receive organic fertilizer, then their growth rate will slow.”
  • “If teens stop using social media, then their anxiety will decrease.”
  • “If ads are personalized, then click-through rates will increase.”

Tip 10: Avoid Assumptions

Don’t assume the audience understands your variables or relationships.

  • Clearly define terms and relationships to avoid misinterpretation.
  • Provide background context where necessary for clarity.
  • Define “anxiety” as a feeling of worry or unease.
  • Specify “plant growth” as the height and health of plants.
  • Describe “personalized ads” as ads matching user preferences.

Tip 11: Review Existing Literature

Previous research offers insights into forming a hypothesis.

  • Conduct a thorough literature review to identify trends and gaps.
  • Use these studies to refine and build upon your hypothesis.
  • Studies showing a link between screen time and anxiety.
  • Research on organic versus chemical fertilizers.
  • Customer behavior analysis in different marketing channels.

Tip 12: Consider Multiple Variables

Hypotheses with multiple variables can offer deeper insights.

  • Explore combinations of independent and dependent variables to see their relationships.
  • Plan experiments accordingly to distinguish separate effects.
  • Studying fertilizer type and soil composition effects on plant growth.
  • Testing social media use frequency and content type on anxiety.
  • Analyzing marketing strategies combined with product preferences.

Tip 13: Review Ethical Considerations

Ethics are essential for trustworthy research.

  • Avoid hypotheses that could cause harm to participants or the environment.
  • Seek approval from relevant ethical boards or committees.
  • Avoiding experiments causing undue stress to teenagers.
  • Preventing chemical contamination when testing fertilizers.
  • Respecting privacy with personalized ads.

Tip 14: Test with Pilot Studies

Small-scale pilot studies test feasibility and refine hypotheses.

  • Use them to identify potential issues and adjust before full-scale research.
  • Ensure pilot tests align with ethical standards.
  • Testing different fertilizer types on small plant samples.
  • Trying brief social media breaks with a small group of teens.
  • Conducting A/B tests on ad personalization with a subset of customers.

Tip 15: Build Hypotheses on Existing Theories

Existing theories provide strong foundations.

  • Use established frameworks to develop or refine your hypothesis.
  • Testing theoretical predictions can yield meaningful data.
  • Applying agricultural theories on soil and crop management.
  • Using psychology theories on screen addiction and mental health.
  • Referencing marketing theories like consumer behavior analysis.

Tip 16: Address Real-World Problems

Solve real-world problems through practical hypotheses.

  • Make sure your research question has relevant, impactful applications.
  • Focus on everyday challenges where actionable insights can help.
  • Testing new eco-friendly farming methods.
  • Reducing anxiety by improving digital wellbeing.
  • Improving marketing ROI with personalized strategies.

Tip 17: Aim for Clear, Measurable Outcomes

The results should be easy to measure and interpret.

  • Quantify your dependent variable or use defined qualitative measures.
  • Avoid overly broad or ambiguous outcomes.
  • Measuring plant growth as a percentage change in height.
  • Quantifying anxiety levels through standard surveys.
  • Tracking click-through rates as a percentage of total views.

Tip 18: Stay Open to Unexpected Results

Not all hypotheses yield expected results.

  • Be open to learning new insights, even if they contradict your prediction.
  • Unexpected findings often reveal unique, significant knowledge.
  • Unexpected fertilizer types boosting growth differently than anticipated.
  • Screen time affecting anxiety differently across various age groups.
  • Targeted ads backfiring with specific customer segments.

Tip 19: Keep Hypotheses Relevant

Ensure your hypothesis aligns with the purpose of your research.

  • Avoid straying from the original question or focusing on tangential issues.
  • Stick to the research scope to ensure accurate and meaningful data.
  • Focus on a specific type of fertilizer for plant growth.
  • Restrict studies to relevant age groups for anxiety research.
  • Keep marketing hypotheses within the same target customer segment.

Tip 20: Collaborate with Peers

Collaboration strengthens hypothesis development.

  • Work with colleagues or mentors for valuable feedback.
  • Peer review helps identify flaws or assumptions in your hypothesis.
  • Reviewing hypothesis clarity with a lab partner.
  • Sharing research plans with a mentor to refine focus.
  • Engaging in academic peer-review groups.

Tip 21: Re-evaluate Hypotheses Periodically

Revising hypotheses ensures relevance.

  • Update based on new literature, data, or technological advances.
  • A dynamic approach keeps your research current.
  • Refining fertilizer studies with recent organic farming research.
  • Adjusting social media hypotheses for new platforms like TikTok.
  • Modifying marketing hypotheses based on changing customer preferences.

Tip 22: Develop Compelling Visuals

Illustrating hypotheses can help communicate relationships effectively.

  • Use diagrams or flowcharts to show how variables interact visually.
  • Infographics make it easier for others to grasp your research concept.
  • A flowchart showing fertilizer effects on different plant growth stages.
  • Diagrams illustrating social media use and its psychological impact.
  • Infographics depicting how various marketing strategies boost engagement.

Tip 23: Refine Your Data Collection Plan

A solid data collection plan is vital for a testable hypothesis.

  • Determine the best ways to measure your dependent variable.
  • Ensure your data collection tools are reliable and accurate.
  • Using a ruler and image analysis software to measure plant height.
  • Designing standardized surveys to assess anxiety levels consistently.
  • Setting up click-through tracking with analytics software.

Tip 24: Focus on Logical Progression

Ensure your hypothesis logically follows your research question.

  • The relationship between variables should naturally flow from your observations.
  • Avoid logical leaps that might confuse your reasoning.
  • Predicting plant growth after observing effects of different fertilizers.
  • Linking anxiety to social media use based on screen time studies.
  • Connecting ad personalization with customer behavior data.

Tip 25: Test Against Diverse Samples

Testing across diverse samples ensures broader applicability.

  • Avoid drawing conclusions from overly narrow sample groups.
  • Try to include different demographics or subgroups in your testing.
  • Testing fertilizer effects on multiple plant species.
  • Including different age groups in anxiety research.
  • Experimenting with personalized ads across varied customer segments.

Tip 26: Use Control Groups

Control groups provide a baseline for comparison.

  • Compare your test group with a control group under unchanged conditions.
  • This allows you to isolate the effect of your independent variable.
  • Comparing plant growth with organic versus no fertilizer.
  • Testing anxiety levels with and without social media breaks.
  • Comparing personalized ads with general marketing content.

Tip 27: Consider Practical Constraints

Work within realistic constraints for your resources and timeline.

  • Assess the feasibility of testing your hypothesis.
  • Modify the hypothesis if the required testing is unmanageable.
  • Reducing fertilizer types to a manageable number for testing.
  • Shortening social media detox periods to realistic durations.
  • Targeting only specific marketing strategies to optimize testing.

Tip 28: Recognize Bias Risks

Biases can skew hypothesis formation.

  • Acknowledge your assumptions and how they may affect your research.
  • Minimize biases by clearly defining and measuring variables.
  • Avoiding assumptions that organic fertilizer is inherently better.
  • Ensuring survey questions don’t lead to specific anxiety outcomes.
  • Testing marketing strategies objectively without favoring any method.

Tip 29: Prepare for Peer Review

Peer review ensures your hypothesis holds up to scrutiny.

  • Provide a clear rationale for why your hypothesis is sound.
  • Address potential criticisms to strengthen your research.
  • Showing your plant growth study builds on existing fertilizer research.
  • Demonstrating social media anxiety links through data and literature.
  • Supporting your marketing hypotheses with solid behavioral data.

Tip 30: Create a Research Proposal

A proposal outlines your hypothesis, methodology, and significance.

  • It ensures your hypothesis is clear and your methods are well-thought-out.
  • Proposals also help secure funding or institutional approval.
  • A proposal for fertilizer studies linking plant growth and soil health.
  • Research plans connecting social media habits to anxiety measures.
  • Marketing proposals tying customer behavior to personalized advertising.

Tip 31: Document Your Findings

Recording findings helps validate or challenge your hypothesis.

  • Document the methodology, data, and conclusions clearly.
  • This allows others to verify, replicate, or expand on your work.
  • Recording fertilizer effects on plant height in different soil types.
  • Survey results linking social media use with anxiety levels.
  • Click-through data proving personalized ads’ impact on engagement.

Check out this really good video about how to write a hypothesis:

Hypothesis Examples for Different Situations

Let’s look at some examples of how to write a hypothesis in different circumstances.

  • Marketing Analysis : “If personalized ads are shown to our target demographic, then click-through rates will increase by at least 10%.”
  • Process Improvement : “If automated workflows replace manual data entry, then task completion times will decrease by 20%.”
  • Product Development : “If adding a chatbot feature to our app increases customer support efficiency, then user satisfaction will improve by 15%.”
  • Biology Experiment : “If students grow plants with different fertilizers, then the organic fertilizer will result in slower growth compared to the chemical fertilizer.”
  • Psychology Research : “If high school students take a break from social media, then their levels of anxiety will decrease.”
  • Environmental Study : “If a controlled forest area is exposed to a certain pollutant, then the local plant species will show signs of damage within two weeks.”

Professional Contacts

  • Medical Research : “If a novel treatment method is applied to patients with chronic illness, then their recovery rate will increase significantly compared to standard treatment.”
  • Technology Research : “If machine learning algorithms analyze big data sets, then the accuracy of predictive models will surpass traditional data analysis.”
  • Engineering Project : “If new composite materials replace standard components in bridge construction, then the resulting structure will be more durable.”

Super Personal

  • Gardening Experiment : “If different types of compost are used in home gardens, then plants receiving homemade compost will yield the most produce.”
  • Fitness Routine : “If consistent strength training is combined with a high-protein diet, then muscle mass will increase more than with diet alone.”
  • Cooking Techniques : “If searing is added before baking, then the resulting roast will retain more moisture.”

Final Thoughts: How to Write a Hypothesis

Crafting hypotheses is both a science and an art. It’s about channeling curiosity into testable questions that propel meaningful discovery.

Each well-thought-out hypothesis is a stepping stone that could lead to the breakthrough you’ve been seeking.

Stay curious and let your research journey unfold.

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Define Hypothesis: Unveiling the First Step in Scientific Inquiry

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Welcome to the world of research, where you’ll journey through a universe brimming with questions and curiosity. In this cosmos, a hypothesis is one celestial object you can’t miss! Today’s expedition invites you on board an exploration to ‘Define Hypothesis.’ Hop in; it wouldn’t be hyperbole to state we’re about to unlock the nucleus behind every ever scientific theory and inquiry!

Definition of Hypothesis

Introduction to the concept of hypothesis.

Picture yourself as a detective solving a case. Right from inspecting clues, formulating potential theories on whodunit, putting these theories under rigorous tests until finally reaching that elusive conclusive evidence – exciting, isn’t it?

Now replace detective with researcher and voila – here comes our heavyweight term: Hypothesis. Much like how any plausible theory drives detectives’ investigations, scientific hypotheses are vital navigational compasses guiding researchers in their quest for scientific evolutions.

Explanation of What a Hypothesis Is in The Context of Research and Scientific Inquiry

A hypothesis – popularly known as an educated guess or predictive statement – represents an initial supposition or proposed explanation made on limited information but founded on validation-grounded knowledge. It forms the basis for preliminary exploration into a specific set of circumstances or natural phenomena beyond.

Formulated prior to conducting research, scientists employ hypotheses as testable conjectures to explain an observed behavior or event. Confused? Fret not. To put it simply and by example: “If I increase the frequency of watering my plants twice daily (instead of solely relying upon weather conditions), then they will grow faster.” Now that’s what we call an everyday-life hypothesis!

Remember, hypotheses are not wild guesses plucked out of thin air but rather preconceived assertions open to empirical verification. They mark the inception point for any scientific investigation and serve as cornerstones for further experiments.

Characteristics and Components of a Hypothesis

Key characteristics of a hypothesis.

Before plunging into the deep end to define a hypothesis, let’s brush up on the features that contribute to effective hypotheses. For starters, a strong hypothesis is testable. This means it must be possible for empirical evidence to either support the word hypothesis or contradict it. The proposal should also be logically consistent and grounded firmly in existing knowledge.

Further down the line, another salient feature is specificity. Good hypotheses are not broad statements but instead focus on a specific aspect or phenomenon within the intended research field. Moreover, they are typically succinct and easily understandable ensuring information isn’t lost in translation among researchers.

Moreover, any well-structured hypothesis connects the independent and dependent variables together – typically, there’s at least one independent and one dependent variable involved. These elements form a relationship where changes instigated in the independent variable affect the values observed for the dependent variable.

Lastly but importantly, a solid hypothesis often carries potential implications for future research areas and can potentially lead to further tests and studies if verified.

Elements that make up a well-formulated hypothesis

Delving deeper into what shapes up a robust hypothesis, we realize that certain crucial components determine its effectiveness.

Firstly, every good hypothesis or test has clear variables which essentially refer to specific aspects of the study subject matter being measured or manipulated during research. These aspects are segregated as:

  • Independent Variable (IV): This component relates directly to what you have control over in your study.
  • Dependent Variable (DV): This component consists of outcomes affected by alterations made in IV

Next comes ‘Predicted Outcome’ – what you anticipate happening as repercussions due to modification of two or more variables under scrutiny.

The ‘Testability’ factor also holds veritable importance comprising experimental procedures capable enough to refute or accept your claims.

The last element circles the argument around presenting a capacity called ‘Relationship’ correlating IV with DV believed to either causing some effect or showcasing an association.

Hence, these prime facets further accentuate your endeavor to adequately define the hypothesis.

Importance and Purpose of a Hypothesis

Understanding the Role of a Hypothesis in Research

First, let’s delve into the overarching role that hypothesis plays within research scenarios. As we define the hypothesis, you should view this as an underlying pillar or guiding star for your investigation. A well-articulated hypothesis steers your exploration by providing clarity on what specifically you aim to examine.

A meaningful analogy would be considering a hypothesis as a compass during a voyage. If research is the vast ocean where confusing whirlpools of data and evidence abound, then it can guide us in our direction rather than letting us drift aimlessly. Furthermore, the formulation of a quality hypothesis inherently demands clarity about your objectives upfront – this essentially sets your research vessel on course bearing towards effective outcomes.

Exploring Why Formulating A Hypothesis is Crucial in Scientific Investigations

So why precisely is nurturing such a detailed forecast vital?

  • Structural Advantage: By proposing potential answers to posed questions via hypotheses, researchers streamline their methods and techniques. The approach undertaken depends significantly on what the suggested outcome or phenomenon might be.
  • Generate Preliminary Expectations: Even if they’re proven wrong, making observations and developing models based on hypotheses often lead to more interesting inquiries or turn up unexpected findings.
  • Quantifiable Predictions: More than simple conjectures, strong hypotheses are testable; they propose results expressed in measurable terms.

In essence, remember that formulating hypotheses smoothes the path towards solid conclusions by being the architect’s blueprints of robust investigations. Never underestimate the forward thrust they provide for progress within scientific inquiry!

Types of Hypotheses

Once we understand to define a hypothesis, we’ll find that hypotheses come in several types. Different classifications of plural hypotheses depend on their formulations and the nature of predictions or assumptions they lead towards – simple, complex, directional, non-directional, null, associative and causal. Let’s explore some of these.

Simple Hypothesis: Definition and Examples

A simple hypothesis is a type of prediction or an educated guess that carries one independent variable and one dependent variable. In essence, it creates a relationship between two singular entities; for instance, ‘Exercise improves memory.’ This suggests that there’s an impact (of improvement) on the ‘memory’ (dependent variable) by ‘exercise’ (independent variable).

Complex Hypothesis: Definition and Examples

On the contrary to its name mate – a simple hypothesis – a complex hypothesis involves more than just two variables. It points out multiple variables and how they interlink with each other. The effects aren’t just limited to cause-and-effect but can be interactive or combined impact-dependent variables too – for instance,’Diet and exercise affect weight loss and heart health.’ Here, diet and exercise are your independent factors influencing multifold aspects like weight loss (a dependent variable) alongside heart health(another dependent variable).

Directional Hypothesis: Definition and Examples

One might argue that the path laid by a directional hypothesis is less twisted as it predicts the directionality of an effect – whether one variable will increase or decrease another variable. An example here could be “Cutting down on alcohol will reduce liver disorders.” Here a reduction in ‘drinking alcohol’ implicitly identifies fewer occurrences of ‘liver disorders.’

Non-directional Hypothesis: Definition and Examples

Sometimes science requires open-ended answers; henceforth comes into play our non-directional hypothesis which merely stipulates that there’s going to be an impact without specifying its course – good, bad or otherwise. For example, “Exposure to secondhand smoke influences lung health.” It infers that there’s an effect on ‘lung health’ due to ‘secondhand smoke,’ without indicating if it’s an improvement or deterioration.

Null Hypothesis: Definition and Examples

The null hypothesis, often symbolized as H0, makes things pretty straight with assumptions; basically, it purports no existence of a relationship between the variables. Researchers utilize this hypothesis chiefly for statistical testing. In lay terms – “Smoking is not linked to lung cancer.” Here a nonexistence of association is suggested between ‘smoking’ and ‘lung cancer.’

Associative and Causal Hypothesis: Explanation and Examples

Now leaving the train station named Null-ville we enter into quite associative terrain where the associative hypothesis foretells ‘relationships’ but are shy when it comes to cause-effects. An instance could be “Students scoring high also tend to play chess.” These fellows here don’t claim that playing chess outrightly shoots up scores yet suggests a specific pattern.

On another spectrum brightful cause-effect claims jump in bravely shouting out not just relationships but boldly stating their causes too – “Consumption of fast food leads to obesity” is being so certain about fast food consumption (cause) escalating obesity levels(effect).

Navigating through these alternative hypotheses and variants allows us to step into researchers’ shoes better while also helps defining complex constructions bit by bit, making them simple outcomes anyone can interpret.

Developing and Testing a Hypothesis

In the world of research, it’s not uncommon to hear someone say “Let’s define hypothesis!” This term may seem complex at first glance, but its essence falls within our natural instinct to question and learn. To give structure to this innate curiosity, we form hypotheses and navigate through the rigorous process of testing them.

Process of Formulating a Hypothesis

Forming an effective hypothesis is both an art and a science. It involves finding a perfect blend between creativity and logical reasoning. Here are some simple yet essential steps you’d want to follow:

  • Identify Your Research Question – The first step towards formulating a hypothesis is defining your research question based on preliminary observations or literature review.
  • Conduct Thorough Literature Review – Once your question is in place, an extensive read about what has already been studied can help refine it further.
  • Create Tentative Explanation – Develop a preliminary answer based on your knowledge and understanding which will serve as your tentative explanation or hypothesis.
  • Refine Your Hypothesis : Refine this initial guess considering available resources for empirical testing, ethical implications, and potential outcomes.

Remember that the key is formation clarity in statement-making; overly complex language might obscure rather than clarify your central idea.

Importance of Testing a Hypothesis Through Empirical Research Methods

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Testing a hypothesis isn’t simply about proving it right or wrong; it’s much more refined than that – it’s about validation and advancement of human knowledge. By applying empirical methods such as observation or experimentation, logic meets practice in real-world scenarios.

These hands-on approaches afford us precious insights into how our theories hold up under scrutiny outside the confines of abstract thought alone.

  • Validity Confirmation : Empirical testing helps confirm if our predictions were correct or not, providing validation for our presumptions.
  • Understanding Relationships : Testing allows us to assess the relational dynamics between variables under investigation.
  • Promotes Scientific Inquiry : Empirical testing encourages a systematic and objective approach to understanding phenomena, which lies at the heart of scientific inquiry.

Consider this: hypotheses are our best-educated guesses – smart hunches rooted in what we know so far. To move beyond guessing and into knowledgeable assertion, we define hypothesis structure as one that can be empirically tested. Only then do we truly start to shape our understanding with any level of certainty.

Examples of Hypotheses in Different Fields

Indeed, it’s fundamental to understand that hypotheses are not confined to a single discipline but span across numerous fields. To better illuminate this, let’s delve into various examples.

Examples of Hypotheses in Scientific Research Studies

In the realm of scientific research studies, hypotheses play a pivotal role in shaping the basis for investigations research hypotheses and experiments. Let’s consider an elementary example: studying plant growth. A researcher might formulate the hypothesis – “If a specific type of fertilizer is used, then plants will grow more rapidly.” This hypothesis aims to validate or refute the assumption that given fertilizer perceptibly affects plant growth rate.

Another common example arises from investigating causal relationships between physical activity and heart health. The scientist may hypothesize that “Regular aerobic exercise decreases the risk of heart disease.”

Examples of Hypotheses in Social Sciences

When we transition towards social sciences, which deals with human behavior and its relation to societal constructs, our formative definitions undergo a change as well.

Imagine researchers examining how socioeconomic status influences educational attainment rates. They could pose a hypothesis saying, “High socioeconomic status positively correlates with higher levels of formal education.” This hypothesis attempts to tie economic background directly to education outcomes.

The correlation between gender diversity within workplace teams and improved business performance presents another illustration. A possible hypothesis could be – “Teams comprising diverse genders exhibit superior business performance than homogenous teams.”

Examples of Hypotheses in Psychology

Within psychology – the study dedicated to how individuals think, feel, and behave; clearly stated hypotheses serve as essential stepping stones for meaningful findings and insights.

Take, for instance, predicting performance under pressure: psychologists may propose an assumption like – “Stress triggers increased errors on complex tasks”. Or when researching cognitive development in children – they may hypothesize – “Language acquisition accelerates once children start attending school”.

Examples of Hypotheses in Medical Research

Lastly but importantly, in medical research, well-articulated hypotheses help probe pressing healthcare questions and identify effective treatments.

For instance: “Patients receiving chemotherapy experience significant weight loss”. Or regarding disease transmission during pandemics – they might propose “Regular hand sanitation reduces the risk of COVID-19 infection.”

In conclusion, these examples hopefully underline the importance and versatility of a hypothesis in scientific inquiry. Irrespective of its utilization within various research fields, a scientific hypothesis still essentially remains an educated assumption that offers direction and purpose to the investigation. Interestingly enough, each study’s defined hypothesis sets forth a path leading towards a better comprehension of our world and life within it.

Common Mistakes to Avoid when Formulating a Hypothesis

Identifying errors that researchers often make when developing a hypothesis.

Many researchers, especially those new in the field, may sometimes falter while crafting their hypotheses. Here are some frequently observed mistakes:

  • Framing Vague Hypotheses : Clarity is vital when defining your hypothesis. A common pitfall involves creating an ambiguous statement which leaves room for multiple interpretations. This hinders precise data collection and analysis.
  • Formulating Unfalsifiable Hypotheses : These are statements that cannot be proven false because they don’t connect to observable or measurable variables.
  • Targeting Unachievable Results : Often, there is an inclination to develop complex hypotheses expecting groundbreaking findings. However, it’s crucial to limit the scope according to practical constraints and possibilities.
  • Ignoring Null Hypothesis : The null hypothesis provides a means of contradiction to the alternative hypothesis being tested, making it essential for any research study.

Tips for avoiding these mistakes

After identifying the commonly made errors when forming a hypothesis, let’s now consider some proactive measures you can adopt:

  • Crystallize Your Thoughts : Before you articulate your hypothesis, refine and clarify your ideas first. Define the parameters of your study clearly and ensure your proposition directly aligns with them.
  • Keep It Simple : Stick with simplicity as much as possible in describing expected relationships or patterns in your research subject area. Remember: A simpler hypothesis often leads to effective testing.
  • Embrace Falsifiability . To avoid making unfalsifiable claims, learn how to craft ‘If – Then’ statements articulately in your define hypothesis process.
  • Remember the Null Hypothesis : Always formulate and account for a null hypothesis—a statement that negates the relationship between variables—for robust results validation.

In truth, it takes practice to strike the right balance and formulate a solid, practical hypothesis for your research. With these tips in mind, you’re better equipped to avoid common pitfalls that can compromise the quality of your investigation as they guide your approach when you define hypotheses.

Evaluating and Refining a Hypothesis

Laying out a hypothesis is merely the first stage of an intricate journey. Testing and refining this conjecture is equally pivotal in perfecting your next scientific method of undertaking. This pathway comprises evaluation for validity, and relevance, followed by refinement through research findings.

Methods for Assessing the Validity and Relevance of a Hypothesis

To define a hypothesis of meticulosity, we need to subject it to rigorous scrutiny. Utilizing statistical tests enables you to judge the validity of your hypothesis. Here’s a brief look at some key methods that can assist in assessing your theory:

  • Empirical Testing : Conduct experiments or surveys as per the requirements of your study.
  • Consistency Check : The hypothesis should remain consistent with other established theories and laws within its field.
  • Falsifiability principle : Proposed by Karl Popper, a valid hypothesis must be capable of being proven wrong.

Let me reemphasize here, that relevance plays an integral part too especially when defining hypotheses linked with pragmatics like social sciences or business studies.

A relevant hypothesis will hold significance to not just existing knowledge but also pave the way for future work within the particular area of expertise. It should address gaps in current scientific theories while shedding light on possible solutions.

Ways to Refine and Modify a Hypothesis Based on Research Findings

Our job doesn’t end up on developing an initial proposition; it’s crucial to use findings from our research to refine that preliminary conception further. This essential process breathes life into what was once purely speculative.

While refining your conjecture can sound daunting initially, I assure you it’s nothing more complicated than diagnosing any missing links between your original theory and novel evidence you’ve discovered along this research journey.

If H0 (null hypothesis) contradicts your empirical results, then getting back onto the drafting board becomes necessary for crafting H1 (alternative hypothesis). This scientific cycle of formulating, testing then reformulating the hypotheses can continue till we eventually reach statistically significant results.

Remember, it’s important to be open-minded and responsive towards indications from your research findings. They will guide you intuitively in tweaking your working hypothesis in sync with your target goals.

Hence we must embrace this intricate art of defining a hypothesis while simultaneously embracing its dynamic nature which requires periodic refinement based upon insightful feedback from meticulous research.

Summarizing the Key Points About the Definition and Characteristics of a Hypothesis

Having delved into the concept extensively, we can confidently define a hypothesis as an informed and testable guess or prediction that acts as a guiding light in research studies and scientific investigations. When formulated correctly, it comprises two essential elements: clarity and specificity. It should be free from ambiguity, allowing other researchers to easily understand its proposed idea and the direction the study is heading.

In addition, a robust hypothesis exhibits predictability. As a researcher, you’re not only stating what you think will happen but also defining the variables in your experiment – your assumption confines your investigation’s parameters to make it manageable. Lastly, remember that any meaningful hypothesis must be verifiable — capable of being supported or refuted through data collection and analysis.

Reiterating the Importance of Hypotheses in Scientific Inquiry and Research

This discourse wouldn’t be complete without reaffirming how indispensable hypotheses are within scientific explorations and research inquiries. A conceptualized hypothesis serves as a foundational block upon which every aspect of a research project is built. It directs your observations along assumed patterns, thereby saving time during investigations.

We also need to note that formulating hypotheses promotes critical thinking skills among researchers because they require logical reasoning backed by empirical evidence rather than just empty conjectures.

Henceforth, whether you’re treading through unchartered waters of complex scientific endeavors or conducting social science research with less strict rules for predictions – keeping these insights on “define hypothesis” at hand would surely enhance your journey towards revealing valuable truths.

In essence, cultivating a comprehensive understanding of what constitutes a well-formed hypothesis not only lends credibility to our investigative ventures but also enables us to bring precision, focus, and relevance to our chosen field of exploration. The power lies in its simplistic yet profound ability to guide us from uncertainty towards concrete evidential findings – truly embodying scientific inquiry’s spirit!

Unlock the Power of Visualization with Mind the Graph: Elevate Your Hypothesis to New Heights

As a scientist, your hypothesis is the cornerstone of your research journey. But what if you could take it beyond mere words and equations, and transform it into a visual masterpiece that captivates your audience? Enter Mind the Graph , your ultimate ally in scientific visualization. With our intuitive platform, you can seamlessly translate complex hypotheses into stunning graphs, charts, and illustrations that speak volumes. Whether you are presenting at a conference, publishing a paper, or simply sharing your findings with the world, Mind the Graph empowers you to convey your hypotheses with clarity, precision, and undeniable impact. Join the scientific revolution today and let your hypotheses shine like never before with Mind the Graph.

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About Fabricio Pamplona

Fabricio Pamplona is the founder of Mind the Graph - a tool used by over 400K users in 60 countries. He has a Ph.D. and solid scientific background in Psychopharmacology and experience as a Guest Researcher at the Max Planck Institute of Psychiatry (Germany) and Researcher in D'Or Institute for Research and Education (IDOR, Brazil). Fabricio holds over 2500 citations in Google Scholar. He has 10 years of experience in small innovative businesses, with relevant experience in product design and innovation management. Connect with him on LinkedIn - Fabricio Pamplona .

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Learn How To Write A Hypothesis For Your Next Research Project!

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Undoubtedly, research plays a crucial role in substantiating or refuting our assumptions. These assumptions act as potential answers to our questions. Such assumptions, also known as hypotheses, are considered key aspects of research. In this blog, we delve into the significance of hypotheses. And provide insights on how to write them effectively. So, let’s dive in and explore the art of writing hypotheses together.

Table of Contents

What is a Hypothesis?

A hypothesis is a crucial starting point in scientific research. It is an educated guess about the relationship between two or more variables. In other words, a hypothesis acts as a foundation for a researcher to build their study.

Here are some examples of well-crafted hypotheses:

  • Increased exposure to natural sunlight improves sleep quality in adults.

A positive relationship between natural sunlight exposure and sleep quality in adult individuals.

  • Playing puzzle games on a regular basis enhances problem-solving abilities in children.

Engaging in frequent puzzle gameplay leads to improved problem-solving skills in children.

  • Students and improved learning hecks.

S tudents using online  paper writing service  platforms (as a learning tool for receiving personalized feedback and guidance) will demonstrate improved writing skills. (compared to those who do not utilize such platforms).

  • The use of APA format in research papers. 

Using the  APA format  helps students stay organized when writing research papers. Organized students can focus better on their topics and, as a result, produce better quality work.

The Building Blocks of a Hypothesis

To better understand the concept of a hypothesis, let’s break it down into its basic components:

  • Variables . A hypothesis involves at least two variables. An independent variable and a dependent variable. The independent variable is the one being changed or manipulated, while the dependent variable is the one being measured or observed.
  • Relationship : A hypothesis proposes a relationship or connection between the variables. This could be a cause-and-effect relationship or a correlation between them.
  • Testability : A hypothesis should be testable and falsifiable, meaning it can be proven right or wrong through experimentation or observation.

Types of Hypotheses

When learning how to write a hypothesis, it’s essential to understand its main types. These include; alternative hypotheses and null hypotheses. In the following section, we explore both types of hypotheses with examples. 

Alternative Hypothesis (H1)

This kind of hypothesis suggests a relationship or effect between the variables. It is the main focus of the study. The researcher wants to either prove or disprove it. Many research divides this hypothesis into two subsections: 

  • Directional 

This type of H1 predicts a specific outcome. Many researchers use this hypothesis to explore the relationship between variables rather than the groups. 

  • Non-directional

You can take a guess from the name. This type of H1 does not provide a specific prediction for the research outcome. 

Here are some examples for your better understanding of how to write a hypothesis.

  • Consuming caffeine improves cognitive performance.  (This hypothesis predicts that there is a positive relationship between caffeine consumption and cognitive performance.)
  • Aerobic exercise leads to reduced blood pressure.  (This hypothesis suggests that engaging in aerobic exercise results in lower blood pressure readings.)
  • Exposure to nature reduces stress levels among employees.  (Here, the hypothesis proposes that employees exposed to natural environments will experience decreased stress levels.)
  • Listening to classical music while studying increases memory retention.  (This hypothesis speculates that studying with classical music playing in the background boosts students’ ability to retain information.)
  • Early literacy intervention improves reading skills in children.  (This hypothesis claims that providing early literacy assistance to children results in enhanced reading abilities.)
  • Time management in nursing students. ( Students who use a  nursing research paper writing service  have more time to focus on their studies and can achieve better grades in other subjects. )

Null Hypothesis (H0)

A null hypothesis assumes no relationship or effect between the variables. If the alternative hypothesis is proven to be false, the null hypothesis is considered to be true. Usually a null hypothesis shows no direct correlation between the defined variables. 

Here are some of the examples

  • The consumption of herbal tea has no effect on sleep quality.  (This hypothesis assumes that herbal tea consumption does not impact the quality of sleep.)
  • The number of hours spent playing video games is unrelated to academic performance.  (Here, the null hypothesis suggests that no relationship exists between video gameplay duration and academic achievement.)
  • Implementing flexible work schedules has no influence on employee job satisfaction.  (This hypothesis contends that providing flexible schedules does not affect how satisfied employees are with their jobs.)
  • Writing ability of a 7th grader is not affected by reading editorial example. ( There is no relationship between reading an  editorial example  and improving a 7th grader’s writing abilities.) 
  • The type of lighting in a room does not affect people’s mood.  (In this null hypothesis, there is no connection between the kind of lighting in a room and the mood of those present.)
  • The use of social media during break time does not impact productivity at work.  (This hypothesis proposes that social media usage during breaks has no effect on work productivity.)

As you learn how to write a hypothesis, remember that aiming for clarity, testability, and relevance to your research question is vital. By mastering this skill, you’re well on your way to conducting impactful scientific research. Good luck!

Importance of a Hypothesis in Research

A well-structured hypothesis is a vital part of any research project for several reasons:

  • It provides clear direction for the study by setting its focus and purpose.
  • It outlines expectations of the research, making it easier to measure results.
  • It helps identify any potential limitations in the study, allowing researchers to refine their approach.

In conclusion, a hypothesis plays a fundamental role in the research process. By understanding its concept and constructing a well-thought-out hypothesis, researchers lay the groundwork for a successful, scientifically sound investigation.

How to Write a Hypothesis?

Here are five steps that you can follow to write an effective hypothesis. 

Step 1: Identify Your Research Question

The first step in learning how to compose a hypothesis is to clearly define your research question. This question is the central focus of your study and will help you determine the direction of your hypothesis.

Step 2: Determine the Variables

When exploring how to write a hypothesis, it’s crucial to identify the variables involved in your study. You’ll need at least two variables:

  • Independent variable : The factor you manipulate or change in your experiment.
  • Dependent variable : The outcome or result you observe or measure, which is influenced by the independent variable.

Step 3: Build the Hypothetical Relationship

In understanding how to compose a hypothesis, constructing the relationship between the variables is key. Based on your research question and variables, predict the expected outcome or connection. This prediction should be specific, testable, and, if possible, expressed in the “If…then” format.

Step 4: Write the Null Hypothesis

When mastering how to write a hypothesis, it’s important to create a null hypothesis as well. The null hypothesis assumes no relationship or effect between the variables, acting as a counterpoint to your primary hypothesis.

Step 5: Review Your Hypothesis

Finally, when learning how to compose a hypothesis, it’s essential to review your hypothesis for clarity, testability, and relevance to your research question. Make any necessary adjustments to ensure it provides a solid basis for your study.

In conclusion, understanding how to write a hypothesis is crucial for conducting successful scientific research. By focusing on your research question and carefully building relationships between variables, you will lay a strong foundation for advancing research and knowledge in your field.

Hypothesis vs. Prediction: What’s the Difference?

Understanding the differences between a hypothesis and a prediction is crucial in scientific research. Often, these terms are used interchangeably, but they have distinct meanings and functions. This segment aims to clarify these differences and explain how to compose a hypothesis correctly, helping you improve the quality of your research projects.

Hypothesis: The Foundation of Your Research

A hypothesis is an educated guess about the relationship between two or more variables. It provides the basis for your research question and is a starting point for an experiment or observational study.

The critical elements for a hypothesis include:

  • Specificity: A clear and concise statement that describes the relationship between variables.
  • Testability: The ability to test the hypothesis through experimentation or observation.

To learn how to write a hypothesis, it’s essential to identify your research question first and then predict the relationship between the variables.

Prediction: The Expected Outcome

A prediction is a statement about a specific outcome you expect to see in your experiment or observational study. It’s derived from the hypothesis and provides a measurable way to test the relationship between variables.

Here’s an example of how to write a hypothesis and a related prediction:

  • Hypothesis: Consuming a high-sugar diet leads to weight gain.
  • Prediction: People who consume a high-sugar diet for six weeks will gain more weight than those who maintain a low-sugar diet during the same period.

Key Differences Between a Hypothesis and a Prediction

While a hypothesis and prediction are both essential components of scientific research, there are some key differences to keep in mind:

  • A hypothesis is an educated guess that suggests a relationship between variables, while a prediction is a specific and measurable outcome based on that hypothesis.
  • A hypothesis can give rise to multiple experiment or observational study predictions.

To conclude, understanding the differences between a hypothesis and a prediction, and learning how to write a hypothesis, are essential steps to form a robust foundation for your research. By creating clear, testable hypotheses along with specific, measurable predictions, you lay the groundwork for scientifically sound investigations.

Here’s a wrap-up for this guide on how to write a hypothesis. We’re confident this article was helpful for many of you. We understand that many students struggle with writing their school research . However, we hope to continue assisting you through our blog tutorial on writing different aspects of academic assignments.

For further information, you can check out our reverent blog or contact our professionals to avail amazing writing services. Paper perk experts tailor assignments to reflect your unique voice and perspectives. Our professionals make sure to stick around till your satisfaction. So what are you waiting for? Pick your required service and order away!

How to write a good hypothesis?

How to write a hypothesis in science, how to write a research hypothesis, how to write a null hypothesis, what is the format for a scientific hypothesis, how do you structure a proper hypothesis, can you provide an example of a hypothesis, what is the ideal hypothesis structure.

The ideal hypothesis structure includes the following;

  • A clear statement of the relationship between variables.
  • testable prediction.
  • falsifiability.

If your hypothesis has all of these, it is both scientifically sound and effective.

How to write a hypothesis for product management?

Writing a hypothesis for product management involves a simple process:

  • First, identify the problem or question you want to address.
  • State your assumption or belief about the solution to that problem. .
  • Make a hypothesis by predicting a specific outcome based on your assumption.
  • Make sure your hypothesis is specific, measurable, and testable.
  • Use experiments, data analysis, or user feedback to validate your hypothesis.
  • Make informed decisions for product improvement.

Following these steps will help you in effectively formulating hypotheses for product management.

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HOW TO WRITE A HYPOTHESIS

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Writing a hypothesis

Frequently, when we hear the word ‘hypothesis’, we immediately think of an investigation in the form of a science experiment. This is not surprising, as science is the subject area where we are usually first introduced to the term.

However, the term hypothesis also applies to investigations and research in many diverse areas and branches of learning, leaving us wondering how to write a hypothesis in statistics and how to write a hypothesis in sociology alongside how to write a hypothesis in a lab report.

We can find hypotheses at work in areas as wide-ranging as history, psychology, technology, engineering, literature, design, and economics. With such a vast array of uses, hypothesis writing is an essential skill for our students to develop.

What Is a Hypothesis?

how to write a hypothesis | Hypothesis definition | HOW TO WRITE A HYPOTHESIS | literacyideas.com

A hypothesis is a proposed or predicted answer to a question. The purpose of writing a hypothesis is to follow it up by testing that answer. This test can take the form of an investigation, experiment, or writing a research paper that will ideally prove or disprove the hypothesis’s prediction.

Despite this element of the unknown, a hypothesis is not the same thing as a guess. Though the hypothesis writer typically has some uncertainty, the creation of the hypothesis is generally based on some background knowledge and research of the topic. The writer believes in the likelihood of a specific outcome, but further investigation will be required to validate or falsify the claim made in their hypothesis.

In this regard, a hypothesis is more along the lines of an ‘educated guess’ that has been based on observation and/or background knowledge.

A hypothesis should:

  • Make a prediction
  • Provide reasons for that prediction
  • Specifies a relationship between two or more variables
  • Be testable
  • Be falsifiable
  • Be expressed simply and concisely
  • Serves as the starting point for an investigation, an experiment, or another form of testing

A COMPLETE TEACHING UNIT ON WRITING PROCEDURAL TEXTS

how to write a hypothesis | procedural text writing unit 1 | HOW TO WRITE A HYPOTHESIS | literacyideas.com

This HUGE BUNDLE  offers 97 PAGES of hands-on, printable, and digital media resources. Your students will be WRITING procedures with STRUCTURE, INSIGHT AND KNOWLEDGE like never before.

Hypothesis Examples for Students and Teachers

If students listen to classical music while studying, they will retain more information.

Mold growth is affected by the level of moisture in the air.

Students who sleep for longer at night retain more information at school.

Employees who work more than 40 hours per week show higher instances of clinical depression.

Time spent on social media is negatively correlated to the length of the average attention span.

People who spend time exercising regularly are less likely to develop a cardiovascular illness.

If people are shorter, then they are more likely to live longer.

What are Variables in a Hypothesis?

Variables are an essential aspect of any hypothesis. But what exactly do we mean by this term?

Variables are changeable factors or characteristics that may affect the outcome of an investigation. Things like age, weight, the height of participants, length of time, the difficulty of reading material, etc., could all be considered variables.

Usually, an investigation or experiment will focus on how different variables affect each other. So, it is vital to define the variables clearly if you are to measure the effect they have on each other accurately.

There are three main types of variables to consider in a hypothesis. These are:

  • Independent Variables
  • Dependent Variables

The Independent Variable

The independent variable is unaffected by any of the other variables in the hypothesis. We can think of the independent variable as the assumed cause .

The Dependent Variable

The dependent variable is affected by the other variables in the hypothesis. It is what is being tested or measured. We can think of the dependent variable as the assumed effect .

For example, let’s investigate the correlation between test scores across different age groups. The age groups will be the independent variable, and the test scores will be the dependent variable .

Now that we know what variables are let’s look at how they work in the various types of hypotheses.

Types of Hypotheses

There are many different types of hypotheses, and it is helpful to know the most common of these if the student selects the most suitable tool for their specific job.

The most frequently used types of hypotheses are:

The Simple Hypothesis

The complex hypothesis, the empirical hypothesis, the null hypothesis, the directional hypothesis, the non-directional hypothesis.

This straightforward hypothesis type predicts the relationship between an independent and dependent variable.

Example: Eating too much sugar causes weight gain.

This type of hypothesis is based on the relationship between multiple independent and/or dependent variables.

Example: Overeating sugar causes weight gain and poor cardiovascular health.

Also called a working hypothesis, an empirical hypothesis is tested through observation and experimentation. An empirical hypothesis is produced through investigation and trial and error. As a result, the empirical hypothesis may change its independent variables in the process.

Example: Exposure to sunlight helps lettuces grow faster.

This hypothesis states that there is no significant or meaningful relationship between specific variables.

Example: Exposure to sunlight does not affect the rate of a plant’s growth.

This type of hypothesis predicts the direction of an effect between variables, i.e., positive or negative.

Example: A high-quality education will result in a greater number of career opportunities.

Similar to the directional hypothesis, this type of hypothesis predicts the nature of the effect but not the direction that effect will go in.

Example: A high-quality education will affect the number of available career opportunities.

How to Write a Hypothesis : A STEP-BY-STEP GUIDE

  • Ask a Question

The starting point for any hypothesis is asking a question. This is often called the research question . The research question is the student’s jumping-off point to developing their hypothesis. This question should be specific and answerable. The hypothesis will be the point where the research question is transformed into a declarative statement.

Ideally, the questions the students develop should be relational, i.e., they should look at how two or more variables relate to each other as described above. For example, what effect does sunlight have on the growth rate of lettuce?

  • Research the Question

The research is an essential part of the process of developing a hypothesis. Students will need to examine the ideas and studies that are out there on the topic already. By examining the literature already out there on their topic, they can begin to refine their questions on the subject and begin to form predictions based on their studies.

Remember, a hypothesis can be defined as an ‘educated’ guess. This is the part of the process where the student educates themself on the subject before making their ‘guess.’

  • Define Your Variables

By now, your students should be ready to form their preliminary hypotheses. To do this, they should first focus on defining their independent and dependent variables. Now may be an excellent opportunity to remind students that the independent variables are the only variables that they have complete control over, while dependent variables are what is tested or measured.

  • Develop Your Preliminary Hypotheses

With variables defined, students can now work on a draft of their hypothesis. To do this, they can begin by examining their variables and the available data and then making a statement about the relationship between these variables. Students must brainstorm and reflect on what they expect to happen in their investigation before making a prediction upon which to base their hypothesis. It’s worth noting, too, that hypotheses are typically, though not exclusively, written in the present tense.

Students revisit the different types of hypotheses described earlier in this article. Students select three types of hypotheses and frame their preliminary hypotheses according to each criteria. Which works best? Which type is the least suitable for the student’s hypothesis?

  • Finalize the Phrasing

By now, students will have made a decision on which type of hypothesis suits their needs best, and it will now be time to finalize the wording of their hypotheses. There are various ways that students can choose to frame their hypothesis, but below, we will examine the three most common ways.

The If/Then Phrasing

This is the most common type of hypothesis and perhaps the easiest to write for students. It follows a simple ‘ If x, then y ’ formula that makes a prediction that forms the basis of a subsequent investigation.

If I eat more calories, then I will gain weight.

Correlation Phrasing

Another way to phrase a hypothesis is to focus on the correlation between the variables. This typically takes the form of a statement that defines that relationship positively or negatively.

The more calories that are eaten beyond the daily recommended requirements, the greater the weight gain will be.

Comparison Phrasing

This form of phrasing is applicable when comparing two groups and focuses on the differences that the investigation is expected to reveal between those two groups.

Those who eat more calories will gain more weight than those who eat fewer calories.

Questions to ask during this process include:

  • What tense is the hypothesis written in?
  • Does the hypothesis contain both independent and dependent variables?
  • Is the hypothesis framed using the if/then, correlation, or comparison framework (or other similar suitable structure)?
  • Is the hypothesis worded clearly and concisely?
  • Does the hypothesis make a prediction?
  • Is the prediction specific?
  • Is the hypothesis testable?
  • Gather Data to Support/Disprove Your Hypothesis

If the purpose of a hypothesis is to provide a reason to pursue an investigation, then the student will need to gather related information together to fuel that investigation.

While, by definition, a hypothesis leans towards a specific outcome, the student shouldn’t worry if their investigations or experiments ultimately disprove their hypothesis. The hypothesis is the starting point; the destination is not preordained. This is the very essence of the scientific method. Students should trust the results of their investigation to speak for themselves. Either way, the outcome is valuable information.

TOP 10 TIPS FOR WRITING A STRONG HYPOTHESIS

  • Begin by asking a clear and compelling question. Your hypothesis is a response to the inquiry you are eager to explore.
  • Keep it simple and straightforward. Avoid using complex phrases or making multiple predictions in one hypothesis.
  • Use the right format. A strong hypothesis is often written in the form of an “if-then” statement.
  • Ensure that your hypothesis is testable. Your hypothesis should be something that can be verified through experimentation or observation.
  • Stay objective. Your hypothesis should be based on facts and evidence, not personal opinions or prejudices.
  • Examine different possibilities. Don’t limit yourself to just one hypothesis. Consider alternative explanations for your observations.
  • Stay open to the possibility of being wrong. Your hypothesis is just a prediction, and it may not always be correct.
  • Search for evidence to support your hypothesis. Investigate existing literature and gather data that supports your hypothesis.
  • Make sure that your hypothesis is pertinent. Your hypothesis should be relevant to the question you are trying to investigate.
  • Revise your hypothesis as necessary. If new evidence arises that contradicts your hypothesis, you may need to adjust it accordingly.

HYPOTHESIS TEACHING STRATEGIES AND ACTIVITIES

When teaching young scientists and writers, it’s essential to remember that the process of formulating a hypothesis is not always straightforward. It’s easy to make mistakes along the way, but with a bit of guidance, you can ensure your students avoid some of the most common pitfalls like these.

  • Don’t let your students be too vague. Remind them that when formulating a hypothesis, it’s essential to be specific and avoid using overly general language. Make sure their hypothesis is clear and easy to understand.
  • Being swayed by personal biases will impact their hypothesis negatively. It’s important to stay objective when formulating a hypothesis, so avoid letting personal biases or opinions get in the way.
  • Not starting with a clear question is the number one stumbling block for students, so before forming a hypothesis, you need to reinforce the need for a clear understanding of the question they’re trying to answer. Start with a question that is specific and relevant.

Hypothesis Warmup Activity: First, organize students into small working groups of four or five. Then, set each group to collect a list of hypotheses. They can find these by searching on the Internet or finding examples in textbooks . When students have gathered together a suitable list of hypotheses, have them identify the independent and dependent variables in each case. They can underline each of these in different colors.

It may be helpful for students to examine each hypothesis to identify the ‘cause’ elements and the ‘effect’ elements. When students have finished, they can present their findings to the class.

Task 1: Set your students the task of coming up with an investigation-worthy question on a topic that interests them. This activity works particularly well for groups.

Task 2: Students search for existing information and theories on their topic on the Internet or in the library. They should take notes where necessary and begin to form an assumption or prediction based on their reading and research that they can investigate further.

Task 3: When working with a talking partner, can students identify which of their partner’s independent and dependent variables? If not, then one partner will need to revisit the definitions for the two types of variables as outlined earlier.

Task 4: Organize students into smaller groups and task them with presenting their hypotheses to each other. Students can then provide feedback before the final wording of each hypothesis is finalized.

Procedural Writing Unit

Perhaps due to their short length, learning how to create a well-written hypothesis is not typically afforded much time in the curriculum.

However, though they are brief in length, they are complex enough to warrant focused learning and practice in class, particularly given their importance across many curriculum areas.

Learning how to write a hypothesis works well as a standalone writing skill. It can also form part of a more comprehensive academic or scientific writing study that focuses on how to write a research question, develop a theory, etc.

As with any text type, practice improves performance. By following the processes outlined above, students will be well on their way to writing their own hypotheses competently in no time.

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How to Write a Research Hypothesis: Good & Bad Examples

how to remember the word hypothesis

What is a research hypothesis?

A research hypothesis is an attempt at explaining a phenomenon or the relationships between phenomena/variables in the real world. Hypotheses are sometimes called “educated guesses”, but they are in fact (or let’s say they should be) based on previous observations, existing theories, scientific evidence, and logic. A research hypothesis is also not a prediction—rather, predictions are ( should be) based on clearly formulated hypotheses. For example, “We tested the hypothesis that KLF2 knockout mice would show deficiencies in heart development” is an assumption or prediction, not a hypothesis. 

The research hypothesis at the basis of this prediction is “the product of the KLF2 gene is involved in the development of the cardiovascular system in mice”—and this hypothesis is probably (hopefully) based on a clear observation, such as that mice with low levels of Kruppel-like factor 2 (which KLF2 codes for) seem to have heart problems. From this hypothesis, you can derive the idea that a mouse in which this particular gene does not function cannot develop a normal cardiovascular system, and then make the prediction that we started with. 

What is the difference between a hypothesis and a prediction?

You might think that these are very subtle differences, and you will certainly come across many publications that do not contain an actual hypothesis or do not make these distinctions correctly. But considering that the formulation and testing of hypotheses is an integral part of the scientific method, it is good to be aware of the concepts underlying this approach. The two hallmarks of a scientific hypothesis are falsifiability (an evaluation standard that was introduced by the philosopher of science Karl Popper in 1934) and testability —if you cannot use experiments or data to decide whether an idea is true or false, then it is not a hypothesis (or at least a very bad one).

So, in a nutshell, you (1) look at existing evidence/theories, (2) come up with a hypothesis, (3) make a prediction that allows you to (4) design an experiment or data analysis to test it, and (5) come to a conclusion. Of course, not all studies have hypotheses (there is also exploratory or hypothesis-generating research), and you do not necessarily have to state your hypothesis as such in your paper. 

But for the sake of understanding the principles of the scientific method, let’s first take a closer look at the different types of hypotheses that research articles refer to and then give you a step-by-step guide for how to formulate a strong hypothesis for your own paper.

Types of Research Hypotheses

Hypotheses can be simple , which means they describe the relationship between one single independent variable (the one you observe variations in or plan to manipulate) and one single dependent variable (the one you expect to be affected by the variations/manipulation). If there are more variables on either side, you are dealing with a complex hypothesis. You can also distinguish hypotheses according to the kind of relationship between the variables you are interested in (e.g., causal or associative ). But apart from these variations, we are usually interested in what is called the “alternative hypothesis” and, in contrast to that, the “null hypothesis”. If you think these two should be listed the other way round, then you are right, logically speaking—the alternative should surely come second. However, since this is the hypothesis we (as researchers) are usually interested in, let’s start from there.

Alternative Hypothesis

If you predict a relationship between two variables in your study, then the research hypothesis that you formulate to describe that relationship is your alternative hypothesis (usually H1 in statistical terms). The goal of your hypothesis testing is thus to demonstrate that there is sufficient evidence that supports the alternative hypothesis, rather than evidence for the possibility that there is no such relationship. The alternative hypothesis is usually the research hypothesis of a study and is based on the literature, previous observations, and widely known theories. 

Null Hypothesis

The hypothesis that describes the other possible outcome, that is, that your variables are not related, is the null hypothesis ( H0 ). Based on your findings, you choose between the two hypotheses—usually that means that if your prediction was correct, you reject the null hypothesis and accept the alternative. Make sure, however, that you are not getting lost at this step of the thinking process: If your prediction is that there will be no difference or change, then you are trying to find support for the null hypothesis and reject H1. 

Directional Hypothesis

While the null hypothesis is obviously “static”, the alternative hypothesis can specify a direction for the observed relationship between variables—for example, that mice with higher expression levels of a certain protein are more active than those with lower levels. This is then called a one-tailed hypothesis. 

Another example for a directional one-tailed alternative hypothesis would be that 

H1: Attending private classes before important exams has a positive effect on performance. 

Your null hypothesis would then be that

H0: Attending private classes before important exams has no/a negative effect on performance.

Nondirectional Hypothesis

A nondirectional hypothesis does not specify the direction of the potentially observed effect, only that there is a relationship between the studied variables—this is called a two-tailed hypothesis. For instance, if you are studying a new drug that has shown some effects on pathways involved in a certain condition (e.g., anxiety) in vitro in the lab, but you can’t say for sure whether it will have the same effects in an animal model or maybe induce other/side effects that you can’t predict and potentially increase anxiety levels instead, you could state the two hypotheses like this:

H1: The only lab-tested drug (somehow) affects anxiety levels in an anxiety mouse model.

You then test this nondirectional alternative hypothesis against the null hypothesis:

H0: The only lab-tested drug has no effect on anxiety levels in an anxiety mouse model.

hypothesis in a research paper

How to Write a Hypothesis for a Research Paper

Now that we understand the important distinctions between different kinds of research hypotheses, let’s look at a simple process of how to write a hypothesis.

Writing a Hypothesis Step:1

Ask a question, based on earlier research. Research always starts with a question, but one that takes into account what is already known about a topic or phenomenon. For example, if you are interested in whether people who have pets are happier than those who don’t, do a literature search and find out what has already been demonstrated. You will probably realize that yes, there is quite a bit of research that shows a relationship between happiness and owning a pet—and even studies that show that owning a dog is more beneficial than owning a cat ! Let’s say you are so intrigued by this finding that you wonder: 

What is it that makes dog owners even happier than cat owners? 

Let’s move on to Step 2 and find an answer to that question.

Writing a Hypothesis Step 2:

Formulate a strong hypothesis by answering your own question. Again, you don’t want to make things up, take unicorns into account, or repeat/ignore what has already been done. Looking at the dog-vs-cat papers your literature search returned, you see that most studies are based on self-report questionnaires on personality traits, mental health, and life satisfaction. What you don’t find is any data on actual (mental or physical) health measures, and no experiments. You therefore decide to make a bold claim come up with the carefully thought-through hypothesis that it’s maybe the lifestyle of the dog owners, which includes walking their dog several times per day, engaging in fun and healthy activities such as agility competitions, and taking them on trips, that gives them that extra boost in happiness. You could therefore answer your question in the following way:

Dog owners are happier than cat owners because of the dog-related activities they engage in.

Now you have to verify that your hypothesis fulfills the two requirements we introduced at the beginning of this resource article: falsifiability and testability . If it can’t be wrong and can’t be tested, it’s not a hypothesis. We are lucky, however, because yes, we can test whether owning a dog but not engaging in any of those activities leads to lower levels of happiness or well-being than owning a dog and playing and running around with them or taking them on trips.  

Writing a Hypothesis Step 3:

Make your predictions and define your variables. We have verified that we can test our hypothesis, but now we have to define all the relevant variables, design our experiment or data analysis, and make precise predictions. You could, for example, decide to study dog owners (not surprising at this point), let them fill in questionnaires about their lifestyle as well as their life satisfaction (as other studies did), and then compare two groups of active and inactive dog owners. Alternatively, if you want to go beyond the data that earlier studies produced and analyzed and directly manipulate the activity level of your dog owners to study the effect of that manipulation, you could invite them to your lab, select groups of participants with similar lifestyles, make them change their lifestyle (e.g., couch potato dog owners start agility classes, very active ones have to refrain from any fun activities for a certain period of time) and assess their happiness levels before and after the intervention. In both cases, your independent variable would be “ level of engagement in fun activities with dog” and your dependent variable would be happiness or well-being . 

Examples of a Good and Bad Hypothesis

Let’s look at a few examples of good and bad hypotheses to get you started.

Good Hypothesis Examples

Bad hypothesis examples, tips for writing a research hypothesis.

If you understood the distinction between a hypothesis and a prediction we made at the beginning of this article, then you will have no problem formulating your hypotheses and predictions correctly. To refresh your memory: We have to (1) look at existing evidence, (2) come up with a hypothesis, (3) make a prediction, and (4) design an experiment. For example, you could summarize your dog/happiness study like this:

(1) While research suggests that dog owners are happier than cat owners, there are no reports on what factors drive this difference. (2) We hypothesized that it is the fun activities that many dog owners (but very few cat owners) engage in with their pets that increases their happiness levels. (3) We thus predicted that preventing very active dog owners from engaging in such activities for some time and making very inactive dog owners take up such activities would lead to an increase and decrease in their overall self-ratings of happiness, respectively. (4) To test this, we invited dog owners into our lab, assessed their mental and emotional well-being through questionnaires, and then assigned them to an “active” and an “inactive” group, depending on… 

Note that you use “we hypothesize” only for your hypothesis, not for your experimental prediction, and “would” or “if – then” only for your prediction, not your hypothesis. A hypothesis that states that something “would” affect something else sounds as if you don’t have enough confidence to make a clear statement—in which case you can’t expect your readers to believe in your research either. Write in the present tense, don’t use modal verbs that express varying degrees of certainty (such as may, might, or could ), and remember that you are not drawing a conclusion while trying not to exaggerate but making a clear statement that you then, in a way, try to disprove . And if that happens, that is not something to fear but an important part of the scientific process.

Similarly, don’t use “we hypothesize” when you explain the implications of your research or make predictions in the conclusion section of your manuscript, since these are clearly not hypotheses in the true sense of the word. As we said earlier, you will find that many authors of academic articles do not seem to care too much about these rather subtle distinctions, but thinking very clearly about your own research will not only help you write better but also ensure that even that infamous Reviewer 2 will find fewer reasons to nitpick about your manuscript. 

Perfect Your Manuscript With Professional Editing

Now that you know how to write a strong research hypothesis for your research paper, you might be interested in our free AI proofreader , Wordvice AI, which finds and fixes errors in grammar, punctuation, and word choice in academic texts. Or if you are interested in human proofreading , check out our English editing services , including research paper editing and manuscript editing .

On the Wordvice academic resources website , you can also find many more articles and other resources that can help you with writing the other parts of your research paper , with making a research paper outline before you put everything together, or with writing an effective cover letter once you are ready to submit.

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Formative Assessment Probe

What Is a Hypothesis?

By Page Keeley

Uncovering Student Ideas in Science, Volume 3: Another 25 Formative Assessment Probes

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This is the new updated edition of the first book in the bestselling  Uncovering Student Ideas in Science  series. Like the first edition of volume 1, this book helps pinpoint what your students know (or think they know) so you can monitor their learning and adjust your teaching accordingly. Loaded with classroom-friendly features you can use immediately, the book includes 25 “probes”—brief, easily administered formative assessments designed to understand your students’ thinking about 60 core science concepts.

What Is a Hypothesis?

Access this probe as a Google form:  English

Download this probe as an editable PDF: English

The purpose of this assessment probe is to elicit students’ ideas about hypotheses. The probe is designed to find out if students understand what a hypothesis is, when it is used, and how it is developed.

Type of Probe

Justified List

Related Concepts

hypothesis, nature of science, scientific inquiry, scientific method

Explanation

The best choices are A, B, G, K, L, and M. However, other possible answers open up discussions to contrast with the provided definition. A hypothesis is a tentative explanation that can be tested and is based on observation and/or scientific knowledge such as that that has been gained from doing background research. Hypotheses are used to investigate a scientific question. Hypotheses can be tested through experimentation or further observation, but contrary to how some students are taught to use the “scientific method,” hypotheses are not proved true or correct. Students will often state their conclusions as “My hypothesis is correct because my data prove…,” thereby equating positive results with proof (McLaughlin 2006, p. 61). In essence, experimentation as well as other means of scientific investigation never prove a hypothesis—the hypothesis gains credibility from the evidence obtained from data that support it. Data either support or negate a hypothesis but never prove something to be 100% true or correct.

Hypotheses are often confused with questions. A hypothesis is not framed as a question but rather provides a tentative explanation in response to the scientific question that leads the investigation. Sometimes the word hypothesis is oversimplified by being defined as “an educated guess.” This terminology fails to convey the explanatory or predictive nature of scientific hypotheses and omits what is most important about hypotheses: their purpose. Hypotheses are developed to explain observations, such as notable patterns in nature; predict the outcome of an experiment based on observations or prior scientific knowledge; and guide the investigator in seeking and paying attention to the right data. Calling a hypothesis a “guess” undermines the explanation that underscores a hypothesis.

Predictions and hypotheses are not the same. A hypothesis, which is a tentative explanation, can lead to a prediction. Predictions forecast the outcome of an experiment but do not include an explanation. Predictions often use if-then statements, just as hypotheses do, but this does not make a prediction a hypothesis. For example, a prediction might take the form of, “If I do [X], then [Y] will happen.” The prediction describes the outcome but it does not provide an explanation of why that outcome might result or describe any relationship between variables.

Sometimes the words hypothesis , theory , and law are inaccurately portrayed in science textbooks as a hierarchy of scientific knowledge, with the hypothesis being the first step on the way to becoming a theory and then a law. These concepts do not form a sequence for the development of scientific knowledge because each represents a different type of knowledge.

Not every investigation requires a hypothesis. Some types of investigations do not lend themselves to hypothesis testing through experimentation. A good deal of science is observational and descriptive—the study of biodiversity, for example, usually involves looking at a wide variety of specimens and maybe sketching and recording their unique characteristics. A biologist studying biodiversity might wonder, “What types of birds are found on island X?” The biologist would observe sightings of birds and perhaps sketch them and record their bird calls but would not be guided by a specific hypothesis. Many of the great discoveries in science did not begin with a hypothesis in mind. For example, Charles Darwin did not begin his observations of species in the Galapagos with a hypothesis in mind.

Contrary to the way hypotheses are often stated by students as an unimaginative response to a question posed at the beginning of an experiment, particularly those of the “cookbook” type, the generation of hypotheses by scientists is actually a creative and imaginative process, combined with the logic of scientific thought. “The process of formulating and testing hypotheses is one of the core activities of scientists. To be useful, a hypothesis should suggest what evidence would support it and what evidence would refute it. A hypothesis that cannot in principle be put to the test of evidence may be interesting, but it is not likely to be scientifically useful” (AAAS 1988, p. 5).

Curricular and Instructional Considerations

Elementary Students

In the elementary school grades, students typically engage in inquiry to begin to construct an understanding of the natural world. Their inquiries are initiated by a question. If students have a great deal of knowledge or have made prior observations, they might propose a hypothesis; in most cases, however, their knowledge and observations are too incomplete for them to hypothesize. If elementary school students are required to develop a hypothesis, it is often just a guess, which does little to contribute to an understanding of the purpose of a hypothesis. At this grade level, it is usually sufficient for students to focus on their questions, instead of hypotheses (Pine 1999).

Middle School Students

At the middle school level, students develop an understanding of what a hypothesis is and when one is used. The notion of a testable hypothesis through experimentation that involves variables is introduced and practiced at this grade level. However, there is a danger that students will think every investigation must include a hypothesis. Hypothesizing as a skill is important to develop at this grade level but it is also important to develop the understandings of what a hypothesis is and why and how it is developed.

High School Students

At this level, students have acquired more scientific knowledge and experiences and so are able to propose tentative explanations. They can formulate a testable hypothesis and demonstrate the logical connections between the scientific concepts guiding a hypothesis and the design of an experiment (NRC 1996).

Administering the Probe

This probe is best used as is at the middle school and high school levels, particularly if students have been previously exposed to the word hypothesis or its use. Remove any answer choices students might not be familiar with. For example, if they have not encountered if-then reasoning, eliminate this distracter. The probe can also be modified as a simpler version for students in grades 3–5 by leaving out some of the choices and simplifying the descriptions.

K–4 Understandings About Scientific Inquiry

  • Scientific investigations involve asking and answering a question and comparing the answer with what scientists already know about the world.
  • Scientists develop explanations using observations (evidence) and what they already know about the world (scientific knowledge).

5–8 Understandings About Scientific Inquiry

  • Different kinds of questions suggest different kinds of investigations. Some investigations involve observing and describing objects, organisms, or events; some involve collecting specimens; some involve experiments; some involve seeking more information; some involve discovery of new objects and phenomena; and some involve making models.
  • Current scientific knowledge and understanding guide scientific investigations. Different scientific domains employ different methods, core theories, and standards to advance scientific knowledge and understanding.

5–8 Science as a Human Endeavor

  • Science is very much a human endeavor, and the work of science relies on basic human qualities such as reasoning, insight, energy, skill, and creativity.

9–12 Abilities Necessary to Do Scientific Inquiry

  • Identify questions and concepts that guide scientific investigations.*

9–12 Understandings About Scientific Inquiry

  • Scientists usually inquire about how physical, living, or designed systems function. Conceptual principles and knowledge guide scientific inquiries. Historical and current scientific knowledge influence the design and interpretation of investigations and the evaluation of proposed explanations made by other scientists.

*Indicates a strong match between the ideas elicited by the probe and a national standard’s learning goal.

K–2 Scientific Inquiry

  • People can often learn about things around them by just observing those things carefully, but sometimes they can learn more by doing something to the things and noting what happens.

3–5 Scientific Inquiry

  • Scientists’ explanations about what happens in the world come partly from what they observe and partly from what they think. Sometimes scientists have different explanations for the same set of observations. That usually leads to their making more observations to resolve the differences.

6–8 Scientific Inquiry

  • Scientists differ greatly in what phenomena they study and how they go about their work. Although there is no fixed set of steps that all scientists follow, scientific investigations usually involve the collection of relevant evidence, the use of logical reasoning, and the application of imagination in devising hypotheses and explanations to make sense of the collected evidence.*

6–8 Values and Attitudes

  • Even if they turn out not to be true, hypotheses are valuable if they lead to fruitful investigations.*

9–12 Scientific Inquiry

  • Hypotheses are widely used in science for choosing what data to pay attention to and what additional data to seek and for guiding the interpretation of the data (both new and previously available).*

Related Research

  • Students generally have difficulty with explaining how science is conducted because they have had little contact with real scientists. Their familiarity with doing science, even at older ages, is “school science,” which is often not how science is generally conducted in the scientific community (Driver et al. 1996).
  • Despite over 10 years of reform efforts in science education, research still shows that students typically have inadequate conceptions of what science is and what scientists do (Schwartz 2007).
  • Upper elementary school and middle school students may not understand experimentation as a method of testing ideas, but rather as a method of trying things out or producing a desired outcome (AAAS 1993).
  • Middle school students tend to invoke personal experiences as evidence to justify their hypothesis. They seem to think of evidence as selected from what is already known or from personal experience or secondhand sources, not as information produced through experiment (AAAS 1993).

Related NSTA Resources

American Association for the Advancement of Science (AAAS). 1993. Benchmarks for science literacy. New York: Oxford University Press.

Keeley, P. 2005. Science curriculum topic study: Bridging the gap between standards and practice. Thousand Oaks, CA: Corwin Press.

McLaughlin, J. 2006. A gentle reminder that a hypothesis is never proven correct, nor is a theory ever proven true. Journal of College Science Teaching 36 (1): 60–62.

National Research Council (NRC). 1996. National science education standards. Washington, DC: National Academy Press.

Schwartz, R. 2007. What’s in a word? How word choice can develop (mis)conceptions about the nature of science. Science Scope 31 (2): 42–47.

VanDorn, K., M. Mavita, L. Montes, B. Ackerson, and M. Rockley. 2004. Hypothesis-based learning. Science Scope 27: 24–25.

Suggestions for Instruction and Assessment

  • The “scientific method” is often the first topic students encounter when using textbooks and this can erroneously imply that there is a rigid set of steps that all scientists follow, including the development of a hypothesis. Often the scientific method described in textbooks applies to experimentation, which is only one of many ways scientists conduct their work. Embedding explicit instruction of the various ways to do science in the actual investigations students do throughout the year as well as in their studies of investigations done by scientists is a better approach to understanding how science is done than starting off the year with the scientific method in a way that is devoid of a context through which students can learn the content and process of science.
  • Students often participate in science fairs that may follow a textbook scientific method of posing a question, developing a hypothesis, and so on, that incorrectly results in students “proving” their hypothesis. Make sure students understand that a hypothesis can be disproven, but it is never proven, which implies 100% certainty.
  • Help students understand that science begins with a question. The structure of some school lab reports may lead students to believe that all investigations begin with a hypothesis. While some investigations do begin with a hypothesis, in most cases, they begin with a question. Sometimes it is just a general question.
  • A technique to help students maintain a consistent image of science as inquiry throughout the year by paying more careful attention to the words they use is to create a “caution words” poster or bulletin board (Schwartz 2007). Important words that have specific meanings in science but are often used inappropriately in the science classroom and through everyday language can be posted in the room as a reminder to pay careful attention to how students are using these words. For example, words like hypothesis and scientific method can be posted here. Words that are banned when referring to hypotheses include prove, correct, and true.
  • Use caution when asking students to write lab reports that use the same format regardless of the type of investigation conducted. The format used in writing about an investigation may imply a rigid, fixed process or erroneously misrepresent aspects of science, such as that hypotheses are developed for every scientific investigation.
  • Avoid using hypotheses with younger children when they result in guesses. It is better to start with a question and have students make a prediction about what they think will happen and why. As they acquire more conceptual understanding and experience a variety of observations, they will be better prepared to develop hypotheses that reflect the way science is done.
  • Avoid using “educated guess” as a description for hypothesis. The common meaning of the word guess implies no prior knowledge, experience, or observations.
  • Scaffold hypothesis writing for students by initially having them use words like may in their statements and then formalizing them with if-then statements. For example, students may start with the statement, “The growth of algae may be affected by temperature.” The next step would be to extend this statement to include a testable relationship, such as, “If the temperature of the water increases, then the algae population will increase.” Encourage students to propose a tentative explanation and then consider how they would go about testing the statement.

American Association for the Advancement of Science (AAAS). 1988. Science for all Americans. New York: Oxford University Press.

Driver, R., J. Leach, R. Millar, and P. Scott. 1996. Young people’s images of science. Buckingham, UK: Open University Press.

Pine, J. 1999. To hypothesize or not to hypothesize. In Foundations: A monograph for professionals in science, mathematics, and technology education. Vol. 2. Inquiry: Thoughts, views, and strategies for the K–5 classroom. Arlington, VA: National Science Foundation.

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how to remember the word hypothesis

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How to Write a Hypothesis? Types and Examples 

how to write a hypothesis for research

All research studies involve the use of the scientific method, which is a mathematical and experimental technique used to conduct experiments by developing and testing a hypothesis or a prediction about an outcome. Simply put, a hypothesis is a suggested solution to a problem. It includes elements that are expressed in terms of relationships with each other to explain a condition or an assumption that hasn’t been verified using facts. 1 The typical steps in a scientific method include developing such a hypothesis, testing it through various methods, and then modifying it based on the outcomes of the experiments.  

A research hypothesis can be defined as a specific, testable prediction about the anticipated results of a study. 2 Hypotheses help guide the research process and supplement the aim of the study. After several rounds of testing, hypotheses can help develop scientific theories. 3 Hypotheses are often written as if-then statements. 

Here are two hypothesis examples: 

Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth. 4  

If a company offers flexible work hours, then their employees will be happier at work. 5  

Table of Contents

  • What is a hypothesis? 
  • Types of hypotheses 
  • Characteristics of a hypothesis 
  • Functions of a hypothesis 
  • How to write a hypothesis 
  • Hypothesis examples 
  • Frequently asked questions 

What is a hypothesis?

Figure 1. Steps in research design

A hypothesis expresses an expected relationship between variables in a study and is developed before conducting any research. Hypotheses are not opinions but rather are expected relationships based on facts and observations. They help support scientific research and expand existing knowledge. An incorrectly formulated hypothesis can affect the entire experiment leading to errors in the results so it’s important to know how to formulate a hypothesis and develop it carefully.

A few sources of a hypothesis include observations from prior studies, current research and experiences, competitors, scientific theories, and general conditions that can influence people. Figure 1 depicts the different steps in a research design and shows where exactly in the process a hypothesis is developed. 4  

There are seven different types of hypotheses—simple, complex, directional, nondirectional, associative and causal, null, and alternative. 

Types of hypotheses

The seven types of hypotheses are listed below: 5 , 6,7  

  • Simple : Predicts the relationship between a single dependent variable and a single independent variable. 

Example: Exercising in the morning every day will increase your productivity.  

  • Complex : Predicts the relationship between two or more variables. 

Example: Spending three hours or more on social media daily will negatively affect children’s mental health and productivity, more than that of adults.  

  • Directional : Specifies the expected direction to be followed and uses terms like increase, decrease, positive, negative, more, or less. 

Example: The inclusion of intervention X decreases infant mortality compared to the original treatment.  

  • Non-directional : Does not predict the exact direction, nature, or magnitude of the relationship between two variables but rather states the existence of a relationship. This hypothesis may be used when there is no underlying theory or if findings contradict prior research. 

Example: Cats and dogs differ in the amount of affection they express.  

  • Associative and causal : An associative hypothesis suggests an interdependency between variables, that is, how a change in one variable changes the other.  

Example: There is a positive association between physical activity levels and overall health.  

A causal hypothesis, on the other hand, expresses a cause-and-effect association between variables. 

Example: Long-term alcohol use causes liver damage.  

  • Null : Claims that the original hypothesis is false by showing that there is no relationship between the variables. 

Example: Sleep duration does not have any effect on productivity.  

  • Alternative : States the opposite of the null hypothesis, that is, a relationship exists between two variables. 

Example: Sleep duration affects productivity.  

how to remember the word hypothesis

Characteristics of a hypothesis

So, what makes a good hypothesis? Here are some important characteristics of a hypothesis. 8,9  

  • Testable : You must be able to test the hypothesis using scientific methods to either accept or reject the prediction. 
  • Falsifiable : It should be possible to collect data that reject rather than support the hypothesis. 
  • Logical : Hypotheses shouldn’t be a random guess but rather should be based on previous theories, observations, prior research, and logical reasoning. 
  • Positive : The hypothesis statement about the existence of an association should be positive, that is, it should not suggest that an association does not exist. Therefore, the language used and knowing how to phrase a hypothesis is very important. 
  • Clear and accurate : The language used should be easily comprehensible and use correct terminology. 
  • Relevant : The hypothesis should be relevant and specific to the research question. 
  • Structure : Should include all the elements that make a good hypothesis: variables, relationship, and outcome. 

Functions of a hypothesis

The following list mentions some important functions of a hypothesis: 1  

  • Maintains the direction and progress of the research. 
  • Expresses the important assumptions underlying the proposition in a single statement. 
  • Establishes a suitable context for researchers to begin their investigation and for readers who are referring to the final report. 
  • Provides an explanation for the occurrence of a specific phenomenon. 
  • Ensures selection of appropriate and accurate facts necessary and relevant to the research subject. 

To summarize, a hypothesis provides the conceptual elements that complete the known data, conceptual relationships that systematize unordered elements, and conceptual meanings and interpretations that explain the unknown phenomena. 1  

how to remember the word hypothesis

How to write a hypothesis

Listed below are the main steps explaining how to write a hypothesis. 2,4,5  

  • Make an observation and identify variables : Observe the subject in question and try to recognize a pattern or a relationship between the variables involved. This step provides essential background information to begin your research.  

For example, if you notice that an office’s vending machine frequently runs out of a specific snack, you may predict that more people in the office choose that snack over another. 

  • Identify the main research question : After identifying a subject and recognizing a pattern, the next step is to ask a question that your hypothesis will answer.  

For example, after observing employees’ break times at work, you could ask “why do more employees take breaks in the morning rather than in the afternoon?” 

  • Conduct some preliminary research to ensure originality and novelty : Your initial answer, which is your hypothesis, to the question is based on some pre-existing information about the subject. However, to ensure that your hypothesis has not been asked before or that it has been asked but rejected by other researchers you would need to gather additional information.  

For example, based on your observations you might state a hypothesis that employees work more efficiently when the air conditioning in the office is set at a lower temperature. However, during your preliminary research you find that this hypothesis was proven incorrect by a prior study. 

  • Develop a general statement : After your preliminary research has confirmed the originality of your proposed answer, draft a general statement that includes all variables, subjects, and predicted outcome. The statement could be if/then or declarative.  
  • Finalize the hypothesis statement : Use the PICOT model, which clarifies how to word a hypothesis effectively, when finalizing the statement. This model lists the important components required to write a hypothesis. 

P opulation: The specific group or individual who is the main subject of the research 

I nterest: The main concern of the study/research question 

C omparison: The main alternative group 

O utcome: The expected results  

T ime: Duration of the experiment 

Once you’ve finalized your hypothesis statement you would need to conduct experiments to test whether the hypothesis is true or false. 

Hypothesis examples

The following table provides examples of different types of hypotheses. 10 ,11  

how to remember the word hypothesis

Key takeaways  

Here’s a summary of all the key points discussed in this article about how to write a hypothesis. 

  • A hypothesis is an assumption about an association between variables made based on limited evidence, which should be tested. 
  • A hypothesis has four parts—the research question, independent variable, dependent variable, and the proposed relationship between the variables.   
  • The statement should be clear, concise, testable, logical, and falsifiable. 
  • There are seven types of hypotheses—simple, complex, directional, non-directional, associative and causal, null, and alternative. 
  • A hypothesis provides a focus and direction for the research to progress. 
  • A hypothesis plays an important role in the scientific method by helping to create an appropriate experimental design. 

Frequently asked questions

Hypotheses and research questions have different objectives and structure. The following table lists some major differences between the two. 9  

Here are a few examples to differentiate between a research question and hypothesis. 

Yes, here’s a simple checklist to help you gauge the effectiveness of your hypothesis. 9   1. When writing a hypothesis statement, check if it:  2. Predicts the relationship between the stated variables and the expected outcome.  3. Uses simple and concise language and is not wordy.  4. Does not assume readers’ knowledge about the subject.  5. Has observable, falsifiable, and testable results. 

As mentioned earlier in this article, a hypothesis is an assumption or prediction about an association between variables based on observations and simple evidence. These statements are usually generic. Research objectives, on the other hand, are more specific and dictated by hypotheses. The same hypothesis can be tested using different methods and the research objectives could be different in each case.     For example, Louis Pasteur observed that food lasts longer at higher altitudes, reasoned that it could be because the air at higher altitudes is cleaner (with fewer or no germs), and tested the hypothesis by exposing food to air cleaned in the laboratory. 12 Thus, a hypothesis is predictive—if the reasoning is correct, X will lead to Y—and research objectives are developed to test these predictions. 

Null hypothesis testing is a method to decide between two assumptions or predictions between variables (null and alternative hypotheses) in a statistical relationship in a sample. The null hypothesis, denoted as H 0 , claims that no relationship exists between variables in a population and any relationship in the sample reflects a sampling error or occurrence by chance. The alternative hypothesis, denoted as H 1 , claims that there is a relationship in the population. In every study, researchers need to decide whether the relationship in a sample occurred by chance or reflects a relationship in the population. This is done by hypothesis testing using the following steps: 13   1. Assume that the null hypothesis is true.  2. Determine how likely the sample relationship would be if the null hypothesis were true. This probability is called the p value.  3. If the sample relationship would be extremely unlikely, reject the null hypothesis and accept the alternative hypothesis. If the relationship would not be unlikely, accept the null hypothesis. 

how to remember the word hypothesis

To summarize, researchers should know how to write a good hypothesis to ensure that their research progresses in the required direction. A hypothesis is a testable prediction about any behavior or relationship between variables, usually based on facts and observation, and states an expected outcome.  

We hope this article has provided you with essential insight into the different types of hypotheses and their functions so that you can use them appropriately in your next research project. 

References  

  • Dalen, DVV. The function of hypotheses in research. Proquest website. Accessed April 8, 2024. https://www.proquest.com/docview/1437933010?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals&imgSeq=1  
  • McLeod S. Research hypothesis in psychology: Types & examples. SimplyPsychology website. Updated December 13, 2023. Accessed April 9, 2024. https://www.simplypsychology.org/what-is-a-hypotheses.html  
  • Scientific method. Britannica website. Updated March 14, 2024. Accessed April 9, 2024. https://www.britannica.com/science/scientific-method  
  • The hypothesis in science writing. Accessed April 10, 2024. https://berks.psu.edu/sites/berks/files/campus/HypothesisHandout_Final.pdf  
  • How to develop a hypothesis (with elements, types, and examples). Indeed.com website. Updated February 3, 2023. Accessed April 10, 2024. https://www.indeed.com/career-advice/career-development/how-to-write-a-hypothesis  
  • Types of research hypotheses. Excelsior online writing lab. Accessed April 11, 2024. https://owl.excelsior.edu/research/research-hypotheses/types-of-research-hypotheses/  
  • What is a research hypothesis: how to write it, types, and examples. Researcher.life website. Published February 8, 2023. Accessed April 11, 2024. https://researcher.life/blog/article/how-to-write-a-research-hypothesis-definition-types-examples/  
  • Developing a hypothesis. Pressbooks website. Accessed April 12, 2024. https://opentext.wsu.edu/carriecuttler/chapter/developing-a-hypothesis/  
  • What is and how to write a good hypothesis in research. Elsevier author services website. Accessed April 12, 2024. https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/what-how-write-good-hypothesis-research/  
  • How to write a great hypothesis. Verywellmind website. Updated March 12, 2023. Accessed April 13, 2024. https://www.verywellmind.com/what-is-a-hypothesis-2795239  
  • 15 Hypothesis examples. Helpfulprofessor.com Published September 8, 2023. Accessed March 14, 2024. https://helpfulprofessor.com/hypothesis-examples/ 
  • Editage insights. What is the interconnectivity between research objectives and hypothesis? Published February 24, 2021. Accessed April 13, 2024. https://www.editage.com/insights/what-is-the-interconnectivity-between-research-objectives-and-hypothesis  
  • Understanding null hypothesis testing. BCCampus open publishing. Accessed April 16, 2024. https://opentextbc.ca/researchmethods/chapter/understanding-null-hypothesis-testing/#:~:text=In%20null%20hypothesis%20testing%2C%20this,said%20to%20be%20statistically%20significant  

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A Simple DIY Short-Term Memory Experiment

Test Your Memory With Lists of Words

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

how to remember the word hypothesis

Amanda Tust is a fact-checker, researcher, and writer with a Master of Science in Journalism from Northwestern University's Medill School of Journalism.

how to remember the word hypothesis

Muharrem Oner / Getty Images

Short-term memory is the part of memory that stores a limited amount of information for a short amount of time. It's brief (about 20 to 30 seconds), and you can only remember so much information (such as a five to nine-word list).

If you want to see for yourself just how short your short-term memory really is, try memorizing some of the word lists below. It can be a great way to learn more about your own limits and can even be an excellent exercise for boosting your memory powers.

At a Glance

Short-term memory experiments often involve memorizing a list of words and then trying to remember them. Most people can hold five to nine words in short-term memory, but your own abilities may vary. You can learn more by using some of the memory test words below. If your results leave something to be desired, performing similar memory challenges may help you gradually boost your abilities.

Test Your Memory With Word Lists

This quick short-term memory test is a simple psychology experiment you can try at home. You can do this experiment on your own or with a small group of volunteers. By seeing how many words you can memorize in a brief period of time, you can learn more about both the capacity and duration of short-term memory .

Look at the list of words below for two minutes. Memorize as many words as you can in this amount of time. Next, get out a sheet of paper. Without looking at the list, give yourself two minutes to write down as many words from the list as you can.

How many words did you get correct? Despite having two minutes to memorize the words, you may have found it surprisingly difficult to recall even a handful of words.

This experiment demonstrates some of the limitations of short-term memory. According to researcher George A. Miller, the typical storage capacity for short-term memory is seven, plus or minus two items.

Try Chunking to Remember More

While short-term memory capacity is limited, some strategies may help improve it a bit. Memory rehearsal strategies, such as chunking , can significantly increase memorization and recall.

Because these items can be easily grouped based on category, you can probably remember far more of these words. Clustering can be a useful memorization strategy that can improve the retention and recall of information.  

Perform Your Own Word Memorization Experiment

There are a number of different approaches you could take in conducting your own word memorization experiment.

  • Compare random words versus related words . Create two lists of words: One that is completely random and another that has groups of related words. Ask participants to first complete one trial with the random words, and then complete another trial with the related words. Compare the results of the two trials.
  • Compare results between male and female participants . Have a group of participants perform the memorization activity, and then compare how many words the male participants remembered on average to how many the female participants remembered.
  • Try the experiment with gender-associated terms versus gender-neutral terms . Create a list of terms related to objects or concepts commonly associated with women or men. Then create a list of neutral terms. Administer both tests to a group and compare the results between the men and women. Did women or men find it easier to remember the gender-associated terms? Or were the results insignificant?
  • Compare results among different age groups . For example, create a group of school-age children, a group of college students, a group of middle-aged adults, and a group of older adults. Give the same test to each participant and then compare the results of each group. Which group performed the best? Which one performed the worst? What do these results have to say about memory and age?

Key Questions for Background Research

  • On average, how many words can a person remember?
  • Can other factors such as gender and age have an impact on memory?
  • Do people tend to remember certain words more than others?
  • What strategies might improve memorization?

When you are exploring  psychology experiment ideas , be sure to understand how to conduct a psychology experiment  to get accurate results and to perform experiments ethically.

Factors That Impact Performance on Word Lists

How well you do at recalling words on a memorization list depends on a variety of factors. Some issues that can affect your performance on memorization lists include things such as:

  • Side effects of medications
  • Sleep deprivation
  • Substance use

Another issue that might play a role is the serial position effect. It involves a tendency to recall words at the beginning or end of a list while having difficulty remembering those in the middle.

Better recall for words at the beginning of a list is known as the primacy effect , and better recall for those at the end of a list is the recency effect .

How to Improve Your Short-Term Memory

If you'd like to strengthen your memory, some strategies can help you boost your memorization powers.

  • Brain training : Some research has found that cognitive training can help slow brain aging and sharpen your mental skills, including short-term memory. Practicing memorizing word lists on your own is one strategy, but there are also many online brain games and apps that can be helpful.
  • Healthy habits : The Alzheimer's Association suggests that strategies such as regular exercise, avoiding smoking, eating a balanced diet, and getting enough rest are crucial for protecting brain health and memory.
  • Try mnemonics : Songs, rhymes, and acronyms are examples of memory devices that can help you remember things more effectively. For example, when you are memorizing a list of words, you might try singing the list to the tune of a familiar melody. Some research suggests that using such tools can boost your memory by as much as 20%!
  • Manage your stress : Chronic stress can take a serious toll on your health and mental well-being, but it can also worsen your memory and concentration. That's why it's so crucial to find ways to minimize and manage stress effectively. Self-care can help, as can using stress management techniques like deep breathing and meditation.
  • Consider herbal memory boosters : Certain herbs purportedly have memory benefits and other positive effects on brain health. Sage, ginseng, and lemon balm are a few that may have a positive impact on memory.

Always check with your doctor before trying any herbal supplement or remedy.

When to Get Help

Less than stellar performance on a memory word list isn't necessarily a reason for concern. It might mean you are distracted, tired, or have difficulty concentrating. If you are noticing other problems with your memory, however, it is essential to discuss your concerns with your doctor.

Your doctor can evaluate your symptoms to determine if a medical or mental health condition might be affecting your memory.

Mental conditions such as depression can lead to problems with memory and concentration. Medical conditions affecting memory include mild cognitive impairment, dementia, Alzheimer's disease , infections, and medication side effects.

Kelley P, Evans MDR, Kelley J.  Making memories: Why time matters .  Front Hum Neurosci . 2018;12:400. doi:10.3389/fnhum.2018.00400

Von Bastian CC, Oberauer K. Effects and mechanisms of working memory training: A review . Psychol Res . 2013;78(6):803-820. doi:10.1007/s00426-013-0524-6

National Institute on Aging.  Do memory problems always mean Alzheimer's disease ?

Gicas KM, Honer WG, Wilson RS, et al. Association of serial position scores on memory tests and hippocampal-related neuropathologic outcomes .  Neurology . 2020;95(24):e3303-e3312. doi:10.1212/WNL.0000000000010952

Hampshire A, Sandrone S, Hellyer PJ.  A large-scale, cross-sectional investigation into the efficacy of brain training .  Front Hum Neurosci . 2019;13:221. doi:10.3389/fnhum.2019.00221

Alzheimer's Association. 10 ways to love your brain .

Knott D, Thaut MH.  Musical mnemonics enhance verbal memory in typically developing children .  Front Educ . 2018;3. doi:10.3389/feduc.2018.00031

Yaribeygi H, Panahi Y, Sahraei H, Johnston TP, Sahebkar A. The impact of stress on body function: A review .  EXCLI J . 2017;16:1057-1072. doi:10.17179/excli2017-480

National Institute on Aging. Memory, forgetfulness, and aging: What's normal and what's not ?

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

ScienceDaily

How does 'not' affect what we understand? Scientists find negation mitigates our interpretation of phrases

New study shows how the brain builds new meanings through word combinations.

When we're told "This coffee is hot" upon being served a familiar caffeinated beverage at our local diner or cafe, the message is clear. But what about when we're told "This coffee is not hot"? Does that mean we think it's cold ? Or room temperature? Or just warm?

A team of scientists has now identified how our brains work to process phrases that include negation (i.e., "not"), revealing that it mitigates rather than inverts meaning -- in other words, in our minds, negation merely reduces the temperature of our coffee and does not make it "cold."

"We now have a firmer sense of how negation operates as we try to make sense of the phrases we process," explains Arianna Zuanazzi, a postdoctoral fellow in New York University's Department of Psychology at the time of the study and the lead author of the paper, which appears in the journal PLOS Biology . "In identifying that negation serves as a mitigator of adjectives -- 'bad' or 'good,' 'sad' or 'happy,' and 'cold' or 'hot' -- we also have a better understanding of how the brain functions to interpret subtle changes in meaning."

In an array of communications, ranging from advertising to legal filings, negation is often used intentionally to mask a clear understanding of a phrase. In addition, large language models in AI tools have difficulty interpreting passages containing negation. The researchers say that their results show how humans process such phrases while also potentially pointing to ways to understand and improve AI functionality.

While the ability of human language to generate novel or complex meanings through the combination of words has long been known, how this process occurs is not well understood.

To address this, Zuanazzi and her colleagues conducted a series of experiments to measure how participants interpreted phrases and also monitored participants' brain activity during these tasks -- in order to precisely gauge related neurological function.

In the experiments, participants read -- on a computer monitor -- adjective phrases with and without negation (e.g., "really not good" and "really really good") and rated their meaning on a scale from 1 ("really really bad") to 10 ("really really good") using a mouse cursor. This scale was designed, in part, to determine if participants interpreted phrases with negation as the opposite of those without negation -- in other words, did they interpret "really not good" as "bad" -- or, instead, as something more measured?

Here, the researchers found that participants took longer to interpret phrases with negation than they did phrases without negation -- indicating, not surprisingly given the greater complexity, that negation slows down our processing of meaning. In addition, drawing from how the participants moved their cursors, negated phrases were first interpreted as affirmative (i.e., "not hot" was initially interpreted as closer to "hot" than to "cold"), but later shifted to a mitigated meaning, suggesting that, for instance, "not hot" is not interpreted as either "hot" or "cold," but, rather, as something between "hot" and "cold."

The scientists also used magnetoencephalography (MEG) to measure the magnetic fields generated by the electrical activity of participants' brains while they were performing these phrase-interpretation tasks. As with the behavioral experiments, neural representations of polar adjectives such as "cold" and "hot" were made more similar by negation, suggesting that the meaning of "not hot" is interpreted as "less hot" and the meaning of "not cold" as "less cold," becoming less distinguishable. In sum, neural data matched what was observed for the mouse movements in the behavioral experiments: negation does not invert the meaning of "hot" to "cold," but rather weakens or mitigates its representation along the semantic continuum between "cold" and "hot."

"This research spotlights the complexity that goes into language comprehension, showing that this cognitive process goes above and beyond the sum of the processing of individual word meanings," observes Zuanazzi, now at the Child Mind Institute.

The paper's other authors were: Pablo Ripollés, an assistant professor in NYU's Department of Psychology and associate director of Music and Audio Research Laboratory at NYU's Steinhardt School of Culture, Education, and Human Development; Jean-Rémi King, a researcher at France's École Normale Supérieure; Wy Ming Lin, a doctoral student at the University of Tübingen; Laura Gwilliams, an NYU doctoral student at the time of the study; and David Poeppel, a professor in NYU's Department of Psychology and managing director of the Ernst Strüngmann Institute for Neuroscience in Frankfurt, Germany.

The research was supported by a grant from the National Science Foundation (2043717).

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Story Source:

Materials provided by New York University . Original written by James Devitt. Note: Content may be edited for style and length.

Journal Reference :

  • Arianna Zuanazzi, Pablo Ripollés, Wy Ming Lin, Laura Gwilliams, Jean-Rémi King, David Poeppel. Negation mitigates rather than inverts the neural representations of adjectives . PLOS Biology , 2024; 22 (5): e3002622 DOI: 10.1371/journal.pbio.3002622

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Faculty & Research | 6.5.2024

Simple Headlines Are Better

Harvard analysis reveals that online readers tend to avoid complexity..

Five people, viewed from behind, are standing in front of a large, wall-mounted laptop screen displaying the text 'READ THIS' in a large, white font on a black background.

In both lab-controlled experiments and real-world trials, headlines that used common words with fewer syllables attracted more reader engagement. | MONTAGE ILLUSTRATION BY NIKO YAITANES /HARVARD MAGAZINE ; IMAGES BY UNSPLASH

A study released today has found empirical evidence behind an old rule for effective writing—the simpler, the better. Weatherhead professor of public policy Todd Rogers , with fellow researchers Hillary Shulman and David Markowitz, looked at how readers engage with headlines from the Washington Post and Upworthy , a storytelling website. Their analysis confirms that, in a gloomy time for journalism, news agencies eager for clicks—and by extension, subscriptions and advertiser dollars—will need to keep their headlines simple and easy to read.

In both lab-controlled experiments and real-world trials, headlines that used common words with fewer syllables attracted more reader engagement. More analytic and complex headlines got fewer clicks, and some readers didn’t even remember them just minutes after seeing them.

The study, published Wednesday in Science Advances , reminds journalists that, in a competitive online news environment where the next possible article is just a scroll away. “Readers are economical with their attention,” they write.

To appeal to them, editors must include simplicity as one of many factors that go into writing headlines, which must summarize often complicated articles in just a few words. Rogers, one of the authors, cautioned against trying to make headlines too precise. “When we’re trying to communicate to a busy audience, it’s great to have a neat vocabulary, but better to use simple words,” he said, quoting Mark Twain’s famous advice: “Don’t use a five-dollar word when a fifty-cent word will do.”

Rogers pointed out that many aspects in the education system, from standardized testing to the culture of academia, push students to use more advanced vocabulary in their writing. But that doesn’t fit the news environment, where the impulse for precision has to be checked with the question, “How do readers read?” Rogers said.

The project also found a gap—what it labeled a potentially “consequential blind spot”—between journalists and their readers. In one of the component studies, journalists were found to be an exception to the “simpler-is-better” hypothesis for holding attention. They showed no difference in engagement between simple and complex headlines, and remembered both equally well, “suggesting a disconnect between what journalists think audiences will read and what they actually do,” according to the paper.

Though the differences in reader engagement between simple and complex headlines were small, for outlets with millions of daily readers, even minor changes in the number of clicks can translate into hundreds of thousands more people reading an article.

In order to analyze headline engagement, the researchers were connected to top editors at the Washington Post who gave them access to nearly 20,000 stories—and an internal system they had already set up to measure headline success. According to Rogers, the Post ’s system would initially run two different headlines for stories published online and measure which one performed better. The candidates could be similar or have almost no overlap, and whichever was more successful then became the final headline for the article.

The selection strategy represents a response to news outlets’ “increasingly digital DNA,” Rogers pointed out. During the last decade, legacy publications have overwhelmingly shifted to a “digital-first” format. The shift has forced outlets to compete in the fierce online struggle for users’ attention, but also provided more flexibility in experimenting with innovative media, design, and other engagement strategies like the Post ’s.

From Upworthy , the platform that shares positive news stories, the researchers obtained even more headlines—more than 100,000. They examined the clicks per impression: among those on whose screens it appeared, how many people clicked to read further.

Just last year, Rogers published a book, Writing for Busy Reader s with Harvard colleague Jessica Lasky-Fink, research director of the People Lab at the Bloomberg Center for Cities, drawing on behavioral science to promote effective writing strategies in the digital age.

As inquiry into human behavior and writing practices progresses, there’s more room to explore the specific qualities Rogers, Shulman, and Markowitz used as proxies for simplicity in the study. For example, the debate about when to consider a word “common”—and when to include explanatory words around it—continues to be blurry for journalists and editors. After the January 6 , 2021, insurrection at the U.S. Capitol, many news outlets may have felt the word “insurrection” warranted definition to better orient readers, Rogers pointed out. But three years later, it may have “graduated” to a word that outlets can expect their readers to know. Similar questions surround when and how to identify public figures—deciding whether to include someone’s title, or just their name in a headline, is not an exact science either.

With the results of the study, however, Rogers said journalists now have at least one more aid for crafting their headlines. “When all else is equal, and you are on the fence,” he said, “simpler language is better.”

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IMAGES

  1. 13 Different Types of Hypothesis (2024)

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  2. Research Hypothesis: Definition, Types, Examples and Quick Tips

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  3. How Do You Formulate A Hypothesis? Hypothesis Testing Assignment Help

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  4. How to Write a Hypothesis: The Ultimate Guide with Examples

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  5. How to write a hypothesis in 5 easy steps: (2023)

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  6. How to Write a Strong Hypothesis in 6 Simple Steps

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COMMENTS

  1. How to Write a Strong Hypothesis in 6 Simple Steps

    Learning how to write a hypothesis comes down to knowledge and strategy. So where do you start? Learn how to make your hypothesis strong step-by-step here. ... Remember that your hypothesis needs to be a statement, not a question. It's an idea, proposal or prediction. For example, a research hypothesis is formatted in an if/then statement: ...

  2. How to Write a Strong Hypothesis

    Developing a hypothesis (with example) 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. Example: Research question.

  3. What Is a Hypothesis and How Do I Write One?

    Merriam Webster defines a hypothesis as "an assumption or concession made for the sake of argument.". In other words, a hypothesis is an educated guess. Scientists make a reasonable assumption--or a hypothesis--then design an experiment to test whether it's true or not.

  4. How to Write a Hypothesis w/ Strong Examples

    Simple Hypothesis Examples. Increasing the amount of natural light in a classroom will improve students' test scores. Drinking at least eight glasses of water a day reduces the frequency of headaches in adults. Plant growth is faster when the plant is exposed to music for at least one hour per day.

  5. Hypothesis: Definition, Examples, and Types

    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. It is a preliminary answer to your question that helps guide the research process. Consider a study designed to examine the relationship between sleep deprivation and test ...

  6. How to Write a Strong Hypothesis

    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. If a first-year student starts attending more lectures, then their exam scores will improve.

  7. How to write a hypothesis in 5 steps (with examples)

    Here are the key steps you can take: 1. Make an observation. The first step to forming a useful hypothesis that you can use to conduct research involves observing an event or a phenomenon. Spending some time making an observation allows you to notice certain patterns that may help you develop your research question.

  8. How To Write A Hypotheses

    Identify the variables involved. Formulate a clear and testable prediction. Use specific and measurable terms. Align the hypothesis with the research question. Distinguish between the null hypothesis (no effect) and alternative hypothesis (expected effect). Ensure the hypothesis is falsifiable and subject to empirical testing.

  9. What is and How to Write a Good Hypothesis in Research?

    Remember that a hypothesis is a prediction of the relationship that exists between two or more variables. Your job is to write a hypothesis, and design the research, to "prove" whether or not your prediction is correct. A common pitfall is to use judgments that are subjective and inappropriate for the construction of a hypothesis.

  10. How to Write a Hypothesis [31 Tips

    Tip 11: Review Existing Literature. Previous research offers insights into forming a hypothesis. Conduct a thorough literature review to identify trends and gaps. Use these studies to refine and build upon your hypothesis. Examples: Studies showing a link between screen time and anxiety.

  11. Research Hypothesis: Definition, Types, Examples and Quick Tips

    3. Simple hypothesis. A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, "Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking. 4.

  12. PDF RESEARCH HYPOTHESIS

    Remember that, within the word "hypothesis" is the word "thesis." Your hypothesis is what you propose to "prove" by your research. As a result of your research, you will arrive at a conclusion, a theory, or understanding that will be useful or applicable beyond the research itself. • 3. Avoid judgmental words in your hypothesis.

  13. Define Hypothesis: Unveiling the First Step in Scientific Inquiry

    Remember the Null Hypothesis: Always formulate and account for a null hypothesis—a statement that negates the relationship between variables—for robust results validation. In truth, it takes practice to strike the right balance and formulate a solid, practical hypothesis for your research. With these tips in mind, you're better equipped ...

  14. What is a Research Hypothesis: How to Write it, Types, and Examples

    It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis. 7.

  15. How to Write a Hypothesis 101: A Step-by-Step Guide

    Step 3: Build the Hypothetical Relationship. In understanding how to compose a hypothesis, constructing the relationship between the variables is key. Based on your research question and variables, predict the expected outcome or connection.

  16. How to Write a Hypothesis in 5 Easy Steps:

    Make a prediction. Provide reasons for that prediction. Specifies a relationship between two or more variables. Be testable. Be falsifiable. Be expressed simply and concisely. Serves as the starting point for an investigation, an experiment, or another form of testing.

  17. PDF Step 6 Writing Your Hypotheses

    In writing a hypothesis(es), it is important to remember the purpose and role of the hypothesis in research. A well stated hypothesis demonstrates to others that you as the research have a good understanding of the literature. A hypothesis provides a framework and direction for collecting, analyzing, and interpreting and reporting data.

  18. Hypothesis Testing

    There are 5 main steps in hypothesis testing: State your research hypothesis as a null hypothesis and alternate hypothesis (H o) and (H a or H 1 ). Collect data in a way designed to test the hypothesis. Perform an appropriate statistical test. Decide whether to reject or fail to reject your null hypothesis. Present the findings in your results ...

  19. How to Write a Research Hypothesis: Good & Bad Examples

    Another example for a directional one-tailed alternative hypothesis would be that. H1: Attending private classes before important exams has a positive effect on performance. Your null hypothesis would then be that. H0: Attending private classes before important exams has no/a negative effect on performance.

  20. What Is a Hypothesis?

    A hypothesis, which is a tentative explanation, can lead to a prediction. Predictions forecast the outcome of an experiment but do not include an explanation. Predictions often use if-then statements, just as hypotheses do, but this does not make a prediction a hypothesis. For example, a prediction might take the form of, "If I do [X], then ...

  21. How to Write a Hypothesis? Types and Examples

    Here are two hypothesis examples: Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth.4. If a company offers flexible work hours, then their employees will be happier at work.5.

  22. Word Lists to Test Memory: A DIY Short-Term Memory Experiment

    At a Glance. Short-term memory experiments often involve memorizing a list of words and then trying to remember them. Most people can hold five to nine words in short-term memory, but your own abilities may vary. You can learn more by using some of the memory test words below. If your results leave something to be desired, performing similar ...

  23. How does 'not' affect what we understand? Scientists find negation

    A team of scientists has now identified how our brains work to process phrases that include negation (i.e., "not"), revealing that it mitigates rather than inverts meaning -- in other words, in ...

  24. Simple Headlines Are Better

    In one of the component studies, journalists were found to be an exception to the "simpler-is-better" hypothesis for holding attention. They showed no difference in engagement between simple and complex headlines, and remembered both equally well, "suggesting a disconnect between what journalists think audiences will read and what they ...

  25. Does curiosity make you read more hard news? How about anxiety?

    Or, to be more generous, people consistently overestimate how much they consume just about every kind of "hard" news. When asked on how many days a week they consume political news online, the average answer in the sample was 3.45 days. The average measured in the web browser sample was just 1.09 days. 1 In all, 70% of people overestimated ...