How to Write a Hypothesis
Two Parts:Preparing to Write a HypothesisFormulating Your HypothesisCommunity Q&A
A hypothesis is a description of a pattern in nature or an explanation about some real-world phenomenon that can be tested through observation and experimentation. The most common way a hypothesis is used in scientific research is as a tentative, testable, and falsifiable statement that explains some observed phenomenon in nature.ok ok We more specifically call this kind of statement an explanatory hypothesis. However, a hypothesis can also be a statement that describes an observed pattern in nature. In this case we call the statement a generalizing hypothesis. Hypotheses can generate predictions: statements that propose that one variable will drive some effect on or change in another variable in the result of a controlled experiment. However, many science resources promote the myth that a hypothesis is simply an educated guess and no different from a prediction. More on this misunderstanding below.
Many academic fields, from the physical sciences to the life sciences to the social sciences, use hypothesis testing as a means of testing ideas to learn about the world and advance scientific knowledge. Whether you are a beginning scholar or a beginning student taking a class in a science subject, understanding what hypotheses are and being able to generate hypotheses and predictions yourself is very important. These instructions will help get you started.
Part 1Preparing to Write a Hypothesis
1Select a topic. Pick a topic that interests you, and that you think it would be good to know more about.
- If you are writing a hypothesis for a school assignment, this step may be taken care of for you.
2Read existing research. Gather all the information you can about the topic you've selected. You'll need to become an expert on the subject and develop a good grasp of what is already known about the topic.
- Focus on academic and scholarly writing. You need to be certain that your information is unbiased, accurate, and comprehensive.
- You can find information in textbooks, at a library, and online. If you are in school, you can also ask for help from teachers, librarians, and your peers.
3Analyze the literature. Spend some time reading the materials you've collected. As you do so, look for and make note of unanswered questions in the literature. These can provide excellent ideas for areas to investigate.
- For example, if you are interested in the effects of caffeine on the human body, but notice that nobody seems to have explored whether caffeine affects males differently than it does females, this could be something to formulate a hypothesis about. Or, if you are interested in organic farming, you might notice that no one has tested whether organic fertilizer results in different growth rates for plants than non-organic fertilizer.
- You can sometimes find holes in the existing literature by looking for statements like “it is unknown” or places where information is clearly missing. You might also find a claim in the literature that seems far-fetched, unlikely, or too good to be true, like that caffeine improves math skills. If the claim is testable, you could provide a great service to scientific knowledge by doing your own investigation. If you confirm the claim, the claim becomes even more credible. If you do not find support for the claim, you are helping with the necessary self-correcting aspect of science.
- Examining these types of questions provides an excellent way for you to set yourself apart by filling in important gaps in a field of study.
4Generate questions. After studying the literature on your topic, generate one or more unanswered questions you'd be interested in exploring further. These are your research questions.
- Following the examples above, you might ask: "How does caffeine affect females as compared to males?" or "How does organic fertilizer affect plant growth compared to non-organic fertilizer?" The rest of your research will be aimed at answering these questions.
5Look for clues as to what the answer might be. Once you have generated your research question or questions, look in the literature to see if the existing findings and/or theories about the topic provide any clues that would allow you to come up with ideas about what the answers to your research questions might be. If so, these clues can form the basis for your hypothesis.
- Following the examples above, if you discover in the literature that there is a pattern that some other types of stimulants seem to affect females more than males, this could be a clue that the same pattern might be true for caffeine. Similarly, if you observe the pattern that organic fertilizer seems to be associated with smaller plants overall, you might explain this pattern with the hypothesis that plants exposed to organic fertilizer grow more slowly than plants exposed to non-organic fertilizer.
Part 2Formulating Your Hypothesis
1Determine your variables. A generalizing hypothesis describes a pattern you think may exist between two variables: an independent variable and a dependent variable. If your experiments confirm the pattern, you may decide to suggest a reason that the pattern exists or a mechanism that generates the pattern. The reason or mechanism you suggest is an explanatory hypothesis.
- You can think of the independent variable as the one that is causing some kind of difference or effect to occur. In the examples, the independent variable would be biological sex, i.e. whether a person is male or female, and fertilizer type, i.e. whether the fertilizer is organic or non-organically-based.
- The dependent variable is what is affected by (i.e. "depends" on) the independent variable. In the examples above, the dependent variable would be the measured impact of caffeine or fertilizer.
- Your hypothesis should only suggest one relationship. Most importantly, it should only have one independent variable. If you have more than one, you won't be able to determine which one is actually the source of any effects you might observe.
2Generate a simple hypothesis. Once you've spent some time thinking about your research question and variables, write down your initial idea about how the variables might be related as a simple declarative statement.
- Don't worry too much at this point about being precise or detailed.
- In the examples above, one hypothesis would make a statement about whether a person's biological sex might impact the way the person is affected by caffeine; for example, at this point, your hypothesis might simply be: "a person's biological sex is related to how caffeine affects his or her heart rate." The other hypothesis would make a general statement about plant growth and fertilizer; for example your simple explanatory hypothesis might be "plants given different types of fertilizer are different sizes because they grow at different rates."
3Decide on direction. Hypotheses can either be directional or non-directional. A non-directional hypothesis simply says that one variable affects the other in some way, but does not say specifically in what way. A directional hypothesis provides more information about the nature (or "direction") of the relationship, stating specifically how one variable affects the other.
- Using our example, our non-directional hypotheses would be "there is a relationship between a person's biological sex and how much caffeine increases the person's heart rate," and "there is a relationship between fertilizer type and the speed at which plants grow."
- Directional predictions using the same example hypotheses above would be : "Females will experience a greater increase in heart rate after consuming caffeine than will males," and "plants fertilized with non-organic fertilizer will grow faster than those fertilized with organic fertilizer." Indeed, these predictions and the hypotheses that allow for them are very different kinds of statements. More on this distinction below.
- If the literature provides any basis for making a directional prediction, it is better to do so, because it provides more information. Especially in the physical sciences, non-directional predictions are often seen as inadequate.
4Get specific. Once you have an initial idea on paper, it's time to start refining. Make your hypotheses as specific as you can, so it's clear exactly what ideas you will be testing and make your predictions specific and measurable so that they provide evidence of a relationship between the variables.
- Where necessary, specify the population (i.e. the people or things) about which you hope to uncover new knowledge. For example, if you were only interested the effects of caffeine on elderly people, your prediction might read: "Females over the age of 65 will experience a greater increase in heart rate than will males of the same age." If you were interested only in how fertilizer affects tomato plants, your prediction might read: "Tomato plants treated with non-organic fertilizer will grow faster in the first three months than will tomato plants treated with organic fertilizer."
5Make sure it is testable. Your hypothesis must suggest a relationship between two variables or a reason that two variables are related that can feasibly be observed and measured in the real and observable world.
- For example, you would not want to make the hypothesis: "red is the prettiest color." This statement is an opinion and it cannot be tested with an experiment. However, proposing the generalizing hypothesis that red is the most popular color is testable with a simple random survey. If you do indeed confirm that red is the most popular color, your next step may be to ask: Why is red the most popular color? The answer you propose is your explanatory hypothesis.
- Often, hypotheses are stated in the form of if-then sentences. For example, "if children are given caffeine, then their heart rates will increase." This statement is not a hypothesis. This kind of statement is a brief description of an experimental method followed by a prediction and is the most common way that hypotheses are misrepresented in science education. An easy way to get to the hypothesis for this method and prediction is to ask yourself why you think heart rates will increase if children are given caffeine. Your explanatory hypothesis in this case may be that caffeine is a stimulant. At this point, some scientists write what is called a research hypothesis, a statement that includes the hypothesis, the experiment, and the prediction all in one statement: If caffeine is a stimulant, and some children are given a drink with caffeine while others are given a drink without caffeine, then the heart rates of those children given a caffeinated drink will increase more than the heart rate of children given a non-caffeinated drink.
- It may sound strange, but researchers rarely ever prove that a hypothesis is right or wrong. Instead, they look for evidence that the opposite of their hypotheses is probably not true. If the opposite (caffeine is not a stimulant) is probably not true, the hypothesis (caffeine is a stimulant) probably is true.
- Using the above example, if you were to test the effects of caffeine on the heart rates of children, evidence that your hypothesis is not true, sometimes called the null hypothesis, could occur if the heart rates of both the children given the caffeinated drink and the children given the non-caffeinated drink (called the placebo control) did not change, or lowered or raised with the same magnitude, if there was no difference between the two groups of children. If you wanted to test the effects of different fertilizer types, evidence that your hypothesis was not true would be that the plants grew at the same rate, regardless of fertilizer, or if plants treated with organic fertilizer grew faster. It is important to note here that the null hypothesis actually becomes much more useful when researchers test the significance of their results with statistics. When statistics are used on the results of an experiment, a researcher is testing the idea of the null statistical hypothesis. For example, that there is no relationship between two variables or that there is no difference between two groups.
Test your hypothesis. Make your observations or conduct your experiment. Your evidence may allow you to reject your null hypotheses, thus lending support to your experimental hypothesis. However, your evidence may not allow you to reject your null hypothesis and this is okay. Any result is important, even when your result sends you back to the drawing board. Constantly having to go "back to the drawing board" and refine your ideas is how authentic science really works!
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Yes, I read the article
How can I improve my hypothesis?
You have to identify the independent and the dependent variables of the experiment, add it to your hypothesis, and that's it, just make sure your hypothesis is specific!
Why is a hypothesis necessary?
A hypothesis is necessary as it explains what you predict will happen. When you find the results, you can see what actually happened and whether or not your prediction was correct or similar to the results.
What is a hypothesis?
A hypothesis is a supposition gathered by reasoning after consideration of the available evidence; it can be tested by obtaining more data, often by experimentation.
What is a hypothesis?
How can I improve my hypothesis?
How do I test my hypothesis?
Test it by coming up with an experiment to try to answer your hypothesis/question. For example, if you said, "if I made a wide winged airplane, it would go faster than a narrow winged airplane." Then you would build both and see which one went faster.
Can I use completed research to formulate a new hypothesis?
Yes, if the research applies to the hypothesis. Example: you have done an experiment to test why plants grow the way they grow,and have taken qualitative and quantitative observations. At the end of the experiment you find that your hypothesis was incorrect, so you have create a new one, but you don't have the time to do another experiment for your new hypothesis. Instead of completely redoing the whole thing and praying that there's still time left before the deadline, you can use the notes you already have to come up with a hypothesis that can be proven by the data resulting from the experiment.
Is there a maximum number of hypothesis that is allowed in one research paper?
There's not a strict limit, but your project or paper needs to be understandable and easily digestible, so you don't want to overwhelm the reader with too many experiments and proposals. It's best to limit each experiment to between one and four hypotheses, roughly.
How do I phrase the hypothesis when there are more than two IVs?
If both of the IVs support the result, then simply combine them using a conjunction like "and." For example, you could say, "If [this] and [that] occurs, then [result] will occur." If the two IVs change different DVs, then two separate hypotheses are required.
Ask a Question
- When examining the literature, look for research that is similar to what you want to do, and try to build on the findings of other researchers. But also look for claims that you think are suspicious, and test them yourself.
- Be specific in your hypotheses, but not so specific that your hypothesis can't be applied to anything outside your specific experiment. You definitely want to be clear about the population about which you are interested in drawing conclusions, but nobody (except your roommates) will be interested in reading a paper with the prediction: "my three roommates will each be able to do a different amount of pushups."
- Keep your feelings and opinions out of your research. Hypotheses should never say "I believe...," "I think...," "I feel...," or "My opinion is that...."
- Remember that science is not necessarily a linear process and can be approached in various ways.From the University of California at Berkeley's Understanding Science Website
The American Heritage Dictionary defines a hypothesis as, "a tentative explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation." This means a hypothesis is the stepping stone to a soon-to-be proven theory. For a hypothesis to be considered a scientific hypothesis, it must be proven through the scientific method. Like anything else in life, there are many paths to take to get to the same ending. Let's take a look at the different types of hypotheses that can be employed when seeking to prove a new theory.
Types of Hypothesis
First, we must take a moment to define independent and dependent variables. Simply put, an independent variable is the cause and the dependent variable is the effect. The independent variable can be changed whereas the dependent variable is what you're watching for change. For example: How does the amount of makeup one applies affect how clear their skin is? Here, the independent variable is the makeup and the dependent variable is the skin.
The six most common forms of hypotheses are:
- Simple Hypothesis
- Complex Hypothesis
- Empirical Hypothesis
- Null Hypothesis (Denoted by "HO")
- Alternative Hypothesis (Denoted by "H1")
- Logical Hypothesis
- Statistical Hypothesis
A simple hypothesis is a prediction of the relationship between two variables: the independent variable and the dependent variable.
- Drinking sugary drinks daily leads to obesity.
A complex hypothesis examines the relationship between two or more independent variables and two or more dependent variables.
Overweight adults who 1) value longevity and 2) seek happiness are more likely than other adults to 1) lose their excess weight and 2) feel a more regular sense of joy.
A null hypothesis (H0) exists when a researcher believes there is no relationship between the two variables, or there is a lack of information to state a scientific hypothesis. This is something to attempt to disprove or discredit.
There is no significant change in my health during the times when I drink green tea only or root beer only.
This is where the alternative hypothesis (H1) enters the scene. In an attempt to disprove a null hypothesis, researchers will seek to discover an alternative hypothesis.
My health improves during the times when I drink green tea only, as opposed to root beer only.
A logical hypothesis is a proposed explanation possessing limited evidence. Generally, you want to turn a logical hypothesis into an empirical hypothesis, putting your theories or postulations to the test.
Cacti experience more successful growth rates than tulips on Mars. (Until we're able to test plant growth in Mars' ground for an extended period of time, the evidence for this claim will be limited and the hypothesis will only remain logical.)
An empirical hypothesis, or working hypothesis, comes to life when a theory is being put to the test, using observation and experiment. It's no longer just an idea or notion. It's actually going through some trial and error, and perhaps changing around those independent variables.
- Roses watered with liquid Vitamin B grow faster than roses watered with liquid Vitamin E. (Here, trial and error is leading to a series of findings.)
A statistical hypothesis is an examination of a portion of a population.
If you wanted to conduct a study on the life expectancy of Savannians, you would want to examine every single resident of Savannah. This is not practical. Therefore, you would conduct your research using a statistical hypothesis, or a sample of the Savannian population.
Parameters of a Good Hypothesis
In order for a hypothesis to be sound, hold tight to these tips:
Ask yourself questions.
- Brainstorm. Define the independent and dependent variables very specifically, and don't take on more than you can handle. Keep yourself laser-focused on one specific cause-and-effect theory.
Be logical and use precise language.
- Keep your language clean and simple. State your hypothesis as concisely, and to the point, as possible. A hypothesis is usually written in a form where it proposes that, if something is done, then something else will occur. Usually, you don't want to state a hypothesis as a question. You believe in something, and you're seeking to prove it. For example: If I raise the temperature of a cup of water, then the amount of sugar that can be dissolved in it will be increased.
Make sure your hypothesis is testable with research and experimentation.
- Any hypothesis will need proof. Your audience will have to see evidence and reason to believe your statement. For example, I may want to drink root beer all day, not green tea. If you're going to make me change my ways, I need some sound reasoning and experimental proof - perhaps case studies of others who lost weight, cleared up their skin, and had a marked improvement in their immunity by drinking green tea.
State Your Case
Scientists can really change the world with their hypotheses and findings. In an effort to improve the world we live in, all it takes is an initial hypothesis that is well-stated, founded in truth, and can withstand extensive research and experimentation. Seek out your independent and dependent variables and go on out here and make this world a better place. Good luck!