General Education
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:
So let’s get started!
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):
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!
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.
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.
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.
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.
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:
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.
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.
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.
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.
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.
Good hypotheses ensure that you can observe the results.
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.
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?
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.
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.
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 ).
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.
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!
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.
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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We have heard of many hypotheses which have led to great inventions in science. Assumptions that are made on the basis of some evidence are known as hypotheses. In this article, let us learn in detail about the hypothesis and the type of hypothesis with examples.
A hypothesis is an assumption that is made based on some evidence. This is the initial point of any investigation that translates the research questions into predictions. It includes components like variables, population and the relation between the variables. A research hypothesis is a hypothesis that is used to test the relationship between two or more variables.
Following are the characteristics of the hypothesis:
Following are the sources of hypothesis:
There are six forms of hypothesis and they are:
It shows a relationship between one dependent variable and a single independent variable. For example – If you eat more vegetables, you will lose weight faster. Here, eating more vegetables is an independent variable, while losing weight is the dependent variable.
It shows the relationship between two or more dependent variables and two or more independent variables. Eating more vegetables and fruits leads to weight loss, glowing skin, and reduces the risk of many diseases such as heart disease.
It shows how a researcher is intellectual and committed to a particular outcome. The relationship between the variables can also predict its nature. For example- children aged four years eating proper food over a five-year period are having higher IQ levels than children not having a proper meal. This shows the effect and direction of the effect.
It is used when there is no theory involved. It is a statement that a relationship exists between two variables, without predicting the exact nature (direction) of the relationship.
It provides a statement which is contrary to the hypothesis. It’s a negative statement, and there is no relationship between independent and dependent variables. The symbol is denoted by “H O ”.
Associative hypothesis occurs when there is a change in one variable resulting in a change in the other variable. Whereas, the causal hypothesis proposes a cause and effect interaction between two or more variables.
Following are the examples of hypotheses based on their types:
Following are the functions performed by the hypothesis:
Researchers use hypotheses to put down their thoughts directing how the experiment would take place. Following are the steps that are involved in the scientific method:
What is hypothesis.
A hypothesis is an assumption made based on some evidence.
What are the types of hypothesis.
Types of hypothesis are:
Define complex hypothesis..
A complex hypothesis shows the relationship between two or more dependent variables and two or more independent variables.
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The Difference Between Hypothesis and Theory
A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.
In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.
A hypothesis is usually tentative; it's an assumption or suggestion made strictly for the objective of being tested.
A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, it is understood to be more likely to be true than a hypothesis is.
In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch, with theory being the more common choice.
Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.
The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)
This mistake is one of projection: since we use theory in general to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.
The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”
While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."
hypothesis , theory , law mean a formula derived by inference from scientific data that explains a principle operating in nature.
hypothesis implies insufficient evidence to provide more than a tentative explanation.
theory implies a greater range of evidence and greater likelihood of truth.
law implies a statement of order and relation in nature that has been found to be invariable under the same conditions.
These examples are programmatically compiled from various online sources to illustrate current usage of the word 'hypothesis.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.
Greek, from hypotithenai to put under, suppose, from hypo- + tithenai to put — more at do
1641, in the meaning defined at sense 1a
This is the Difference Between a...
In scientific reasoning, they're two completely different things
hypothermia
hypothesize
“Hypothesis.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/hypothesis. Accessed 16 Aug. 2024.
Kids definition of hypothesis, medical definition, medical definition of hypothesis, more from merriam-webster on hypothesis.
Nglish: Translation of hypothesis for Spanish Speakers
Britannica English: Translation of hypothesis for Arabic Speakers
Britannica.com: Encyclopedia article about hypothesis
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Click here if you have ever found yourself in the position of having to wrestle with the development of a hypothesis for your research paper. As an expert writer, I have seen that this is where most students begin to sweat. It is a potpourri of theory and practice, hence rather intimidating. But not to worry because I have got your back. This guide is a pool of tips and tricks for writing a hypothesis to set the stage for compelling research.
A hypothesis is a tentative statement, usually in the form of an educated guess, that provides a probable explanation for something either a phenomenon or a relationship between variables. This will, therefore, form a basis for conducting experiments and research studies, hence laying down the course of your investigation and mainly laying the ground for your conclusion.
A good hypothesis should be:
Specific and clear
Testable and falsifiable
Based upon existing knowledge
Logically consistent
There are different kinds of hypotheses used in research, all of which serve different purposes depending on the nature of the study. Here are eight common types:
1. The null hypothesis (H0): asserts that there is no effect or relationship between variables. This forms a baseline for comparison. Example: "There is no difference in test scores for students who study music and for those who do not."
2. Alternative Hypothesis (H1): The hypothesis that postulates some effect or relationship between variables; it is, therefore, the opposite of the null hypothesis. For instance, "Students who study with music have different test scores than those who study in silence."
3. Simple Hypothesis: The hypothesis that states a relationship between two variables: one independent and one dependent. For example, "More sunlight increases plant growth."
4. Complex Hypothesis: This hypothesis involves the relationship of more than one variable. For example, "More sunlight and water increase plant growth."
5. Directional Hypothesis: The hypothesis which specifies the direction of the effect between variables. For instance, "Students who study with music will have higher test scores than students who study in silence."
6. Non-Directional Hypothesis: This is a hypothesis used where the relationship is indicated, but the direction is not specified. For example, "There is a difference in test scores between students who study with music and those who study in silence."
7. Associative Hypothesis: This hypothesis merely states that the change in one variable is associated with a change in another. It does not indicate cause and effect. For example: "There is a relationship between study habits and academic performance."
8. Causal Hypothesis: This hypothesis states that one variable causes a change in another. For example: "Increased study time results in higher test scores."
Understanding such types of hypotheses will help in the selection of the correct hypothesis for your research and in making your analysis clear and effective.
An excellent hypothesis provides a backbone to any scientific research. Leave some help behind in writing one? Follow this easy guide:
Step 1: Ask a Question
First, you must understand what your research question is. Suppose you want to carry out an experiment on plant growth. Your question can be, "How does sunlight affect plant growth?"
Use WPS AI to help when you get stuck. Feed it a topic, and it will come up with related questions to ask.
Step 2: Do Preliminary Research
Do some research to see what's already known about your topic. That way, you can build upon existing knowledge.
Research information in journals, books and credible websites. Then summarize what you read. This will help you formulate your hypothesis.
Step 3: Define Variables
Identify your variables:
Independent Variable: What you manipulate. For example, the amount of sun.
Dependent Variable: What you measure. For example, plant growth rate.
Clearly defining these makes your hypothesis specific and testable.
Step 4: State Your Hypothesis
State your question in the form of a hypothesis. Here are some examples:
If then: "If plants receive more sunlight, then they will grow faster."
Comparative statements: "Plants receiving more sunlight grow faster than plants receiving less."
Correlation statements: "There is positive correlation between sunlight and plant growth." This kind of pattern makes your hypothesis easy to test.
Step 5: Refine Your Hypothesis
Revise your hypothesis to be clear and specific, and elicit feedback to improve it.
You will also need a null hypothesis, which says that there is no effect or relationship between variables. An example would be, "Sunlight has no effect on the growth of plants."
With these steps, you are now bound to come up with a testable hypothesis. WPS AI can help you in this process more efficiently.
A good hypothesis is seen as the backbone of doing effective research. Following are some key characteristics that define a good hypothesis:
A good hypothesis has to be testable either by experimentation or observation. The hypothesis should clearly predict what can be measured or observed. For example, "If it receives more sunlight, the plant will grow taller" is a testable hypothesis since it states what can be measured.
Falsifiable
A hypothesis has to be falsifiable: it should be able to prove it wrong. This feature is important because it accommodates testing in science. For example, the statement "All swans are white" is falsifiable since it just takes one black swan to disprove the claim.
A good hypothesis should be grounded in current knowledge and should be properly reasoned. It should be broad or reasonable within existing knowledge. For example, "Increasing the amount of sunlight will boost plant growth" makes sense, in that it tallies with generally known facts about photosynthesis.
Specific and Clear
What is needed is clarity and specificity. A hypothesis has to be brief, yet free from ambiguity. For instance, "Increased sunlight leads to taller plants" is clear and specific whereas "Sunlight affects plants" is too vague.
Built upon Prior Knowledge
A good hypothesis is informed by prior research and existing theories. The available knowledge enlightens it to build on what is known to find new relationships or effects. For example, "Given photosynthesis requires sunlight, increasing sunlight will enhance plant growth" is informed by available scientific understanding.
Ethical Considerations
Finally, a good hypothesis needs to consider the ethics involved. The research should not bring damage to participants or the environment. For instance, "How the new drug will affect a human when tested without testing it on animals" may present an ethical concern.
Checklist for Reviewing Your Hypothesis
To be certain that your hypothesis has the following characteristics, use this checklist to review your hypothesis:
1. Is the hypothesis testable through experimentation or observation?
2. Can the hypothesis be proven false?
3. Is the hypothesis logically deduced from known facts?
4. Is your hypothesis clear and specific?
5. Does your hypothesis relate to previous research or theories?
6. Will there be any ethical issues with the proposed research?
7. Are your independent and dependent variables well defined?
8. Is your hypothesis concise and ambiguity free?
9. Did you get feedback to help in refining your hypothesis?
10. Does your hypothesis contain a null hypothesis for comparison?
By making sure that your hypothesis has these qualities, you are much more likely to set yourself on the course of higher-quality research and larger impacts. WPS AI can help fine-tune a hypothesis to ensure it is well-structured and clear.
Drafting a good hypothesis is the real inception of any research project. WPS AI, with its advanced language functions, can very strongly improve this stage of your study. Here's how WPS AI can help you perfect your hypothesis:
Check Grammar and Syntax
Grammar and punctuation errors can make your hypothesis weak. WPS AI checks and corrects this with the assurance that your hypothesis is as clear as possible and professional in its presentation. For example, when your hypothesis is written, "If the temperature increases then plant growth will increases", WPS AI can correct it to "If the temperature increases, then plant growth will increase."
Rewrite Your Hypothesis for Clarity
There needs to be a clear hypothesis. WPS AI can suggest ways to reword your hypothesis so that it makes sense. If your original hypothesis is, "More sunlight will result in more significant plant growth due to photosynthesis," WPS AI can suggest, "Increased sunlight will lead to greater plant growth through enhanced photosynthesis."
Automatic Content Expansion
Sometimes, your hypothesis or the related paragraphs may require more detail. WPS AI's [Continue Writing] feature can help enlarge the content. For example, after having written, "This study will examine the effects of sunlight on plant growth", using [Continue Writing] it can enlarge it to, "This research paper is going to study how sunlight affects the growth of plants by measuring their height and their health under different amounts of sunlight over a period of six weeks."
WPS AI is a great tool that can help you in drafting a good hypothesis for your research. It will help you check grammar, syntax, clarity, and completeness. Using WPS AI , you will be assured that the results of your hypothesis will be well-written and clear to understand.
The hypothesis is one single testable prediction regarding some phenomenon. The theory is an explanation for some part of the natural world which is well-substantiated by a body of evidence, together with multiple hypotheses.
If your results turn out not to support your hypothesis, analyze the data again to see why your result rejects your hypothesis. Do not manipulate the observations or experiment so that it leads to your hypothesis.
Yes, there may be more than one hypothesis, especially when one research study is examining several interrelated phenomena or variables. Each hypothesis has to be separately and clearly stated and tested.
Correct formulation of a strong, testable hypothesis is one of the most critical steps in the application of the scientific method and within academic research. The steps provided in this article will help you write a hypothesis that is clear, specific, and based on available knowledge. Give the tools and tips a try to elevate your academic writing and kick your research up a notch.
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Expressed as a single equation:
eGFR = 142 * min(standardized S cr /K, 1) α * max(standardized S cr /K, 1) -1.200 * 0.9938 Age * 1.012 [if female]
eGFR (estimated glomerular filtration rate) = mL/min/ 1.73 m 2
S cr (serum creatinine) = mg/dL
K = 0.7 (females) or 0.9 (males)
α = -0.241 (females) or -0.302 (males)
min = indicates the minimum of S cr /K or 1
max = indicates the maximum of S cr /K or 1
COMMENTS
An In-Depth Explanation. A hypothesis is a vital part of scientific research. It is a statement that predicts the outcome of an experiment or study. Formulating a hypothesis involves observing a problem, gathering information, and coming up with possible explanations that can be tested. This article will guide you through the steps of creating ...
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.
Definition: Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation. Hypothesis is often used in scientific research to guide the design of experiments ...
A hypothesis is a prediction of what will be found at the outcome of a research project and is typically focused on the relationship between two different variables studied in the research. It is usually based on both theoretical expectations about how things work and already existing scientific evidence. Within social science, a hypothesis can ...
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 ...
What is a Hypothesis / Definition. A hypothesis is like a bet: you size things up and tell your mates exactly what you think is going to happen with respect to X, Y, Z. ... Formulate the Hypothesis; Based on your research question and preliminary research, now you can create your hypothesis. A good hypothesis should be clear, concise, and testable.
3 Define your variables. Once you have an idea of what your hypothesis will be, select which variables are independent and which are dependent. Remember that independent variables can only be factors that you have absolute control over, so consider the limits of your experiment before finalizing your hypothesis.
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.
hypothesis. science. scientific hypothesis, an idea that proposes a tentative explanation about a phenomenon or a narrow set of phenomena observed in the natural world. The two primary features of a scientific hypothesis are falsifiability and testability, which are reflected in an "If…then" statement summarizing the idea and in the ...
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.
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.
The hypothesis is a predictive, testable statement predicting the outcome and the results the researcher expects to find. The hypothesis provides a summary of what direction, if any, is taken to investigate a theory. In scientific research, there is a criterion that hypotheses need to be met to be regarded as acceptable.
Hypothesis testing example. You want to test whether there is a relationship between gender and height. Based on your knowledge of human physiology, you formulate a hypothesis that men are, on average, taller than women. To test this hypothesis, you restate it as: H 0: Men are, on average, not taller than women. H a: Men are, on average, taller ...
A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable. So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you'll not only have rock-solid ...
Identifying the Research Question. The first step in formulating a strong hypothesis is to identify the main research question. This involves recognizing a pattern or phenomenon that piques your interest and then asking a specific question that your hypothesis will aim to answer. This step is crucial as it sets the direction for your targeted ...
A research hypothesis, in its plural form "hypotheses," is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.
The researcher states a hypothesis to be tested, formulates an analysis plan, analyzes sample data. according to the plan, and accepts or rejects the null hypothesis, based on r esults of the ...
To formulate a hypothesis, a researcher must consider the requirements of a strong hypothesis: Make a prediction based on previous observations or research. Define objective independent and ...
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 ...
Hypothesis is a prediction of the outcome of a study. Hypotheses are drawn from theories and research questions or from direct observations. In fact, a research problem can be formulated as a hypothesis. To test the hypothesis we need to formulate it in terms that can actually be analysed with statistical tools.
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.
Functions of Hypothesis. Following are the functions performed by the hypothesis: Hypothesis helps in making an observation and experiments possible. It becomes the start point for the investigation. Hypothesis helps in verifying the observations. It helps in directing the inquiries in the right direction.
hypothesis: [noun] an assumption or concession made for the sake of argument. an interpretation of a practical situation or condition taken as the ground for action.
A hypothesis is a tentative statement, usually in the form of an educated guess, that provides a probable explanation for something either a phenomenon or a relationship between variables. This will, therefore, form a basis for conducting experiments and research studies, hence laying down the course of your investigation and mainly laying the ...
What the jury found Donald Trump did to E. Jean Carroll was in fact rape, as commonly understood, even if it didn't fit New York law's narrow definition, says Judge Lewis A. Kaplan.
The Recommended method for estimating GFR in adults from the National Kidney Foundation is the 2021 CKD-EPI equations. Designed for use with laboratory creatinine values that are standardized to IDMS.