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A hypothesis is a description of a law of nature or an explanation of real-world phenomena that can be tested through observation and experiment. In scientific research, a hypothesis is often proposed in the form of an exploratory, testable, and negative claim – used to explain some phenomenon observed in nature. [1] X Research Source This is the explanatory hypothesis . In addition, a hypothesis can also be a description of a law, how it works in nature. That is the general hypothesis . [2] X Source of Research[3] X Source of Research Hypothesis that can make predictions : assertions that one variable will have an effect or change in the other through controlled experiment . However, much of the scientific literature promotes the view that a hypothesis is simply an educated guess and is no different from a prediction. [4] X Research Source More information on this misunderstanding is presented below.
Many academic disciplines, from the physical sciences to the life and social sciences, use hypothesis testing as a means to test ideas, understand more about the world, and enrich scientific knowledge. Whether you’re an academic or a freshman taking a science class, it’s important to understand what a hypothesis is and to know how to build your own hypothesis and prediction. The instructions below will help you take your first steps.
Steps
Prepare to write a hypothesis
- If you’re writing a hypothesis for a school assignment, this step is probably already there.
- Focus on scholarly and academic writing. Make sure your information is accurate, complete, and free from distortion.
- You can find information in the textbook, at the library, or online. If you are still in school, you can also ask for help from teachers, librarians and classmates.
- For example, if you are interested in the effects of caffeine on the human body and find that no one seems to understand how caffeine affects men and women differently, that could be the beginning. points for you to build your hypothesis. Or, as you’re interested in organic farming, you may find that no one has considered whether organic fertilizers produce a different growth rate in plants than inorganic fertilizers.
- Sometimes, you can spot holes in existing documents by looking for statements like “unconfirmed” or clearly lacking information. You can also look in the literature for claims that seem unconvincing, unlikely, or too good to be true, such as: caffeine improves math skills. If it is a verifiable claim, you will greatly benefit your scientific knowledge by conducting your own investigation. If corroborated, that claim will become even more amazing. If the results are not enough to confirm, you are contributing to the process of self-examination and correction – an essential aspect of science.
- Looking at these types of questions is a great way to fill in important gaps in your field of study and stand out.
- Continuing with the example above, you might ask: “How does caffeine affect women compared to men?” or “How do organic fertilizers affect plant growth when compared to inorganic fertilizers?”. The remainder of the study will aim to answer these questions.
- With the example above, if you look through the literature and you notice that with some other stimulants, the effect on women always seems to be greater than on men, this could be an indication of this condition. The same may be true of caffeine. Similarly, if you observe that, in general, organic fertilizers always seem to be associated with smaller plants, you can explain it by the hypothesis that organically fertilized plants grow more slowly than inorganically fertilized plants. muscle.
Form your hypothesis
- You can also view the independent variable as the variable that makes a difference or an impact. In our example, the independent variable is gender: whether a person is male or female, and the type of fertilizer: inorganic or organic.
- A dependent variable is the object that is affected by (“depends” on) the independent variable. In the example above, the dependent variable would be the measured effect of caffeine or fertilizer.
- Your hypothesis should suggest only one relationship. Most importantly, it should have only one independent variable. If there is more than one, you cannot determine which variable is the true source of any observed effects.
- At this point, don’t worry too much about accuracy or going into details.
- In the example above, it could be an assertion about whether a person’s gender can influence the effects of caffeine on them. For example, at this point, your hypothesis could simply be: “A person’s gender is related to how caffeine affects their heart rate.” Or, it could be a general statement about plant growth and fertilizer. Your simple explanation could be: “Plants that are fertilized with different fertilizers are of different sizes because they grow at different rates”.
- For our example, the scalar hypothesis could be: “There is a relationship between a person’s sex and the increase in heart rate that caffeine causes for that person” and “There is a relationship between the type of fertilizer and growth rate of the tree”.
- Directional predictions for the above examples might be: “After caffeine intake, the increase in heart rate in women will be higher than in men” and “Plants with inorganic fertilizers will grow faster than plants using organic fertilizers”. In fact, the predictions and the hypotheses that make up the predictions are very different statements. This difference will be discussed further in the following section.
- If the literature provides any basis for building a directed prediction, you should do it because directed prediction is more informative. In particular, in the physical sciences, scalar predictions are generally not accepted.
- When necessary, clarify the whole (person or thing) you are hoping to uncover new insights into. For example, if you’re only interested in the effects of caffeine on older adults, your forecast might be: “The increase in heart rate in women over 65 is higher than in men of the same age.” If you’re just interested in the effect of fertilizer on tomato plants, your prediction might be: “Tomato plants that are fertilized with inorganic fertilizers will grow faster than tomatoes that are fertilized with organic fertilizers in the first three months. “.
- For example, you wouldn’t want to build the hypothesis: “Red is the best color”. This is an opinion and cannot be tested experimentally. However, the general hypothesis: “Red is the most popular color” can be tested by a simple random survey. If it is confirmed that red is the most loved color, the next step might be to ask the question: Why is red the most loved color? The suggested answer would be your explanatory hypothesis .
- Usually, the hypothesis is stated in the form of if-then sentences. Example: “If children are given caffeine, their heart rate will increase”. This statement is not a hypothesis. This type of statement is just a brief description of the experimental method that follows a prediction and is the most commonly misrepresented hypothesis in science education. A simple way to form hypotheses and predictions for this method is to ask yourself why you think your heart rate will increase when you give your baby caffeine. Here, the possible explanation is: caffeine is a stimulant. By this point, some scientists would have written the research hypothesis , a claim that included hypothesis, experiment, and prediction: If caffeine were a stimulant and some children were given caffeine during a When some children were given a non-caffeinated drink, the heart rate of the children given the caffeinated drink increased more than that of the other children .
- It may seem odd, but researchers rarely prove a hypothesis to be true or false. Instead, they look for evidence that the opposite of their hypothesis is likely not true. If the opposite (caffeine is not a stimulant) is likely to be false, the hypothesis (caffeine is a stimulant) is likely to be true.
- With the example above, when testing the effects of caffeine on heart rate in children, evidence that your hypothesis is incorrect – sometimes called the null hypothesis , can appear if the heart rate is at both caffeine and non-caffeinated children (called the control group) did not change or both increased or decreased to the same extent – there was no difference between the two groups of children. If you want to test the effects of different fertilizers, the proof that your hypothesis isn’t correct would be that plants grow at the same rate regardless of the type of fertilizer, or that plants used compost grow faster. The important thing to note here is this: the null hypothesis becomes much more useful when the significance of the result is tested statistically. When statistics are applied to the results of an experiment, the researcher tests the idea of the null hypothesis. For example, test that there is no relationship between two variables or that there is no difference between the two groups. [5] X Research Sources
Advice
- As you go through the literature, look for research that is similar to the research you want to do and build on the work of other researchers. At the same time, also pay attention to the assertions you feel doubtful and test them yourself.
- The hypothesis should be specific, but it should not be so extreme that it can only be applied to your experiment. Surely you need to understand the whole you want to study. However, no one (except roommates) will be interested in reading the report with the prediction: “The number of push-ups my three roommates are capable of performing is different.”
- Don’t let personal feelings and opinions influence your research. Hypotheses should never state: “I believe…”, “I think…”, “I feel…” or “My opinion is…”.
- Remember that science is not necessarily a linear process and can be approached in many different ways. [7] X Research Sources
wikiHow is a “wiki” site, which means that many of the articles here are written by multiple authors. To create this article, 82 people, some of whom are anonymous, have edited and improved the article over time.
This article has been viewed 56,449 times.
A hypothesis is a description of a law of nature or an explanation of real-world phenomena that can be tested through observation and experiment. In scientific research, a hypothesis is often proposed in the form of an exploratory, testable, and negative claim – used to explain some phenomenon observed in nature. [1] X Research Source This is the explanatory hypothesis . In addition, a hypothesis can also be a description of a law, how it works in nature. That is the general hypothesis . [2] X Source of Research[3] X Source of Research Hypothesis that can make predictions : assertions that one variable will have an effect or change in the other through controlled experiment . However, much of the scientific literature promotes the view that a hypothesis is simply an educated guess and is no different from a prediction. [4] X Research Source More information on this misunderstanding is presented below.
Many academic disciplines, from the physical sciences to the life and social sciences, use hypothesis testing as a means of testing ideas, understanding more about the world, and enriching scientific knowledge. Whether you’re an academic or a freshman taking a science class, it’s important to understand what a hypothesis is and to know how to build your own hypothesis and prediction. The instructions below will help you take your first steps.
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