How to Write a Hypothesis
If I [do something], then [this] will happen.
This basic statement/formula should be pretty familiar to any or all of you as it could be the starting point of almost every scientific project or paper. It's a hypothesis – a statement that showcases what you “think” will happen all through an experiment. This assumption is made on the basis of the knowledge, facts, and data you have.
How will you write a hypothesis? When you have a clear understanding of the correct structure of a hypothesis, you should not think it is too hard to generate one. But if you have never written a hypothesis before, you might find it a bit frustrating. In this specific article, we are going to let you know everything you need to learn about hypotheses, their types, and practical tips for writing them.
In line with the definition, a hypothesis can be an assumption one makes predicated on existing knowledge. To elaborate, it is a statement that translates the initial research question right into a logical prediction shaped based on available facts and evidence. To solve a particular problem, one first must identify the study problem (research question), conduct initial research, and attempt to answer the given question by performing experiments and observing their outcomes. But before you can move to the experimental area of the research, they ought to first identify what they expect to see for results. At this stage, a scientist makes an educated guess and writes a hypothesis that he or she will prove or refute throughout their study.
A hypothesis may also be seen as a type of development of knowledge. This is a well-grounded assumption put forward to clarify the properties and causes of the phenomena being studied.
Usually, a hypothesis is formed based on numerous observations and examples that confirm it. This way, it looks plausible as it is backed up with some known information. The hypothesis is subsequently proved by making it an established fact or refuted (for example, by pointing out a counterexample), allowing it to attribute it to the category of false statements.
As a student, perhaps you are asked to produce a hypothesis statement as a part of your academic papers. Hypothesis-based approaches are commonly used among scientific academic works, including although not limited to research papers, theses, and Dissertations.
Remember that in some disciplines, a hypothesis statement is named a thesis statement. Nevertheless , its essence and purpose remain unchanged – this statement aims to make an assumption about the outcomes of the investigation that will either be proved or refuted.
Characteristics and Sources of a Hypothesis
Now, as you know just what a hypothesis is in a nutshell, let’s look at the key characteristics that define it:
- It has to be clear and accurate in order to look reliable.
- It has to be specific.
- There ought to be scope for further investigation and experiments.
- A hypothesis must certanly be explained in simple language—while retaining its significance.
- If you should be making a relational hypothesis, two essential elements you have to include are variables and the connection between them.
The main sources of a hypothesis are:
- Scientific theories.
- Observations from previous studies and current experiences.
- The resemblance among different phenomena.
- General patterns that affect people’s thinking process.
Types of Hypothesis
Ostensibly, there are two major forms of scientific hypothesis: alternative and null.
- Alternative Hypothesis
This sort of hypothesis is normally denoted as H1. This statement can be used to identify the expected upshot of your research. Based on the alternative hypothesis definition, this sort of hypothesis could be further split into two subcategories:
- Directional — a statement that explains the direction of the expected outcomes. Sometimes this type of hypothesis is used to review the relationship between variables as opposed to comparing between your groups.
- nondirectional — unlike the directional alternative hypothesis, a nondirectional one doesn't imply a certain direction of the expected outcomes.
Now, let’s see an alternative hypothesis example for every single type:
Directional: Attending more lectures will result in improved test scores among students. Non-directional: Lecture attendance will influence test scores among students.
Notice how in the directional hypothesis we specified that the attendance of more lectures will boost student’s performance on tests, whereas in the nondirectional hypothesis we only stated that there's a relationship between the two variables (i. e. lecture attendance and students’ test scores) but did not specify whether the performance will improve or decrease.
- Null Hypothesis
This sort of hypothesis is normally denoted as H0. This statement may be the complete opposite of what you are expecting or predict will happen through the entire course of your study—meaning it's the opposite of one's alternative hypothesis. Simply put, a null hypothesis claims that there surely is no exact or actual correlation between your variables defined in the hypothesis.
To offer a better notion of how to write a null hypothesis, this is a clear example: Lecture attendance does not have any effect on student’s test scores.
These two types of hypotheses provide specific clarifications and restatements of the research problem. The main big difference between these hypotheses and a research problem is that the latter is just a question that can’t be tested, whereas hypotheses can.
On the basis of the alternative and null hypothesis examples provided earlier, we could conclude that the importance and main intent behind these hypotheses are which they deliver a rough description of the niche matter. The key purpose of these statements is always to give an investigator a certain guess that may be directly tested in research. Simply put, a hypothesis outlines the framework, scope, and direction for the study. Even though null and alternative hypotheses are the major types, additionally, there are a few more to bear in mind:
Research Hypothesis — a statement that is used to test the correlation between two or more variables.
For example: Eating vitamin-rich foods affects human health.
Simple Hypothesis — a statement used to point the correlation between one independent and something dependent variable.
For example: Eating more vegetables leads to better immunity.
Complex Hypothesis — a statement used to point the correlation between a couple of independent variables and a couple of dependent variables.
For example: Consuming more fruits and vegetables results in better immunity, weight loss, and lower threat of diseases.
Associative and Causal Hypothesis — an associative hypothesis is just a statement used to indicate the correlation between variables underneath the scenario each time a change in one single variable inevitably changes one other variable. A causal hypothesis is a statement that highlights the cause and effect relationship between variables.
Hypothesis vs Prediction
When speaking of hypotheses, another term that involves mind is prediction. Both of these terms tend to be used interchangeably, which can be rather confusing. Even though both a hypothesis and prediction can generally be defined as “guesses” and can be easy to confuse, these terms are different. The primary difference between a hypothesis and a prediction is that the foremost is predominantly found in science, as the latter is most often used outside of science.
In other words, a hypothesis is an intelligent assumption. It's a guess made regarding the nature of the unknown (or less known) phenomena centered on existing knowledge, studies, and/or series of experiments, and is otherwise grounded by valid facts. The key purpose of a hypothesis is to utilize available facts to create a logical relationship between variables so that you can provide a more precise scientific explanation. In addition , hypotheses are statements which can be tested with further experiments. It is an assumption you make about the flow and outcome(s) of one's research study.
A prediction, on the other hand, is a reckon that often lacks grounding. Even though, in theory, a prediction could be scientific, generally it is rather fictional—i. e. a pure reckon that is not predicated on current knowledge and/or facts. As a rule, predictions are associated with foretelling events that may or may not occur in the future. Frequently , a person who makes predictions has little or no actual knowledge of the topic matter she or he makes the assumption about.
Still another big difference between these terms is in the methodology used to prove every one of them. A prediction can only be proven once. You can determine whether it is right or wrong only upon the occurrence or nonoccurrence of the predicted event. A hypothesis, on the other hand, offers scope for further testing and experiments. Additionally , a hypothesis may be proven in multiple stages. This ostensibly means that just one hypothesis may be proven or refuted numerous times by different boffins who use different scientific tools and methods.
To offer a better concept of how a hypothesis is different from the prediction, let’s look at the following examples:
Hypothesis: Basically eat more vegetables & fruits, then I will totally lose weight faster.
It is a hypothesis since it is based on broadly speaking available knowledge (i. e. fruits and vegetables include fewer kcalories compared to other foods) and past experiences (i. e. people who give preference to healthier foods like vegetables & fruits are slimming down easier). It really is still a guess, nonetheless it is based on facts and can be tested having an experiment.
Prediction: The end of the world will occur in 2023.
It is a prediction since it foretells future events. But this assumption is fictional as it doesn’t have any actual grounded evidence supported by facts.
Predicated on everything that was said earlier in the day and our examples, we are able to highlight the next key takeaways:
- A hypothesis, unlike a prediction, is a more intelligent assumption based on facts.
- Hypotheses define existing variables and analyze the relationship(s) between them.
- Predictions are most often fictional and lack grounding.
- A prediction is most often used to foretell events as time goes by.
- A prediction can just only be proven once – when the predicted event does occur or doesn’t occur.
- A hypothesis can remain a hypothesis even though one scientist has already proven or disproven it. Other scientists in the foreseeable future can obtain another result using other techniques and tools.
How to Write a Hypothesis
Now, as you know just what a hypothesis is, what types of it exist, and how it differs from the prediction, you're probably wondering how to state a hypothesis. In this section, we shall guide you through the main stages of writing a good hypothesis and offer handy recommendations and examples to help you over come this challenge:
1. Define Your Research Question
Here's one thing to bear in mind – whatever the paper or project you're working on, the procedure should always focus on asking the proper research question. A perfect research question ought to be specific, clear, focused (meaning not too broad), and manageable.
Example: So how exactly does eating vegetables & fruits affect human health?
2. Conduct Your Basic Initial Research
As you already know, a hypothesis is definitely an educated guess of the expected results and outcomes of a study. Thus, it's important to collect some information one which just make this assumption.
At this time, you should find an answer to your research question based on what has already been discovered. Search for facts, past studies, theories, and so on Based on the collected information, you ought to be able to make a logical and intelligent guess.
3. Formulate a Hypothesis
In line with the initial research, you should have a particular idea of everything you may find through the entire course of your quest. Use this knowledge to shape a clear and concise hypothesis.
In line with the type of project you are focusing on, and the sort of hypothesis you've planned to use, it is possible to restate your hypothesis in a number of different ways:
Non-directional: Eating fruits and vegetables will affect one’s human physical health.
Directional: Eating fruits and vegetables will positively affect one’s human physical health.
Null: Eating fruits and vegetables may have no impact on one’s human physical health.
4. Refine Your Hypothesis
Finally, the last stage of making a good hypothesis is refining what you’ve got. During this step, you need to define whether your hypothesis:
- Has clear and relevant variables;
- Identifies the relationship between its variables;
- Is specific and testable;
- Suggests a predicted result of the investigation or experiment.
Carrying out a step-by-step guide and recommendations from this article, you should be in a position to create good hypotheses easily. To give you a starting point, we've also compiled a list of different research questions with one hypothesis and something null hypothesis example for every: