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Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.
A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .
Daily apple consumption leads to fewer doctor’s visits.
What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.
A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.
A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).
Hypotheses propose a relationship between two or more types of variables .
If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias will affect your results.
In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .
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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.
Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.
At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.
Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.
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:
To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.
In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.
If you are comparing two groups, the hypothesis can state what difference you expect to find between them.
If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .
Research question | Hypothesis | Null hypothesis |
---|---|---|
What are the health benefits of eating an apple a day? | Increasing apple consumption in over-60s will result in decreasing frequency of doctor’s visits. | Increasing apple consumption in over-60s will have no effect on frequency of doctor’s visits. |
Which airlines have the most delays? | Low-cost airlines are more likely to have delays than premium airlines. | Low-cost and premium airlines are equally likely to have delays. |
Can flexible work arrangements improve job satisfaction? | Employees who have flexible working hours will report greater job satisfaction than employees who work fixed hours. | There is no relationship between working hour flexibility and job satisfaction. |
How effective is high school sex education at reducing teen pregnancies? | Teenagers who received sex education lessons throughout high school will have lower rates of unplanned pregnancy teenagers who did not receive any sex education. | High school sex education has no effect on teen pregnancy rates. |
What effect does daily use of social media have on the attention span of under-16s? | There is a negative between time spent on social media and attention span in under-16s. | There is no relationship between social media use and attention span in under-16s. |
If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.
Statistics
Research bias
A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).
Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
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McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved September 4, 2024, from https://www.scribbr.com/methodology/hypothesis/
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Home » What is a Hypothesis – Types, Examples and Writing Guide
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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 and the collection and analysis of data. It is an essential element of the scientific method, as it allows researchers to make predictions about the outcome of their experiments and to test those predictions to determine their accuracy.
Types of Hypothesis are as follows:
A research hypothesis is a statement that predicts a relationship between variables. It is usually formulated as a specific statement that can be tested through research, and it is often used in scientific research to guide the design of experiments.
The null hypothesis is a statement that assumes there is no significant difference or relationship between variables. It is often used as a starting point for testing the research hypothesis, and if the results of the study reject the null hypothesis, it suggests that there is a significant difference or relationship between variables.
An alternative hypothesis is a statement that assumes there is a significant difference or relationship between variables. It is often used as an alternative to the null hypothesis and is tested against the null hypothesis to determine which statement is more accurate.
A directional hypothesis is a statement that predicts the direction of the relationship between variables. For example, a researcher might predict that increasing the amount of exercise will result in a decrease in body weight.
A non-directional hypothesis is a statement that predicts the relationship between variables but does not specify the direction. For example, a researcher might predict that there is a relationship between the amount of exercise and body weight, but they do not specify whether increasing or decreasing exercise will affect body weight.
A statistical hypothesis is a statement that assumes a particular statistical model or distribution for the data. It is often used in statistical analysis to test the significance of a particular result.
A composite hypothesis is a statement that assumes more than one condition or outcome. It can be divided into several sub-hypotheses, each of which represents a different possible outcome.
An empirical hypothesis is a statement that is based on observed phenomena or data. It is often used in scientific research to develop theories or models that explain the observed phenomena.
A simple hypothesis is a statement that assumes only one outcome or condition. It is often used in scientific research to test a single variable or factor.
A complex hypothesis is a statement that assumes multiple outcomes or conditions. It is often used in scientific research to test the effects of multiple variables or factors on a particular outcome.
Hypotheses are used in various fields to guide research and make predictions about the outcomes of experiments or observations. Here are some examples of how hypotheses are applied in different fields:
Here are the steps to follow when writing a hypothesis:
The first step is to identify the research question that you want to answer through your study. This question should be clear, specific, and focused. It should be something that can be investigated empirically and that has some relevance or significance in the field.
Before writing your hypothesis, it’s essential to conduct a thorough literature review to understand what is already known about the topic. This will help you to identify the research gap and formulate a hypothesis that builds on existing knowledge.
The next step is to identify the variables involved in the research question. A variable is any characteristic or factor that can vary or change. There are two types of variables: independent and dependent. The independent variable is the one that is manipulated or changed by the researcher, while the dependent variable is the one that is measured or observed as a result of the independent variable.
Based on the research question and the variables involved, you can now formulate your hypothesis. A hypothesis should be a clear and concise statement that predicts the relationship between the variables. It should be testable through empirical research and based on existing theory or evidence.
The null hypothesis is the opposite of the alternative hypothesis, which is the hypothesis that you are testing. The null hypothesis states that there is no significant difference or relationship between the variables. It is important to write the null hypothesis because it allows you to compare your results with what would be expected by chance.
After formulating the hypothesis, it’s important to refine it and make it more precise. This may involve clarifying the variables, specifying the direction of the relationship, or making the hypothesis more testable.
Here are a few examples of hypotheses in different fields:
The purpose of a hypothesis is to provide a testable explanation for an observed phenomenon or a prediction of a future outcome based on existing knowledge or theories. A hypothesis is an essential part of the scientific method and helps to guide the research process by providing a clear focus for investigation. It enables scientists to design experiments or studies to gather evidence and data that can support or refute the proposed explanation or prediction.
The formulation of a hypothesis is based on existing knowledge, observations, and theories, and it should be specific, testable, and falsifiable. A specific hypothesis helps to define the research question, which is important in the research process as it guides the selection of an appropriate research design and methodology. Testability of the hypothesis means that it can be proven or disproven through empirical data collection and analysis. Falsifiability means that the hypothesis should be formulated in such a way that it can be proven wrong if it is incorrect.
In addition to guiding the research process, the testing of hypotheses can lead to new discoveries and advancements in scientific knowledge. When a hypothesis is supported by the data, it can be used to develop new theories or models to explain the observed phenomenon. When a hypothesis is not supported by the data, it can help to refine existing theories or prompt the development of new hypotheses to explain the phenomenon.
Here are some common situations in which hypotheses are used:
Here are some common characteristics of a hypothesis:
Hypotheses have several advantages in scientific research and experimentation:
Some Limitations of the Hypothesis are as follows:
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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
Predictions typically arise from a thorough knowledge of the research literature, curiosity about real-world problems or implications, and integrating this to advance theory. They build on existing literature while providing new insight.
Alternative hypothesis.
The research hypothesis is often called the alternative or experimental hypothesis in experimental research.
It typically suggests a potential relationship between two key variables: the independent variable, which the researcher manipulates, and the dependent variable, which is measured based on those changes.
The alternative hypothesis states a relationship exists between the two variables being studied (one variable affects the other).
A hypothesis is a testable statement or prediction about the relationship between two or more variables. It is a key component of the scientific method. Some key points about hypotheses:
In summary, a hypothesis is a precise, testable statement of what researchers expect to happen in a study and why. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.
An experimental hypothesis predicts what change(s) will occur in the dependent variable when the independent variable is manipulated.
It states that the results are not due to chance and are significant in supporting the theory being investigated.
The alternative hypothesis can be directional, indicating a specific direction of the effect, or non-directional, suggesting a difference without specifying its nature. It’s what researchers aim to support or demonstrate through their study.
The null hypothesis states no relationship exists between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to manipulating the independent variable.
It states results are due to chance and are not significant in supporting the idea being investigated.
The null hypothesis, positing no effect or relationship, is a foundational contrast to the research hypothesis in scientific inquiry. It establishes a baseline for statistical testing, promoting objectivity by initiating research from a neutral stance.
Many statistical methods are tailored to test the null hypothesis, determining the likelihood of observed results if no true effect exists.
This dual-hypothesis approach provides clarity, ensuring that research intentions are explicit, and fosters consistency across scientific studies, enhancing the standardization and interpretability of research outcomes.
A non-directional hypothesis, also known as a two-tailed hypothesis, predicts that there is a difference or relationship between two variables but does not specify the direction of this relationship.
It merely indicates that a change or effect will occur without predicting which group will have higher or lower values.
For example, “There is a difference in performance between Group A and Group B” is a non-directional hypothesis.
A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e., greater, smaller, less, more)
It specifies whether one variable is greater, lesser, or different from another, rather than just indicating that there’s a difference without specifying its nature.
For example, “Exercise increases weight loss” is a directional hypothesis.
The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory or hypothesis to be considered scientific, it must be testable and irrefutable.
Falsifiability emphasizes that scientific claims shouldn’t just be confirmable but should also have the potential to be proven wrong.
It means that there should exist some potential evidence or experiment that could prove the proposition false.
However many confirming instances exist for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.
For Popper, science should attempt to disprove a theory rather than attempt to continually provide evidence to support a research hypothesis.
Hypotheses make probabilistic predictions. They state the expected outcome if a particular relationship exists. However, a study result supporting a hypothesis does not definitively prove it is true.
All studies have limitations. There may be unknown confounding factors or issues that limit the certainty of conclusions. Additional studies may yield different results.
In science, hypotheses can realistically only be supported with some degree of confidence, not proven. The process of science is to incrementally accumulate evidence for and against hypothesized relationships in an ongoing pursuit of better models and explanations that best fit the empirical data. But hypotheses remain open to revision and rejection if that is where the evidence leads.
We can never 100% prove the alternative hypothesis. Instead, we see if we can disprove, or reject the null hypothesis.
If we reject the null hypothesis, this doesn’t mean that our alternative hypothesis is correct but does support the alternative/experimental hypothesis.
Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.
Consider a hypothesis many teachers might subscribe to: students work better on Monday morning than on Friday afternoon (IV=Day, DV= Standard of work).
Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and a Friday afternoon and then measuring their immediate recall of the material covered in each session, we would end up with the following:
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Published on 6 May 2022 by Shona McCombes .
A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.
What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.
A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.
A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).
Hypotheses propose a relationship between two or more variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.
In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .
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.
Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.
At this stage, you might construct a conceptual framework to identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise more complex constructs.
Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.
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:
To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable.
In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.
If you are comparing two groups, the hypothesis can state what difference you expect to find between them.
If your research involves statistical hypothesis testing , you will also have to write a null hypothesis. The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .
Research question | Hypothesis | Null hypothesis |
---|---|---|
What are the health benefits of eating an apple a day? | Increasing apple consumption in over-60s will result in decreasing frequency of doctor’s visits. | Increasing apple consumption in over-60s will have no effect on frequency of doctor’s visits. |
Which airlines have the most delays? | Low-cost airlines are more likely to have delays than premium airlines. | Low-cost and premium airlines are equally likely to have delays. |
Can flexible work arrangements improve job satisfaction? | Employees who have flexible working hours will report greater job satisfaction than employees who work fixed hours. | There is no relationship between working hour flexibility and job satisfaction. |
How effective is secondary school sex education at reducing teen pregnancies? | Teenagers who received sex education lessons throughout secondary school will have lower rates of unplanned pregnancy than teenagers who did not receive any sex education. | Secondary school sex education has no effect on teen pregnancy rates. |
What effect does daily use of social media have on the attention span of under-16s? | There is a negative correlation between time spent on social media and attention span in under-16s. | There is no relationship between social media use and attention span in under-16s. |
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).
A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).
A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.
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McCombes, S. (2022, May 06). How to Write a Strong Hypothesis | Guide & Examples. Scribbr. Retrieved 3 September 2024, from https://www.scribbr.co.uk/research-methods/hypothesis-writing/
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Updated December 26, 2023
A research hypothesis is a statement that a researcher makes at the beginning of their research to outline what they expect the outcome to be.
If the hypothesis is “ More air pollution in an area can lead to more respiratory diseases ,” researchers expect that an increase in air pollution will cause more respiratory diseases in that area.
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This hypothesis is needed because it provides focus, structure, and purpose to research, helping researchers test their ideas and make meaningful conclusions based on evidence gathered during their study.
How to write a research hypothesis.
Research vs. null vs. statistical hypothesis, key highlights.
Detailed explanation of each type is as follows:
This type looks at how two variables might be related to each other. These variables are the dependent variable and independent variable. A dependent variable is a factor that changes with the changes in the independent variable.
Suppose you want to study the relationship between studying for long hours and grades. In this relationship, grades are the dependent variable, and hours of study are the independent variable, as getting a high or low grade depends on how much you study. And your simple hypothesis could be: “ More study time leads to higher grades .”
Unlike the simple hypothesis, a complex hypothesis predicts a relationship between multiple variables.
Imagine you want to understand how sleep, diet, and exercise affect health. In this case, you have one dependent variable, health, and three independent variables – sleep, diet, and exercise. Your complex hypothesis can be something like: “ A combination of enough sleep, a balanced diet, and regular exercise positively impacts overall health. “
This hypothesis assumes no relationship between variables. It is a negative statement. It’s usually the opposite of your actual hypothesis.
Suppose you are studying whether shoe size affects intelligence; the null hypothesis would say: “ There is no association between shoe size and intelligence. “
This is the opposite of the null hypothesis. It is a statement specifying a relationship between variables.
Suppose you are researching the effect of water intake on memory. An alternative hypothesis could be: “ Increased water intake improves memory performance. “
A directional hypothesis predicts the specific direction or nature of the relationship between two or more variables.
Let’s say you want to investigate the effect of practicing an instrument on musical skills. A directional hypothesis could be something like: “ Increased practice time improves musical skill. ” In this case, it is clear how one variable impacts the other.
In a non-directional hypothesis, a researcher states that two variables are related but doesn’t specify how.
Suppose you are researching the relationship between caffeine intake and heart rate. A non-directional hypothesis might state: “ There is a relationship between caffeine intake and heart rate. ” This hypothesis doesn’t tell you if caffeine intake affects the heart rate or if the heart rate affects your caffeine intake.
This hypothesis focuses on a relationship between variables but doesn’t claim that one causes the other.
Imagine you want to study if TV watching and increased snacking are related. An associative hypothesis might state: “ Watching more TV is related to increased snacking .”
On the other hand, a causal hypothesis suggests that the changes in one thing directly cause changes in another.
If you are studying sunlight exposure and vitamin D levels, a causal hypothesis could be: “ Lack of sunlight exposure causes vitamin D deficiency. “
A research hypothesis should have the following characteristics:
It’s important for research to have a research hypothesis because of the following reasons:
Below is the step-by-step guide to writing a research hypothesis.
Start by identifying what you want to research. Say, for instance, you are interested in understanding the relationship between AI and Productivity; this will form the basis of your research question. Your research question could be:
In the above example, the two variables are AI integration and employee productivity. Now, define which variable is dependent and which one is independent. The independent variable is the one you think will influence, and the dependent variable is the one that will be influenced.
Before you formulate your research hypothesis, you need to find out what past research on this subject is saying. This will help you understand what direction your research might take.
Based on past research, you can now write a clear and specific statement predicting how your dependent and independent variables are connected. Now, write down your research and null hypothesis.
Once you have developed your alternative/research and null hypothesis, your next task is to test your research hypothesis. Here’s how you do that:
Decide how you will gather information or conduct experiments to test your hypothesis. Determine what tools or methods you will use, the research population, the research sample, sample size, etc.
Carry out your experiments or observations and gather data related to your hypothesis. For example, if you are studying the impact of study time on grades, write down how many hours each student participating in your research spends on studying and the grades they get.
Use statistical tools or other analysis methods to study the collected data.
Based on your analysis, determine if the evidence supports your hypothesis. If the data backs up your prediction, your hypothesis is supported.
Share your results with others through reports or presentations, explaining how your experiments or observations relate to your hypothesis.
Let’s take the example of Dr. Lily Perry, a researcher from New York City. She wants to investigate if there is a relationship between respiratory diseases and air pollution in New York.
She starts by creating her research hypothesis and null hypothesis.
Dr. Perry followed a detailed plan to do her research:
After an intensive three-year study, Dr. Perry found interesting results:
Based on these results, Dr. Perry concluded that: There is a correlation between increased air pollution and respiratory diseases in New York.
She recommended the following:
Following are the main advantages and disadvantages of a research hypothesis
It gives your research a specific direction. | It can stop you from exploring all aspects of the study. |
It helps you predict the outcome of your study. | It can cause bias as you already have an outcome in mind. |
It assists in finding an appropriate data collection method. | You might need to revise your hypothesis based on the results of the study. |
The following are the main differences between research, null, and statistical hypothesis.
States the expected relationship between two or more variables. | Assumes there is no relationship between the variables involved in a study. | A mathematical explanation of the relationship between variables. | |
Individuals exercising regularly have a lower risk of heart disease. | There is no link between exercise and heart diseases. | Individuals exercising regularly have a lower resting heart rate than those who do not. | |
To prove a certain relationship exists between the variables. | To prove the variables are not related to each other. | To be proven using statistical methods. | |
Usually states how two variables are related. | Has no direction and emphasizes there is no correlation. | Could be directional as well as non-directional based on the context. | |
Needs to be tested through statistical and non-statistical methods. | Assumed true until disproven by research. | Is tested with statistical methods. |
Formulating a research hypothesis is usually the first step in conducting any research. However, it is important to know that your hypothesis might be disproven on occasion as well. The purpose of the research is to determine if your predictions about a specific relationship hold in light of evidence.
Q1. how long should a research hypothesis be.
Answer: A good research hypothesis should be just one or two sentences. For example: Increasing the amount of water that a cucumber plant receives will lead to increased production.
Answer: In the research paper, the hypothesis is usually placed after the introduction section. The introduction section is added after the background section and before the research methodology.
Answer: To understand this concept, let’s use an example. Let’s say you want to investigate whether there is a difference in the average marks of students in four different divisions. For this, you can use ANOVA (it helps determine if there is a significant difference between the means of three or more samples). So, your research hypothesis would be: There is a difference in the average scores of students in the four divisions. Your null hypothesis would be: There is no difference in the average scores of students in the four divisions. To test these hypotheses, you would collect data (marks of the students) from the four divisions. You would then analyze the data using ANOVA and determine whether you should accept the research hypothesis and reject the null hypothesis or vice versa.
Answer: Qualitative and descriptive research typically do not have a hypothesis. Instead, they have research questions to help the researcher conduct a detailed analysis.
Examples of research questions:
Answer: A research question is what you want to explore, while a research hypothesis is what you expect the outcome of the study to be.
Answer: “ Increased exercise leads to improved heart health ” is an example of a strong hypothesis as it predicts a clear relationship between variables. Furthermore, it is possible to test the hypothesis. On the other hand, “ Apples are better than oranges ” is an example of a bad or poor hypothesis as it is a subjective statement and can’t be tested.
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Learning objectives.
Before describing how to develop a hypothesis it is imporant to distinguish betwee a theory and a hypothesis. A theory is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition. He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.
Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.
A hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observation before we can develop a broader theory.
Theories and hypotheses always have this if-then relationship. “ If drive theory is correct, then cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.
But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this question is an interesting one on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.
Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [1] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the number of examples they bring to mind and the other was that people base their judgments on how easily they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.
The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). A researcher begins with a set of phenomena and either constructs a theory to explain or interpret them or chooses an existing theory to work with. He or she then makes a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researcher then conducts an empirical study to test the hypothesis. Finally, he or she reevaluates the theory in light of the new results and revises it if necessary. This process is usually conceptualized as a cycle because the researcher can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 2.2 shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.
Figure 2.2 Hypothetico-Deductive Method Combined With the General Model of Scientific Research in Psychology Together they form a model of theoretically motivated research.
As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [2] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans (Zajonc & Sales, 1966) [3] in many other studies afterward).
When you write your research report or plan your presentation, be aware that there are two basic ways that researchers usually include theory. The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more existing theories, derive a hypothesis from one of those theories, test the hypothesis in a new study, and finally reevaluate the theory. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.
To use theories in your research will not only give you guidance in coming up with experiment ideas and possible projects, but it lends legitimacy to your work. Psychologists have been interested in a variety of human behaviors and have developed many theories along the way. Using established theories will help you break new ground as a researcher, not limit you from developing your own ideas.
There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use inductive reasoning which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that really it does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.
By: Derek Jansen (MBA) | Reviewed By: Dr Eunice Rautenbach | June 2020
If you’re new to the world of research, or it’s your first time writing a dissertation or thesis, you’re probably noticing that the words “research hypothesis” and “scientific hypothesis” are used quite a bit, and you’re wondering what they mean in a research context .
“Hypothesis” is one of those words that people use loosely, thinking they understand what it means. However, it has a very specific meaning within academic research. So, it’s important to understand the exact meaning before you start hypothesizing.
Let’s start with the general definition of a hypothesis (not a research hypothesis or scientific hypothesis), according to the Cambridge Dictionary:
Hypothesis: an idea or explanation for something that is based on known facts but has not yet been proved.
In other words, it’s a statement that provides an explanation for why or how something works, based on facts (or some reasonable assumptions), but that has not yet been specifically tested . For example, a hypothesis might look something like this:
Hypothesis: sleep impacts academic performance.
This statement predicts that academic performance will be influenced by the amount and/or quality of sleep a student engages in – sounds reasonable, right? It’s based on reasonable assumptions , underpinned by what we currently know about sleep and health (from the existing literature). So, loosely speaking, we could call it a hypothesis, at least by the dictionary definition.
But that’s not good enough…
Unfortunately, that’s not quite sophisticated enough to describe a research hypothesis (also sometimes called a scientific hypothesis), and it wouldn’t be acceptable in a dissertation, thesis or research paper . In the world of academic research, a statement needs a few more criteria to constitute a true research hypothesis .
A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes – specificity , clarity and testability .
Let’s take a look at these more closely.
A good research hypothesis needs to be extremely clear and articulate about both what’ s being assessed (who or what variables are involved ) and the expected outcome (for example, a difference between groups, a relationship between variables, etc.).
Let’s stick with our sleepy students example and look at how this statement could be more specific and clear.
Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.
As you can see, the statement is very specific as it identifies the variables involved (sleep hours and test grades), the parties involved (two groups of students), as well as the predicted relationship type (a positive relationship). There’s no ambiguity or uncertainty about who or what is involved in the statement, and the expected outcome is clear.
Contrast that to the original hypothesis we looked at – “Sleep impacts academic performance” – and you can see the difference. “Sleep” and “academic performance” are both comparatively vague , and there’s no indication of what the expected relationship direction is (more sleep or less sleep). As you can see, specificity and clarity are key.
A statement must be testable to qualify as a research hypothesis. In other words, there needs to be a way to prove (or disprove) the statement. If it’s not testable, it’s not a hypothesis – simple as that.
For example, consider the hypothesis we mentioned earlier:
Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.
We could test this statement by undertaking a quantitative study involving two groups of students, one that gets 8 or more hours of sleep per night for a fixed period, and one that gets less. We could then compare the standardised test results for both groups to see if there’s a statistically significant difference.
Again, if you compare this to the original hypothesis we looked at – “Sleep impacts academic performance” – you can see that it would be quite difficult to test that statement, primarily because it isn’t specific enough. How much sleep? By who? What type of academic performance?
So, remember the mantra – if you can’t test it, it’s not a hypothesis 🙂
You’re still with us? Great! Let’s recap and pin down a clear definition of a hypothesis.
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 hypotheses but you’ll also ensure a clear focus for your entire research project.
You may have also heard the terms null hypothesis , alternative hypothesis, or H-zero thrown around. At a simple level, the null hypothesis is the counter-proposal to the original hypothesis.
For example, if the hypothesis predicts that there is a relationship between two variables (for example, sleep and academic performance), the null hypothesis would predict that there is no relationship between those variables.
At a more technical level, the null hypothesis proposes that no statistical significance exists in a set of given observations and that any differences are due to chance alone.
And there you have it – hypotheses in a nutshell.
If you have any questions, be sure to leave a comment below and we’ll do our best to help you. If you need hands-on help developing and testing your hypotheses, consider our private coaching service , where we hold your hand through the research journey.
Very useful information. I benefit more from getting more information in this regard.
Very great insight,educative and informative. Please give meet deep critics on many research data of public international Law like human rights, environment, natural resources, law of the sea etc
In a book I read a distinction is made between null, research, and alternative hypothesis. As far as I understand, alternative and research hypotheses are the same. Can you please elaborate? Best Afshin
This is a self explanatory, easy going site. I will recommend this to my friends and colleagues.
Very good definition. How can I cite your definition in my thesis? Thank you. Is nul hypothesis compulsory in a research?
It’s a counter-proposal to be proven as a rejection
Please what is the difference between alternate hypothesis and research hypothesis?
It is a very good explanation. However, it limits hypotheses to statistically tasteable ideas. What about for qualitative researches or other researches that involve quantitative data that don’t need statistical tests?
In qualitative research, one typically uses propositions, not hypotheses.
could you please elaborate it more
I’ve benefited greatly from these notes, thank you.
This is very helpful
well articulated ideas are presented here, thank you for being reliable sources of information
Excellent. Thanks for being clear and sound about the research methodology and hypothesis (quantitative research)
I have only a simple question regarding the null hypothesis. – Is the null hypothesis (Ho) known as the reversible hypothesis of the alternative hypothesis (H1? – How to test it in academic research?
this is very important note help me much more
Hi” best wishes to you and your very nice blog”
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The story of a research study begins by asking a question. Researchers all around the globe are asking curious questions and formulating research hypothesis. However, whether the research study provides an effective conclusion depends on how well one develops a good research hypothesis. Research hypothesis examples could help researchers get an idea as to how to write a good research hypothesis.
This blog will help you understand what is a research hypothesis, its characteristics and, how to formulate a research hypothesis
Table of Contents
Hypothesis is an assumption or an idea proposed for the sake of argument so that it can be tested. It is a precise, testable statement of what the researchers predict will be outcome of the study. Hypothesis usually involves proposing a relationship between two variables: the independent variable (what the researchers change) and the dependent variable (what the research measures).
Research hypothesis is a statement that introduces a research question and proposes an expected result. It is an integral part of the scientific method that forms the basis of scientific experiments. Therefore, you need to be careful and thorough when building your research hypothesis. A minor flaw in the construction of your hypothesis could have an adverse effect on your experiment. In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment).
As the hypothesis is specific, there is a testable prediction about what you expect to happen in a study. You may consider drawing hypothesis from previously published research based on the theory.
A good research hypothesis involves more effort than just a guess. In particular, your hypothesis may begin with a question that could be further explored through background research.
To help you formulate a promising research hypothesis, you should ask yourself the following questions:
The questions listed above can be used as a checklist to make sure your hypothesis is based on a solid foundation. Furthermore, it can help you identify weaknesses in your hypothesis and revise it if necessary.
How to formulate a research hypothesis.
A testable hypothesis is not a simple statement. It is rather an intricate statement that needs to offer a clear introduction to a scientific experiment, its intentions, and the possible outcomes. However, there are some important things to consider when building a compelling hypothesis.
Make sure that the hypothesis clearly defines the topic and the focus of the experiment.
Follow this template: If a specific action is taken, then a certain outcome is expected.
Independent variables are the ones that are manipulated, controlled, or changed. Independent variables are isolated from other factors of the study.
Dependent variables , as the name suggests are dependent on other factors of the study. They are influenced by the change in independent variable.
Evaluate assumptions, predictions, and evidence rigorously to refine your understanding.
The types of research hypothesis are stated below:
It predicts the relationship between a single dependent variable and a single independent variable.
It predicts the relationship between two or more independent and dependent variables.
It specifies the expected direction to be followed to determine the relationship between variables and is derived from theory. Furthermore, it implies the researcher’s intellectual commitment to a particular outcome.
It does not predict the exact direction or nature of the relationship between the two variables. The non-directional hypothesis is used when there is no theory involved or when findings contradict previous research.
The associative hypothesis defines interdependency between variables. A change in one variable results in the change of the other variable. On the other hand, the causal hypothesis proposes an effect on the dependent due to manipulation of the independent variable.
Null hypothesis states a negative statement to support the researcher’s findings that there is no relationship between two variables. There will be no changes in the dependent variable due the manipulation of the independent variable. Furthermore, it states results are due to chance and are not significant in terms of supporting the idea being investigated.
It states that there is a relationship between the two variables of the study and that the results are significant to the research topic. An experimental hypothesis predicts what changes will take place in the dependent variable when the independent variable is manipulated. Also, it states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.
Research Hypothesis Example 1 The greater number of coal plants in a region (independent variable) increases water pollution (dependent variable). If you change the independent variable (building more coal factories), it will change the dependent variable (amount of water pollution).
Research Hypothesis Example 2 What is the effect of diet or regular soda (independent variable) on blood sugar levels (dependent variable)? If you change the independent variable (the type of soda you consume), it will change the dependent variable (blood sugar levels)
You should not ignore the importance of the above steps. The validity of your experiment and its results rely on a robust testable hypothesis. Developing a strong testable hypothesis has few advantages, it compels us to think intensely and specifically about the outcomes of a study. Consequently, it enables us to understand the implication of the question and the different variables involved in the study. Furthermore, it helps us to make precise predictions based on prior research. Hence, forming a hypothesis would be of great value to the research. Here are some good examples of testable hypotheses.
More importantly, you need to build a robust testable research hypothesis for your scientific experiments. A testable hypothesis is a hypothesis that can be proved or disproved as a result of experimentation.
To devise and perform an experiment using scientific method, you need to make sure that your hypothesis is testable. To be considered testable, some essential criteria must be met:
Without these criteria, the hypothesis and the results will be vague. As a result, the experiment will not prove or disprove anything significant.
What are your experiences with building hypotheses for scientific experiments? What challenges did you face? How did you overcome these challenges? Please share your thoughts with us in the comments section.
The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a ‘if-then’ structure. 3. Defining the variables: Define the variables as Dependent or Independent based on their dependency to other factors. 4. Scrutinizing the hypothesis: Identify the type of your hypothesis
Hypothesis testing is a statistical tool which is used to make inferences about a population data to draw conclusions for a particular hypothesis.
Hypothesis in statistics is a formal statement about the nature of a population within a structured framework of a statistical model. It is used to test an existing hypothesis by studying a population.
Research hypothesis is a statement that introduces a research question and proposes an expected result. It forms the basis of scientific experiments.
The different types of hypothesis in research are: • Null hypothesis: Null hypothesis is a negative statement to support the researcher’s findings that there is no relationship between two variables. • Alternate hypothesis: Alternate hypothesis predicts the relationship between the two variables of the study. • Directional hypothesis: Directional hypothesis specifies the expected direction to be followed to determine the relationship between variables. • Non-directional hypothesis: Non-directional hypothesis does not predict the exact direction or nature of the relationship between the two variables. • Simple hypothesis: Simple hypothesis predicts the relationship between a single dependent variable and a single independent variable. • Complex hypothesis: Complex hypothesis predicts the relationship between two or more independent and dependent variables. • Associative and casual hypothesis: Associative and casual hypothesis predicts the relationship between two or more independent and dependent variables. • Empirical hypothesis: Empirical hypothesis can be tested via experiments and observation. • Statistical hypothesis: A statistical hypothesis utilizes statistical models to draw conclusions about broader populations.
Wow! You really simplified your explanation that even dummies would find it easy to comprehend. Thank you so much.
Thanks a lot for your valuable guidance.
I enjoy reading the post. Hypotheses are actually an intrinsic part in a study. It bridges the research question and the methodology of the study.
Useful piece!
This is awesome.Wow.
It very interesting to read the topic, can you guide me any specific example of hypothesis process establish throw the Demand and supply of the specific product in market
Nicely explained
It is really a useful for me Kindly give some examples of hypothesis
It was a well explained content ,can you please give me an example with the null and alternative hypothesis illustrated
clear and concise. thanks.
So Good so Amazing
Good to learn
Thanks a lot for explaining to my level of understanding
Explained well and in simple terms. Quick read! Thank you
It awesome. It has really positioned me in my research project
Brief and easily digested
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Research hypothesis.
A research hypothesis is referred to as a scientific hypothesis. This is a clear, specific, and testable statement that predicts the expected result in a scientific study. It is a prediction, reasonable guess, and logical supposition about the relationship between the variables. A research hypothesis is an integral and central part of research whether it is exploratory or explanatory, qualitative or quantitative. It creates the base of scientific experiments. So, you must be very careful while building any hypothesis.
A hypothesis can be correct or wrong. It is tested through experiments or research to determine whether it is correct or incorrect.
There are major functions of research hypothesis that are as follow:
Following are the sources of the hypothesis:
Following are the characteristics of an effective research hypothesis:
Following are the types of research hypotheses.
It shows a relationship between a single dependent variable and an independent variable. For instance, if you take in more carbs and fats, you will gain obesity. Here taking more carbs and fats are an independent variable and gaining weight is the dependent variable.
It predicts the relationship between two or more independent variables and dependent variables. For example, we can say that taking in more carbs and fats can cause obesity along with other problems like high blood pressure, heart disease, and so on.
Typically, directional hypotheses are derived from theory. This type of hypothesis shows the researcher’s intellectual commitment towards a specific outcome. The researcher predicts the existence and nature of a relationship between variables.
The non-directional hypothesis is used when there is no theory and the findings of studies are contradictory. It shows the relationship between two variables but does not set down the expected direction or nature of the relationship.
Null hypotheses are made when there is no empirical and adequate theoretical information to show a hypothesis. The null hypothesis negates the relationship between variables. It is denoted by Ho. This hypothesis is made when the researcher wants to reject or disapprove the null hypothesis. It is contrary to what an experimenter or investigator expects. The purpose is to confirm the existence of a relationship between the variables.
The null hypothesis can be:
1. Alternative hypothesis
When a hypothesis is rejected, then another hypothesis is made to be tested and show the desired results. This is called an alternative hypothesis. It is opposite to the null hypothesis and is made to disprove that hypothesis. This hypothesis is denoted by H1.
2. Statistical hypothesis
As the name mentions, this hypothesis has the quality to be verified statistically. It is tested by using quantitative techniques. The variables in this hypothesis are quantifiable and can also transform into quantifiable indicators to verify it statistically.
This hypothesis is used when a theory is tested with observation and experiment. It is just a notion or idea. This hypothesis goes through trial and error by changing independent variables. The series of trial and error helps to find the best result. The outcomes of these experiments can be proven over time.
The associative hypothesis shows interdependency between variables. Any change in one variable causes the change in another variable. Whereas, the causal hypothesis shows a cause and effect between variables.
How to formulate a research hypothesis
There are some important points you must consider while formulating a hypothesis:
The first and foremost thing for creating a research hypothesis is to generate a research question. The question should be specific, focused, and researchable within the limitations of your project.
Now try to find the answer to your question. The initial answer must be based on previous knowledge about the topic. Concern theories and previous studies and try to form assumptions about what you will find in your research.
Create a conceptual framework about different variables you are going to study and the relationships between them.
Now you have an idea of what you are expecting to find. Make a clear and concise answer to the question.
Now check whether your hypothesis is testable. There must be clear definitions of your hypothesis while phrasing. It should contain:
The particular group being studied.
The predicted result of the analysis or experiment
To recognize the variables, write a prediction in (if-then) form. Like, if a particular action is taken, a certain result is expected. The first part of the phrase shows the independent variable while the second part shows the dependent variable.
If the research requires statistical hypothesis testing, you must have to make a null hypothesis and an alternative hypothesis.
Now test your hypothesis through observations, techniques, and experiments by keeping necessary things and resources in consideration.
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Rajiv S. Jhangiani; I-Chant A. Chiang; Carrie Cuttler; and Dana C. Leighton
Before describing how to develop a hypothesis, it is important to distinguish between a theory and a hypothesis. A theory is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition (1965) [1] . He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.
Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.
A hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observations before we can develop a broader theory.
Theories and hypotheses always have this if-then relationship. “ If drive theory is correct, then cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.
But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this question is an interesting one on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.
Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [2] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the number of examples they bring to mind and the other was that people base their judgments on how easily they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.
The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers begin with a set of phenomena and either construct a theory to explain or interpret them or choose an existing theory to work with. They then make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary. This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 2.3 shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.
As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [3] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans [Zajonc & Sales, 1966] [4] in many other studies afterward).
When you write your research report or plan your presentation, be aware that there are two basic ways that researchers usually include theory. The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more existing theories, derive a hypothesis from one of those theories, test the hypothesis in a new study, and finally reevaluate the theory. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.
To use theories in your research will not only give you guidance in coming up with experiment ideas and possible projects, but it lends legitimacy to your work. Psychologists have been interested in a variety of human behaviors and have developed many theories along the way. Using established theories will help you break new ground as a researcher, not limit you from developing your own ideas.
There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use inductive reasoning which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that it really does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.
A coherent explanation or interpretation of one or more phenomena.
A specific prediction about a new phenomenon that should be observed if a particular theory is accurate.
A cyclical process of theory development, starting with an observed phenomenon, then developing or using a theory to make a specific prediction of what should happen if that theory is correct, testing that prediction, refining the theory in light of the findings, and using that refined theory to develop new hypotheses, and so on.
The ability to test the hypothesis using the methods of science and the possibility to gather evidence that will disconfirm the hypothesis if it is indeed false.
Developing a Hypothesis Copyright © by Rajiv S. Jhangiani; I-Chant A. Chiang; Carrie Cuttler; and Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.
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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 ability to be supported or refuted through observation and experimentation. The notion of the scientific hypothesis as both falsifiable and testable was advanced in the mid-20th century by Austrian-born British philosopher Karl Popper .
The formulation and testing of a hypothesis is part of the scientific method , the approach scientists use when attempting to understand and test ideas about natural phenomena. The generation of a hypothesis frequently is described as a creative process and is based on existing scientific knowledge, intuition , or experience. Therefore, although scientific hypotheses commonly are described as educated guesses, they actually are more informed than a guess. In addition, scientists generally strive to develop simple hypotheses, since these are easier to test relative to hypotheses that involve many different variables and potential outcomes. Such complex hypotheses may be developed as scientific models ( see scientific modeling ).
Depending on the results of scientific evaluation, a hypothesis typically is either rejected as false or accepted as true. However, because a hypothesis inherently is falsifiable, even hypotheses supported by scientific evidence and accepted as true are susceptible to rejection later, when new evidence has become available. In some instances, rather than rejecting a hypothesis because it has been falsified by new evidence, scientists simply adapt the existing idea to accommodate the new information. In this sense a hypothesis is never incorrect but only incomplete.
The investigation of scientific hypotheses is an important component in the development of scientific theory . Hence, hypotheses differ fundamentally from theories; whereas the former is a specific tentative explanation and serves as the main tool by which scientists gather data, the latter is a broad general explanation that incorporates data from many different scientific investigations undertaken to explore hypotheses.
Countless hypotheses have been developed and tested throughout the history of science . Several examples include the idea that living organisms develop from nonliving matter, which formed the basis of spontaneous generation , a hypothesis that ultimately was disproved (first in 1668, with the experiments of Italian physician Francesco Redi , and later in 1859, with the experiments of French chemist and microbiologist Louis Pasteur ); the concept proposed in the late 19th century that microorganisms cause certain diseases (now known as germ theory ); and the notion that oceanic crust forms along submarine mountain zones and spreads laterally away from them ( seafloor spreading hypothesis ).
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A hypothesis is an educated guess or prediction of what will happen. In science, a hypothesis proposes a relationship between factors called variables. A good hypothesis relates an independent variable and a dependent variable. The effect on the dependent variable depends on or is determined by what happens when you change the independent variable . While you could consider any prediction of an outcome to be a type of hypothesis, a good hypothesis is one you can test using the scientific method. In other words, you want to propose a hypothesis to use as the basis for an experiment.
A good experimental hypothesis can be written as an if, then statement to establish cause and effect on the variables. If you make a change to the independent variable, then the dependent variable will respond. Here's an example of a hypothesis:
If you increase the duration of light, (then) corn plants will grow more each day.
The hypothesis establishes two variables, length of light exposure, and the rate of plant growth. An experiment could be designed to test whether the rate of growth depends on the duration of light. The duration of light is the independent variable, which you can control in an experiment . The rate of plant growth is the dependent variable, which you can measure and record as data in an experiment.
When you have an idea for a hypothesis, it may help to write it out in several different ways. Review your choices and select a hypothesis that accurately describes what you are testing.
It's not wrong or bad if the hypothesis is not supported or is incorrect. Actually, this outcome may tell you more about a relationship between the variables than if the hypothesis is supported. You may intentionally write your hypothesis as a null hypothesis or no-difference hypothesis to establish a relationship between the variables.
For example, the hypothesis:
The rate of corn plant growth does not depend on the duration of light.
This can be tested by exposing corn plants to different length "days" and measuring the rate of plant growth. A statistical test can be applied to measure how well the data support the hypothesis. If the hypothesis is not supported, then you have evidence of a relationship between the variables. It's easier to establish cause and effect by testing whether "no effect" is found. Alternatively, if the null hypothesis is supported, then you have shown the variables are not related. Either way, your experiment is a success.
Need more examples of how to write a hypothesis ? Here you go:
All research studies involve the use of the scientific method, which is a mathematical and experimental technique used to conduct experiments by developing and testing a hypothesis or a prediction about an outcome. Simply put, a hypothesis is a suggested solution to a problem. It includes elements that are expressed in terms of relationships with each other to explain a condition or an assumption that hasn’t been verified using facts. 1 The typical steps in a scientific method include developing such a hypothesis, testing it through various methods, and then modifying it based on the outcomes of the experiments.
A research hypothesis can be defined as a specific, testable prediction about the anticipated results of a study. 2 Hypotheses help guide the research process and supplement the aim of the study. After several rounds of testing, hypotheses can help develop scientific theories. 3 Hypotheses are often written as if-then statements.
Here are two hypothesis examples:
Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth. 4
If a company offers flexible work hours, then their employees will be happier at work. 5
A hypothesis expresses an expected relationship between variables in a study and is developed before conducting any research. Hypotheses are not opinions but rather are expected relationships based on facts and observations. They help support scientific research and expand existing knowledge. An incorrectly formulated hypothesis can affect the entire experiment leading to errors in the results so it’s important to know how to formulate a hypothesis and develop it carefully.
A few sources of a hypothesis include observations from prior studies, current research and experiences, competitors, scientific theories, and general conditions that can influence people. Figure 1 depicts the different steps in a research design and shows where exactly in the process a hypothesis is developed. 4
There are seven different types of hypotheses—simple, complex, directional, nondirectional, associative and causal, null, and alternative.
The seven types of hypotheses are listed below: 5 , 6,7
Example: Exercising in the morning every day will increase your productivity.
Example: Spending three hours or more on social media daily will negatively affect children’s mental health and productivity, more than that of adults.
Example: The inclusion of intervention X decreases infant mortality compared to the original treatment.
Example: Cats and dogs differ in the amount of affection they express.
Example: There is a positive association between physical activity levels and overall health.
A causal hypothesis, on the other hand, expresses a cause-and-effect association between variables.
Example: Long-term alcohol use causes liver damage.
Example: Sleep duration does not have any effect on productivity.
Example: Sleep duration affects productivity.
So, what makes a good hypothesis? Here are some important characteristics of a hypothesis. 8,9
The following list mentions some important functions of a hypothesis: 1
To summarize, a hypothesis provides the conceptual elements that complete the known data, conceptual relationships that systematize unordered elements, and conceptual meanings and interpretations that explain the unknown phenomena. 1
Listed below are the main steps explaining how to write a hypothesis. 2,4,5
For example, if you notice that an office’s vending machine frequently runs out of a specific snack, you may predict that more people in the office choose that snack over another.
For example, after observing employees’ break times at work, you could ask “why do more employees take breaks in the morning rather than in the afternoon?”
For example, based on your observations you might state a hypothesis that employees work more efficiently when the air conditioning in the office is set at a lower temperature. However, during your preliminary research you find that this hypothesis was proven incorrect by a prior study.
P opulation: The specific group or individual who is the main subject of the research
I nterest: The main concern of the study/research question
C omparison: The main alternative group
O utcome: The expected results
T ime: Duration of the experiment
Once you’ve finalized your hypothesis statement you would need to conduct experiments to test whether the hypothesis is true or false.
The following table provides examples of different types of hypotheses. 10 ,11
Null | Hyperactivity is not related to eating sugar. |
There is no relationship between height and shoe size. | |
Alternative | Hyperactivity is positively related to eating sugar. |
There is a positive association between height and shoe size. | |
Simple | Students who eat breakfast perform better in exams than students who don’t eat breakfast. |
Reduced screen time improves sleep quality. | |
Complex | People with high-sugar diet and sedentary activity levels are more likely to develop depression. |
Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone. | |
Directional | As job satisfaction increases, the rate of employee turnover decreases. |
Increase in sun exposure increases the risk of skin cancer. | |
Non-directional | College students will perform differently from elementary school students on a memory task. |
Advertising exposure correlates with variations in purchase decisions among consumers. | |
Associative | Hospitals have more sick people in them than other institutions in society. |
Watching TV is related to increased snacking. | |
Causal | Inadequate sleep decreases memory retention. |
Recreational drugs cause psychosis. |
Key takeaways
Here’s a summary of all the key points discussed in this article about how to write a hypothesis.
Hypotheses and research questions have different objectives and structure. The following table lists some major differences between the two. 9
Includes a prediction based on the proposed research | No prediction is made |
Designed to forecast the relationship of and between two or more variables | Variables may be explored |
Closed ended | Open ended, invites discussion |
Used if the research topic is well established and there is certainty about the relationship between the variables | Used for new topics that haven’t been researched extensively. The relationship between different variables is less known |
Here are a few examples to differentiate between a research question and hypothesis.
What is the effect of eating an apple a day by adults aged over 60 years on the frequency of physician visits? | Eating an apple each day, after the age of 60, will result in a reduction of frequency of physician visits |
What is the effect of flexible or fixed working hours on employee job satisfaction? | Workplaces that offer flexible working hours report higher levels of employee job satisfaction than workplaces with fixed hours. |
Does drinking coffee in the morning affect employees’ productivity? | Drinking coffee in the morning improves employees’ productivity. |
Yes, here’s a simple checklist to help you gauge the effectiveness of your hypothesis. 9 1. When writing a hypothesis statement, check if it: 2. Predicts the relationship between the stated variables and the expected outcome. 3. Uses simple and concise language and is not wordy. 4. Does not assume readers’ knowledge about the subject. 5. Has observable, falsifiable, and testable results.
As mentioned earlier in this article, a hypothesis is an assumption or prediction about an association between variables based on observations and simple evidence. These statements are usually generic. Research objectives, on the other hand, are more specific and dictated by hypotheses. The same hypothesis can be tested using different methods and the research objectives could be different in each case. For example, Louis Pasteur observed that food lasts longer at higher altitudes, reasoned that it could be because the air at higher altitudes is cleaner (with fewer or no germs), and tested the hypothesis by exposing food to air cleaned in the laboratory. 12 Thus, a hypothesis is predictive—if the reasoning is correct, X will lead to Y—and research objectives are developed to test these predictions.
Null hypothesis testing is a method to decide between two assumptions or predictions between variables (null and alternative hypotheses) in a statistical relationship in a sample. The null hypothesis, denoted as H 0 , claims that no relationship exists between variables in a population and any relationship in the sample reflects a sampling error or occurrence by chance. The alternative hypothesis, denoted as H 1 , claims that there is a relationship in the population. In every study, researchers need to decide whether the relationship in a sample occurred by chance or reflects a relationship in the population. This is done by hypothesis testing using the following steps: 13 1. Assume that the null hypothesis is true. 2. Determine how likely the sample relationship would be if the null hypothesis were true. This probability is called the p value. 3. If the sample relationship would be extremely unlikely, reject the null hypothesis and accept the alternative hypothesis. If the relationship would not be unlikely, accept the null hypothesis.
To summarize, researchers should know how to write a good hypothesis to ensure that their research progresses in the required direction. A hypothesis is a testable prediction about any behavior or relationship between variables, usually based on facts and observation, and states an expected outcome.
We hope this article has provided you with essential insight into the different types of hypotheses and their functions so that you can use them appropriately in your next research project.
References
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In the realm of scientific research, a hypothesis plays a crucial role in formulating and testing ideas. A good hypothesis serves as the foundation for an experiment or study, guiding the researcher towards meaningful results. In this FAQ-style subsection, we'll explore the characteristics of a good hypothesis, their types, formulation, and more.
Characteristics of Hypothesis. A good hypothesis has the following characteristics. ... As a result of the predictive capacity, hypothesis is the finest guidance for research activities. Closest to things that can be seen A hypothesis must be in intimate contact with objects that may be observed. It is based on observation and does not believe ...
3. Simple hypothesis. A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, "Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking. 4.
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.
A research hypothesis helps test theories. A hypothesis plays a pivotal role in the scientific method by providing a basis for testing existing theories. For example, a hypothesis might test the predictive power of a psychological theory on human behavior. It serves as a great platform for investigation activities.
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 ...
INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...
At the primary level, a hypothesis is the possible and probable explanation of the sequence of happenings or data. Sometimes, hypothesis may emerge from an imagination, common sense or a sudden event. Hypothesis can be a probable answer to the research problem undertaken for study. 4. Hypothesis may not always be true.
The specific group being studied. The predicted outcome of the experiment or analysis. 5. Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.
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 ...
Examples. 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.
Step 5: Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.
Characteristics. A research hypothesis should have the following characteristics: Simple and Clear: A good research hypothesis should make sense, be believable, and be based on past research. Testability: It should be something that can be tested in real life through scientific methods like experiments or observations.; Realistic: Your research hypothesis can't be unrealistic or restricted ...
First, a good hypothesis must be testable and falsifiable. We must be able to test the hypothesis using the methods of science and if you'll recall Popper's falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical.
A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes - specificity, clarity and testability. Let's take a look at these more closely.
The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem. 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a 'if-then' structure.
A research hypothesis is referred to as a scientific hypothesis. This is a clear, specific, and testable statement that predicts the expected result in a scientific study. It is a prediction, reasonable guess, and logical supposition about the relationship between the variables. A research hypothesis is an integral and central part of research ...
Hypotheses in research need to satisfy specific criteria to be considered scientifically rigorous. Here are the most notable qualities of a strong hypothesis: Testability: Ensure the hypothesis allows you to work towards observable and testable results. Brevity and objectivity: Present your hypothesis as a brief statement and avoid wordiness.
First, a good hypothesis must be testable and falsifiable. We must be able to test the hypothesis using the methods of science and if you'll recall Popper's falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical.
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 ...
A hypothesis is an educated guess or prediction of what will happen. In science, a hypothesis proposes a relationship between factors called variables. A good hypothesis relates an independent variable and a dependent variable. The effect on the dependent variable depends on or is determined by what happens when you change the independent variable.
Here are two hypothesis examples: Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth.4. If a company offers flexible work hours, then their employees will be happier at work.5.