hypothesis contributes to the development of

2.4 Developing a Hypothesis

Learning objectives.

Distinguish between a theory and a hypothesis.
Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
Understand the characteristics of a good hypothesis.

Theories and Hypotheses

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.

Theory Testing

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 4.4 Hypothetico-Deductive Method Combined With the General Model of Scientific Research in Psychology Together they form a model of theoretically motivated 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).

Incorporating Theory into Your Research

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.

Characteristics of a Good Hypothesis

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.

Key Takeaways

A theory is broad in nature and explains larger bodies of data. A hypothesis is more specific and makes a prediction about the outcome of a particular study.
Working with theories is not “icing on the cake.” It is a basic ingredient of psychological research.
Like other scientists, psychologists use the hypothetico-deductive method. They construct theories to explain or interpret phenomena (or work with existing theories), derive hypotheses from their theories, test the hypotheses, and then reevaluate the theories in light of the new results.
Practice: Find a recent empirical research report in a professional journal. Read the introduction and highlight in different colors descriptions of theories and hypotheses.
Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61 , 195–202. ↵
Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach. Journal of Personality and Social Psychology, 13 , 83–92. ↵
Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

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Developing a Hypothesis

Rajiv S. Jhangiani; I-Chant A. Chiang; Carrie Cuttler; and Dana C. Leighton

Learning Objectives

Distinguish between a theory and a hypothesis.
Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
Understand the characteristics of a good hypothesis.

Theories and Hypotheses

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.

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.

Theory Testing

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.

hypothesis contributes to the development of

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).

Incorporating Theory into Your Research

Characteristics of a Good Hypothesis

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.

Zajonc, R. B. (1965). Social facilitation. Science, 149 , 269–274 ↵
Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61 , 195–202. ↵
Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach. Journal of Personality and Social Psychology, 13 , 83–92. ↵
Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

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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Hypothesis n., plural: hypotheses [/haɪˈpɑːθəsɪs/] Definition: Testable scientific prediction

Table of Contents

What Is Hypothesis?

A scientific hypothesis is a foundational element of the scientific method . It’s a testable statement proposing a potential explanation for natural phenomena. The term hypothesis means “little theory” . A hypothesis is a short statement that can be tested and gives a possible reason for a phenomenon or a possible link between two variables . In the setting of scientific research, a hypothesis is a tentative explanation or statement that can be proven wrong and is used to guide experiments and empirical research.

It is an important part of the scientific method because it gives a basis for planning tests, gathering data, and judging evidence to see if it is true and could help us understand how natural things work. Several hypotheses can be tested in the real world, and the results of careful and systematic observation and analysis can be used to support, reject, or improve them.

Researchers and scientists often use the word hypothesis to refer to this educated guess . These hypotheses are firmly established based on scientific principles and the rigorous testing of new technology and experiments .

For example, in astrophysics, the Big Bang Theory is a working hypothesis that explains the origins of the universe and considers it as a natural phenomenon. It is among the most prominent scientific hypotheses in the field.

“The scientific method: steps, terms, and examples” by Scishow:

Biology definition: A hypothesis  is a supposition or tentative explanation for (a group of) phenomena, (a set of) facts, or a scientific inquiry that may be tested, verified or answered by further investigation or methodological experiment. It is like a scientific guess . It’s an idea or prediction that scientists make before they do experiments. They use it to guess what might happen and then test it to see if they were right. It’s like a smart guess that helps them learn new things. A scientific hypothesis that has been verified through scientific experiment and research may well be considered a scientific theory .

Etymology: The word “hypothesis” comes from the Greek word “hupothesis,” which means “a basis” or “a supposition.” It combines “hupo” (under) and “thesis” (placing). Synonym: proposition; assumption; conjecture; postulate Compare:   theory See also: null hypothesis

Characteristics Of Hypothesis

A useful hypothesis must have the following qualities:

It should never be written as a question.
You should be able to test it in the real world to see if it’s right or wrong.
It needs to be clear and exact.
It should list the factors that will be used to figure out the relationship.
It should only talk about one thing. You can make a theory in either a descriptive or form of relationship.
It shouldn’t go against any natural rule that everyone knows is true. Verification will be done well with the tools and methods that are available.
It should be written in as simple a way as possible so that everyone can understand it.
It must explain what happened to make an answer necessary.
It should be testable in a fair amount of time.
It shouldn’t say different things.

Sources Of Hypothesis

Sources of hypothesis are:

Patterns of similarity between the phenomenon under investigation and existing hypotheses.
Insights derived from prior research, concurrent observations, and insights from opposing perspectives.
The formulations are derived from accepted scientific theories and proposed by researchers.
In research, it’s essential to consider hypothesis as different subject areas may require various hypotheses (plural form of hypothesis). Researchers also establish a significance level to determine the strength of evidence supporting a hypothesis.
Individual cognitive processes also contribute to the formation of hypotheses.

One hypothesis is a tentative explanation for an observation or phenomenon. It is based on prior knowledge and understanding of the world, and it can be tested by gathering and analyzing data. Observed facts are the data that are collected to test a hypothesis. They can support or refute the hypothesis.

For example, the hypothesis that “eating more fruits and vegetables will improve your health” can be tested by gathering data on the health of people who eat different amounts of fruits and vegetables. If the people who eat more fruits and vegetables are healthier than those who eat less fruits and vegetables, then the hypothesis is supported.

Hypotheses are essential for scientific inquiry. They help scientists to focus their research, to design experiments, and to interpret their results. They are also essential for the development of scientific theories.

Types Of Hypothesis

In research, you typically encounter two types of hypothesis: the alternative hypothesis (which proposes a relationship between variables) and the null hypothesis (which suggests no relationship).

Simple Hypothesis

It illustrates the association between one dependent variable and one independent variable. For instance, if you consume more vegetables, you will lose weight more quickly. Here, increasing vegetable consumption is the independent variable, while weight loss is the dependent variable.

Complex Hypothesis

It exhibits the relationship between at least two dependent variables and at least two independent variables. Eating more vegetables and fruits results in weight loss, radiant skin, and a decreased risk of numerous diseases, including heart disease.

Directional Hypothesis

It shows that a researcher wants to reach a certain goal. The way the factors are related can also tell us about their nature. For example, four-year-old children who eat well over a time of five years have a higher IQ than children who don’t eat well. This shows what happened and how it happened.

Non-directional Hypothesis

When there is no theory involved, it is used. It is a statement that there is a connection between two variables, but it doesn’t say what that relationship is or which way it goes.

Null Hypothesis

It says something that goes against the theory. It’s a statement that says something is not true, and there is no link between the independent and dependent factors. “H 0 ” represents the null hypothesis.

Associative and Causal Hypothesis

When a change in one variable causes a change in the other variable, this is called the associative hypothesis . The causal hypothesis, on the other hand, says that there is a cause-and-effect relationship between two or more factors.

Examples Of Hypothesis

Examples of simple hypotheses:

Students who consume breakfast before taking a math test will have a better overall performance than students who do not consume breakfast.
Students who experience test anxiety before an English examination will get lower scores than students who do not experience test anxiety.
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, is a statement that suggests that drivers who talk on the phone while driving are more likely to make mistakes.

Examples of a complex hypothesis:

Individuals who consume a lot of sugar and don’t get much exercise are at an increased risk of developing depression.
Younger people who are routinely exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces, according to a new study.
Increased levels of air pollution led to higher rates of respiratory illnesses, which in turn resulted in increased costs for healthcare for the affected communities.

Examples of Directional Hypothesis:

The crop yield will go up a lot if the amount of fertilizer is increased.
Patients who have surgery and are exposed to more stress will need more time to get better.
Increasing the frequency of brand advertising on social media will lead to a significant increase in brand awareness among the target audience.

Examples of Non-Directional Hypothesis (or Two-Tailed Hypothesis):

The test scores of two groups of students are very different from each other.
There is a link between gender and being happy at work.
There is a correlation between the amount of caffeine an individual consumes and the speed with which they react.

Examples of a null hypothesis:

Children who receive a new reading intervention will have scores that are different than students who do not receive the intervention.
The results of a memory recall test will not reveal any significant gap in performance between children and adults.
There is not a significant relationship between the number of hours spent playing video games and academic performance.

Examples of Associative Hypothesis:

There is a link between how many hours you spend studying and how well you do in school.
Drinking sugary drinks is bad for your health as a whole.
There is an association between socioeconomic status and access to quality healthcare services in urban neighborhoods.

Functions Of Hypothesis

The research issue can be understood better with the help of a hypothesis, which is why developing one is crucial. The following are some of the specific roles that a hypothesis plays: (Rashid, Apr 20, 2022)

A hypothesis gives a study a point of concentration. It enlightens us as to the specific characteristics of a study subject we need to look into.
It instructs us on what data to acquire as well as what data we should not collect, giving the study a focal point .
The development of a hypothesis improves objectivity since it enables the establishment of a focal point.
A hypothesis makes it possible for us to contribute to the development of the theory. Because of this, we are in a position to definitively determine what is true and what is untrue .

How will Hypothesis help in the Scientific Method?

The scientific method begins with observation and inquiry about the natural world when formulating research questions. Researchers can refine their observations and queries into specific, testable research questions with the aid of hypothesis. They provide an investigation with a focused starting point.
Hypothesis generate specific predictions regarding the expected outcomes of experiments or observations. These forecasts are founded on the researcher’s current knowledge of the subject. They elucidate what researchers anticipate observing if the hypothesis is true.
Hypothesis direct the design of experiments and data collection techniques. Researchers can use them to determine which variables to measure or manipulate, which data to obtain, and how to conduct systematic and controlled research.
Following the formulation of a hypothesis and the design of an experiment, researchers collect data through observation, measurement, or experimentation. The collected data is used to verify the hypothesis’s predictions.
Hypothesis establish the criteria for evaluating experiment results. The observed data are compared to the predictions generated by the hypothesis. This analysis helps determine whether empirical evidence supports or refutes the hypothesis.
The results of experiments or observations are used to derive conclusions regarding the hypothesis. If the data support the predictions, then the hypothesis is supported. If this is not the case, the hypothesis may be revised or rejected, leading to the formulation of new queries and hypothesis.
The scientific approach is iterative, resulting in new hypothesis and research issues from previous trials. This cycle of hypothesis generation, testing, and refining drives scientific progress.

Importance Of Hypothesis

Hypothesis are testable statements that enable scientists to determine if their predictions are accurate. This assessment is essential to the scientific method, which is based on empirical evidence.
Hypothesis serve as the foundation for designing experiments or data collection techniques. They can be used by researchers to develop protocols and procedures that will produce meaningful results.
Hypothesis hold scientists accountable for their assertions. They establish expectations for what the research should reveal and enable others to assess the validity of the findings.
Hypothesis aid in identifying the most important variables of a study. The variables can then be measured, manipulated, or analyzed to determine their relationships.
Hypothesis assist researchers in allocating their resources efficiently. They ensure that time, money, and effort are spent investigating specific concerns, as opposed to exploring random concepts.
Testing hypothesis contribute to the scientific body of knowledge. Whether or not a hypothesis is supported, the results contribute to our understanding of a phenomenon.
Hypothesis can result in the creation of theories. When supported by substantive evidence, hypothesis can serve as the foundation for larger theoretical frameworks that explain complex phenomena.
Beyond scientific research, hypothesis play a role in the solution of problems in a variety of domains. They enable professionals to make educated assumptions about the causes of problems and to devise solutions.

Research Hypotheses: Did you know that a hypothesis refers to an educated guess or prediction about the outcome of a research study?

It’s like a roadmap guiding researchers towards their destination of knowledge. Just like a compass points north, a well-crafted hypothesis points the way to valuable discoveries in the world of science and inquiry.

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Research Hypothesis In Psychology: Types, & Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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On This Page:

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

Some key points about hypotheses:

A hypothesis expresses an expected pattern or relationship. It connects the variables under investigation.
It is stated in clear, precise terms before any data collection or analysis occurs. This makes the hypothesis testable.
A hypothesis must be falsifiable. It should be possible, even if unlikely in practice, to collect data that disconfirms rather than supports the hypothesis.
Hypotheses guide research. Scientists design studies to explicitly evaluate hypotheses about how nature works.
For a hypothesis to be valid, it must be testable against empirical evidence. The evidence can then confirm or disprove the testable predictions.
Hypotheses are informed by background knowledge and observation, but go beyond what is already known to propose an explanation of how or why something occurs.

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.

Types of Research Hypotheses

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:

Important hypotheses lead to predictions that can be tested empirically. The evidence can then confirm or disprove the testable predictions.

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.

Null Hypothesis

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.

Nondirectional Hypothesis

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.

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.

Falsifiability

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.

Can a Hypothesis be Proven?

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.

Disproving a hypothesis is definitive. Solid disconfirmatory evidence will falsify a hypothesis and require altering or discarding it based on the evidence.
However, confirming evidence is always open to revision. Other explanations may account for the same results, and additional or contradictory evidence may emerge over time.

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.

How to Write a Hypothesis

Identify variables . The researcher manipulates the independent variable and the dependent variable is the measured outcome.
Operationalized the variables being investigated . Operationalization of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression, you might count the number of punches given by participants.
Decide on a direction for your prediction . If there is evidence in the literature to support a specific effect of the independent variable on the dependent variable, write a directional (one-tailed) hypothesis. If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
Make it Testable : Ensure your hypothesis can be tested through experimentation or observation. It should be possible to prove it false (principle of falsifiability).
Clear & concise language . A strong hypothesis is concise (typically one to two sentences long), and formulated using clear and straightforward language, ensuring it’s easily understood and testable.

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:

The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.

More Examples

Memory : Participants exposed to classical music during study sessions will recall more items from a list than those who studied in silence.
Social Psychology : Individuals who frequently engage in social media use will report higher levels of perceived social isolation compared to those who use it infrequently.
Developmental Psychology : Children who engage in regular imaginative play have better problem-solving skills than those who don’t.
Clinical Psychology : Cognitive-behavioral therapy will be more effective in reducing symptoms of anxiety over a 6-month period compared to traditional talk therapy.
Cognitive Psychology : Individuals who multitask between various electronic devices will have shorter attention spans on focused tasks than those who single-task.
Health Psychology : Patients who practice mindfulness meditation will experience lower levels of chronic pain compared to those who don’t meditate.
Organizational Psychology : Employees in open-plan offices will report higher levels of stress than those in private offices.
Behavioral Psychology : Rats rewarded with food after pressing a lever will press it more frequently than rats who receive no reward.

Research Methodology

Qualitative Data Coding

What Is a Focus Group?

Cross-Cultural Research Methodology In Psychology

What Is Internal Validity In Research?

Research Methodology , Statistics

What Is Face Validity In Research? Importance & How To Measure

Criterion Validity: Definition & Examples

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J Korean Med Sci
v.34(45); 2019 Nov 25

Scientific Hypotheses: Writing, Promoting, and Predicting Implications

Armen yuri gasparyan.

1 Departments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, West Midlands, UK.

Lilit Ayvazyan

2 Department of Medical Chemistry, Yerevan State Medical University, Yerevan, Armenia.

Ulzhan Mukanova

3 Department of Surgical Disciplines, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.

Marlen Yessirkepov

4 Department of Biology and Biochemistry, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.

George D. Kitas

5 Arthritis Research UK Epidemiology Unit, University of Manchester, Manchester, UK.

Scientific hypotheses are essential for progress in rapidly developing academic disciplines. Proposing new ideas and hypotheses require thorough analyses of evidence-based data and predictions of the implications. One of the main concerns relates to the ethical implications of the generated hypotheses. The authors may need to outline potential benefits and limitations of their suggestions and target widely visible publication outlets to ignite discussion by experts and start testing the hypotheses. Not many publication outlets are currently welcoming hypotheses and unconventional ideas that may open gates to criticism and conservative remarks. A few scholarly journals guide the authors on how to structure hypotheses. Reflecting on general and specific issues around the subject matter is often recommended for drafting a well-structured hypothesis article. An analysis of influential hypotheses, presented in this article, particularly Strachan's hygiene hypothesis with global implications in the field of immunology and allergy, points to the need for properly interpreting and testing new suggestions. Envisaging the ethical implications of the hypotheses should be considered both by authors and journal editors during the writing and publishing process.

INTRODUCTION

We live in times of digitization that radically changes scientific research, reporting, and publishing strategies. Researchers all over the world are overwhelmed with processing large volumes of information and searching through numerous online platforms, all of which make the whole process of scholarly analysis and synthesis complex and sophisticated.

Current research activities are diversifying to combine scientific observations with analysis of facts recorded by scholars from various professional backgrounds. 1 Citation analyses and networking on social media are also becoming essential for shaping research and publishing strategies globally. 2 Learning specifics of increasingly interdisciplinary research studies and acquiring information facilitation skills aid researchers in formulating innovative ideas and predicting developments in interrelated scientific fields.

Arguably, researchers are currently offered more opportunities than in the past for generating new ideas by performing their routine laboratory activities, observing individual cases and unusual developments, and critically analyzing published scientific facts. What they need at the start of their research is to formulate a scientific hypothesis that revisits conventional theories, real-world processes, and related evidence to propose new studies and test ideas in an ethical way. 3 Such a hypothesis can be of most benefit if published in an ethical journal with wide visibility and exposure to relevant online databases and promotion platforms.

Although hypotheses are crucially important for the scientific progress, only few highly skilled researchers formulate and eventually publish their innovative ideas per se . Understandably, in an increasingly competitive research environment, most authors would prefer to prioritize their ideas by discussing and conducting tests in their own laboratories or clinical departments, and publishing research reports afterwards. However, there are instances when simple observations and research studies in a single center are not capable of explaining and testing new groundbreaking ideas. Formulating hypothesis articles first and calling for multicenter and interdisciplinary research can be a solution in such instances, potentially launching influential scientific directions, if not academic disciplines.

The aim of this article is to overview the importance and implications of infrequently published scientific hypotheses that may open new avenues of thinking and research.

Despite the seemingly established views on innovative ideas and hypotheses as essential research tools, no structured definition exists to tag the term and systematically track related articles. In 1973, the Medical Subject Heading (MeSH) of the U.S. National Library of Medicine introduced “Research Design” as a structured keyword that referred to the importance of collecting data and properly testing hypotheses, and indirectly linked the term to ethics, methods and standards, among many other subheadings.

One of the experts in the field defines “hypothesis” as a well-argued analysis of available evidence to provide a realistic (scientific) explanation of existing facts, fill gaps in public understanding of sophisticated processes, and propose a new theory or a test. 4 A hypothesis can be proven wrong partially or entirely. However, even such an erroneous hypothesis may influence progress in science by initiating professional debates that help generate more realistic ideas. The main ethical requirement for hypothesis authors is to be honest about the limitations of their suggestions. 5

EXAMPLES OF INFLUENTIAL SCIENTIFIC HYPOTHESES

Daily routine in a research laboratory may lead to groundbreaking discoveries provided the daily accounts are comprehensively analyzed and reproduced by peers. The discovery of penicillin by Sir Alexander Fleming (1928) can be viewed as a prime example of such discoveries that introduced therapies to treat staphylococcal and streptococcal infections and modulate blood coagulation. 6 , 7 Penicillin got worldwide recognition due to the inventor's seminal works published by highly prestigious and widely visible British journals, effective ‘real-world’ antibiotic therapy of pneumonia and wounds during World War II, and euphoric media coverage. 8 In 1945, Fleming, Florey and Chain got a much deserved Nobel Prize in Physiology or Medicine for the discovery that led to the mass production of the wonder drug in the U.S. and ‘real-world practice’ that tested the use of penicillin. What remained globally unnoticed is that Zinaida Yermolyeva, the outstanding Soviet microbiologist, created the Soviet penicillin, which turned out to be more effective than the Anglo-American penicillin and entered mass production in 1943; that year marked the turning of the tide of the Great Patriotic War. 9 One of the reasons of the widely unnoticed discovery of Zinaida Yermolyeva is that her works were published exclusively by local Russian (Soviet) journals.

The past decades have been marked by an unprecedented growth of multicenter and global research studies involving hundreds and thousands of human subjects. This trend is shaped by an increasing number of reports on clinical trials and large cohort studies that create a strong evidence base for practice recommendations. Mega-studies may help generate and test large-scale hypotheses aiming to solve health issues globally. Properly designed epidemiological studies, for example, may introduce clarity to the hygiene hypothesis that was originally proposed by David Strachan in 1989. 10 David Strachan studied the epidemiology of hay fever in a cohort of 17,414 British children and concluded that declining family size and improved personal hygiene had reduced the chances of cross infections in families, resulting in epidemics of atopic disease in post-industrial Britain. Over the past four decades, several related hypotheses have been proposed to expand the potential role of symbiotic microorganisms and parasites in the development of human physiological immune responses early in life and protection from allergic and autoimmune diseases later on. 11 , 12 Given the popularity and the scientific importance of the hygiene hypothesis, it was introduced as a MeSH term in 2012. 13

Hypotheses can be proposed based on an analysis of recorded historic events that resulted in mass migrations and spreading of certain genetic diseases. As a prime example, familial Mediterranean fever (FMF), the prototype periodic fever syndrome, is believed to spread from Mesopotamia to the Mediterranean region and all over Europe due to migrations and religious prosecutions millennia ago. 14 Genetic mutations spearing mild clinical forms of FMF are hypothesized to emerge and persist in the Mediterranean region as protective factors against more serious infectious diseases, particularly tuberculosis, historically common in that part of the world. 15 The speculations over the advantages of carrying the MEditerranean FeVer (MEFV) gene are further strengthened by recorded low mortality rates from tuberculosis among FMF patients of different nationalities living in Tunisia in the first half of the 20th century. 16

Diagnostic hypotheses shedding light on peculiarities of diseases throughout the history of mankind can be formulated using artefacts, particularly historic paintings. 17 Such paintings may reveal joint deformities and disfigurements due to rheumatic diseases in individual subjects. A series of paintings with similar signs of pathological conditions interpreted in a historic context may uncover mysteries of epidemics of certain diseases, which is the case with Ruben's paintings depicting signs of rheumatic hands and making some doctors to believe that rheumatoid arthritis was common in Europe in the 16th and 17th century. 18

WRITING SCIENTIFIC HYPOTHESES

There are author instructions of a few journals that specifically guide how to structure, format, and make submissions categorized as hypotheses attractive. One of the examples is presented by Med Hypotheses , the flagship journal in its field with more than four decades of publishing and influencing hypothesis authors globally. However, such guidance is not based on widely discussed, implemented, and approved reporting standards, which are becoming mandatory for all scholarly journals.

Generating new ideas and scientific hypotheses is a sophisticated task since not all researchers and authors are skilled to plan, conduct, and interpret various research studies. Some experience with formulating focused research questions and strong working hypotheses of original research studies is definitely helpful for advancing critical appraisal skills. However, aspiring authors of scientific hypotheses may need something different, which is more related to discerning scientific facts, pooling homogenous data from primary research works, and synthesizing new information in a systematic way by analyzing similar sets of articles. To some extent, this activity is reminiscent of writing narrative and systematic reviews. As in the case of reviews, scientific hypotheses need to be formulated on the basis of comprehensive search strategies to retrieve all available studies on the topics of interest and then synthesize new information selectively referring to the most relevant items. One of the main differences between scientific hypothesis and review articles relates to the volume of supportive literature sources ( Table 1 ). In fact, hypothesis is usually formulated by referring to a few scientific facts or compelling evidence derived from a handful of literature sources. 19 By contrast, reviews require analyses of a large number of published documents retrieved from several well-organized and evidence-based databases in accordance with predefined search strategies. 20 , 21 , 22

The format of hypotheses, especially the implications part, may vary widely across disciplines. Clinicians may limit their suggestions to the clinical manifestations of diseases, outcomes, and management strategies. Basic and laboratory scientists analysing genetic, molecular, and biochemical mechanisms may need to view beyond the frames of their narrow fields and predict social and population-based implications of the proposed ideas. 23

Advanced writing skills are essential for presenting an interesting theoretical article which appeals to the global readership. Merely listing opposing facts and ideas, without proper interpretation and analysis, may distract the experienced readers. The essence of a great hypothesis is a story behind the scientific facts and evidence-based data.

ETHICAL IMPLICATIONS

The authors of hypotheses substantiate their arguments by referring to and discerning rational points from published articles that might be overlooked by others. Their arguments may contradict the established theories and practices, and pose global ethical issues, particularly when more or less efficient medical technologies and public health interventions are devalued. The ethical issues may arise primarily because of the careless references to articles with low priorities, inadequate and apparently unethical methodologies, and concealed reporting of negative results. 24 , 25

Misinterpretation and misunderstanding of the published ideas and scientific hypotheses may complicate the issue further. For example, Alexander Fleming, whose innovative ideas of penicillin use to kill susceptible bacteria saved millions of lives, warned of the consequences of uncontrolled prescription of the drug. The issue of antibiotic resistance had emerged within the first ten years of penicillin use on a global scale due to the overprescription that affected the efficacy of antibiotic therapies, with undesirable consequences for millions. 26

The misunderstanding of the hygiene hypothesis that primarily aimed to shed light on the role of the microbiome in allergic and autoimmune diseases resulted in decline of public confidence in hygiene with dire societal implications, forcing some experts to abandon the original idea. 27 , 28 Although that hypothesis is unrelated to the issue of vaccinations, the public misunderstanding has resulted in decline of vaccinations at a time of upsurge of old and new infections.

A number of ethical issues are posed by the denial of the viral (human immunodeficiency viruses; HIV) hypothesis of acquired Immune deficiency Syndrome (AIDS) by Peter Duesberg, who overviewed the links between illicit recreational drugs and antiretroviral therapies with AIDS and refuted the etiological role of HIV. 29 That controversial hypothesis was rejected by several journals, but was eventually published without external peer review at Med Hypotheses in 2010. The publication itself raised concerns of the unconventional editorial policy of the journal, causing major perturbations and more scrutinized publishing policies by journals processing hypotheses.

WHERE TO PUBLISH HYPOTHESES

Although scientific authors are currently well informed and equipped with search tools to draft evidence-based hypotheses, there are still limited quality publication outlets calling for related articles. The journal editors may be hesitant to publish articles that do not adhere to any research reporting guidelines and open gates for harsh criticism of unconventional and untested ideas. Occasionally, the editors opting for open-access publishing and upgrading their ethics regulations launch a section to selectively publish scientific hypotheses attractive to the experienced readers. 30 However, the absence of approved standards for this article type, particularly no mandate for outlining potential ethical implications, may lead to publication of potentially harmful ideas in an attractive format.

A suggestion of simultaneously publishing multiple or alternative hypotheses to balance the reader views and feedback is a potential solution for the mainstream scholarly journals. 31 However, that option alone is hardly applicable to emerging journals with unconventional quality checks and peer review, accumulating papers with multiple rejections by established journals.

A large group of experts view hypotheses with improbable and controversial ideas publishable after formal editorial (in-house) checks to preserve the authors' genuine ideas and avoid conservative amendments imposed by external peer reviewers. 32 That approach may be acceptable for established publishers with large teams of experienced editors. However, the same approach can lead to dire consequences if employed by nonselective start-up, open-access journals processing all types of articles and primarily accepting those with charged publication fees. 33 In fact, pseudoscientific ideas arguing Newton's and Einstein's seminal works or those denying climate change that are hardly testable have already found their niche in substandard electronic journals with soft or nonexistent peer review. 34

CITATIONS AND SOCIAL MEDIA ATTENTION

The available preliminary evidence points to the attractiveness of hypothesis articles for readers, particularly those from research-intensive countries who actively download related documents. 35 However, citations of such articles are disproportionately low. Only a small proportion of top-downloaded hypotheses (13%) in the highly prestigious Med Hypotheses receive on average 5 citations per article within a two-year window. 36

With the exception of a few historic papers, the vast majority of hypotheses attract relatively small number of citations in a long term. 36 Plausible explanations are that these articles often contain a single or only a few citable points and that suggested research studies to test hypotheses are rarely conducted and reported, limiting chances of citing and crediting authors of genuine research ideas.

A snapshot analysis of citation activity of hypothesis articles may reveal interest of the global scientific community towards their implications across various disciplines and countries. As a prime example, Strachan's hygiene hypothesis, published in 1989, 10 is still attracting numerous citations on Scopus, the largest bibliographic database. As of August 28, 2019, the number of the linked citations in the database is 3,201. Of the citing articles, 160 are cited at least 160 times ( h -index of this research topic = 160). The first three citations are recorded in 1992 and followed by a rapid annual increase in citation activity and a peak of 212 in 2015 ( Fig. 1 ). The top 5 sources of the citations are Clin Exp Allergy (n = 136), J Allergy Clin Immunol (n = 119), Allergy (n = 81), Pediatr Allergy Immunol (n = 69), and PLOS One (n = 44). The top 5 citing authors are leading experts in pediatrics and allergology Erika von Mutius (Munich, Germany, number of publications with the index citation = 30), Erika Isolauri (Turku, Finland, n = 27), Patrick G Holt (Subiaco, Australia, n = 25), David P. Strachan (London, UK, n = 23), and Bengt Björksten (Stockholm, Sweden, n = 22). The U.S. is the leading country in terms of citation activity with 809 related documents, followed by the UK (n = 494), Germany (n = 314), Australia (n = 211), and the Netherlands (n = 177). The largest proportion of citing documents are articles (n = 1,726, 54%), followed by reviews (n = 950, 29.7%), and book chapters (n = 213, 6.7%). The main subject areas of the citing items are medicine (n = 2,581, 51.7%), immunology and microbiology (n = 1,179, 23.6%), and biochemistry, genetics and molecular biology (n = 415, 8.3%).

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Interestingly, a recent analysis of 111 publications related to Strachan's hygiene hypothesis, stating that the lack of exposure to infections in early life increases the risk of rhinitis, revealed a selection bias of 5,551 citations on Web of Science. 37 The articles supportive of the hypothesis were cited more than nonsupportive ones (odds ratio adjusted for study design, 2.2; 95% confidence interval, 1.6–3.1). A similar conclusion pointing to a citation bias distorting bibliometrics of hypotheses was reached by an earlier analysis of a citation network linked to the idea that β-amyloid, which is involved in the pathogenesis of Alzheimer disease, is produced by skeletal muscle of patients with inclusion body myositis. 38 The results of both studies are in line with the notion that ‘positive’ citations are more frequent in the field of biomedicine than ‘negative’ ones, and that citations to articles with proven hypotheses are too common. 39

Social media channels are playing an increasingly active role in the generation and evaluation of scientific hypotheses. In fact, publicly discussing research questions on platforms of news outlets, such as Reddit, may shape hypotheses on health-related issues of global importance, such as obesity. 40 Analyzing Twitter comments, researchers may reveal both potentially valuable ideas and unfounded claims that surround groundbreaking research ideas. 41 Social media activities, however, are unevenly distributed across different research topics, journals and countries, and these are not always objective professional reflections of the breakthroughs in science. 2 , 42

Scientific hypotheses are essential for progress in science and advances in healthcare. Innovative ideas should be based on a critical overview of related scientific facts and evidence-based data, often overlooked by others. To generate realistic hypothetical theories, the authors should comprehensively analyze the literature and suggest relevant and ethically sound design for future studies. They should also consider their hypotheses in the context of research and publication ethics norms acceptable for their target journals. The journal editors aiming to diversify their portfolio by maintaining and introducing hypotheses section are in a position to upgrade guidelines for related articles by pointing to general and specific analyses of the subject, preferred study designs to test hypotheses, and ethical implications. The latter is closely related to specifics of hypotheses. For example, editorial recommendations to outline benefits and risks of a new laboratory test or therapy may result in a more balanced article and minimize associated risks afterwards.

Not all scientific hypotheses have immediate positive effects. Some, if not most, are never tested in properly designed research studies and never cited in credible and indexed publication outlets. Hypotheses in specialized scientific fields, particularly those hardly understandable for nonexperts, lose their attractiveness for increasingly interdisciplinary audience. The authors' honest analysis of the benefits and limitations of their hypotheses and concerted efforts of all stakeholders in science communication to initiate public discussion on widely visible platforms and social media may reveal rational points and caveats of the new ideas.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

Conceptualization: Gasparyan AY, Yessirkepov M, Kitas GD.
Methodology: Gasparyan AY, Mukanova U, Ayvazyan L.
Writing - original draft: Gasparyan AY, Ayvazyan L, Yessirkepov M.
Writing - review & editing: Gasparyan AY, Yessirkepov M, Mukanova U, Kitas GD.

Home » What is a Hypothesis – Types, Examples and Writing Guide

What is a Hypothesis – Types, Examples and Writing Guide

Table of Contents

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

Types of Hypothesis are as follows:

Research Hypothesis

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.

Null Hypothesis

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.

Alternative Hypothesis

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.

Directional Hypothesis

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.

Non-directional Hypothesis

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.

Statistical Hypothesis

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.

Composite Hypothesis

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.

Empirical Hypothesis

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.

Simple Hypothesis

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.

Complex Hypothesis

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.

Applications of Hypothesis

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:

Science : In scientific research, hypotheses are used to test the validity of theories and models that explain natural phenomena. For example, a hypothesis might be formulated to test the effects of a particular variable on a natural system, such as the effects of climate change on an ecosystem.
Medicine : In medical research, hypotheses are used to test the effectiveness of treatments and therapies for specific conditions. For example, a hypothesis might be formulated to test the effects of a new drug on a particular disease.
Psychology : In psychology, hypotheses are used to test theories and models of human behavior and cognition. For example, a hypothesis might be formulated to test the effects of a particular stimulus on the brain or behavior.
Sociology : In sociology, hypotheses are used to test theories and models of social phenomena, such as the effects of social structures or institutions on human behavior. For example, a hypothesis might be formulated to test the effects of income inequality on crime rates.
Business : In business research, hypotheses are used to test the validity of theories and models that explain business phenomena, such as consumer behavior or market trends. For example, a hypothesis might be formulated to test the effects of a new marketing campaign on consumer buying behavior.
Engineering : In engineering, hypotheses are used to test the effectiveness of new technologies or designs. For example, a hypothesis might be formulated to test the efficiency of a new solar panel design.

How to write a Hypothesis

Here are the steps to follow when writing a hypothesis:

Identify the Research Question

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.

Conduct a Literature Review

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.

Determine the Variables

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.

Formulate the Hypothesis

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.

Write the Null Hypothesis

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.

Refine the Hypothesis

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.

Examples of Hypothesis

Here are a few examples of hypotheses in different fields:

Psychology : “Increased exposure to violent video games leads to increased aggressive behavior in adolescents.”
Biology : “Higher levels of carbon dioxide in the atmosphere will lead to increased plant growth.”
Sociology : “Individuals who grow up in households with higher socioeconomic status will have higher levels of education and income as adults.”
Education : “Implementing a new teaching method will result in higher student achievement scores.”
Marketing : “Customers who receive a personalized email will be more likely to make a purchase than those who receive a generic email.”
Physics : “An increase in temperature will cause an increase in the volume of a gas, assuming all other variables remain constant.”
Medicine : “Consuming a diet high in saturated fats will increase the risk of developing heart disease.”

Purpose of Hypothesis

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.

When to use Hypothesis

Here are some common situations in which hypotheses are used:

In scientific research , hypotheses are used to guide the design of experiments and to help researchers make predictions about the outcomes of those experiments.
In social science research , hypotheses are used to test theories about human behavior, social relationships, and other phenomena.
I n business , hypotheses can be used to guide decisions about marketing, product development, and other areas. For example, a hypothesis might be that a new product will sell well in a particular market, and this hypothesis can be tested through market research.

Characteristics of Hypothesis

Here are some common characteristics of a hypothesis:

Testable : A hypothesis must be able to be tested through observation or experimentation. This means that it must be possible to collect data that will either support or refute the hypothesis.
Falsifiable : A hypothesis must be able to be proven false if it is not supported by the data. If a hypothesis cannot be falsified, then it is not a scientific hypothesis.
Clear and concise : A hypothesis should be stated in a clear and concise manner so that it can be easily understood and tested.
Based on existing knowledge : A hypothesis should be based on existing knowledge and research in the field. It should not be based on personal beliefs or opinions.
Specific : A hypothesis should be specific in terms of the variables being tested and the predicted outcome. This will help to ensure that the research is focused and well-designed.
Tentative: A hypothesis is a tentative statement or assumption that requires further testing and evidence to be confirmed or refuted. It is not a final conclusion or assertion.
Relevant : A hypothesis should be relevant to the research question or problem being studied. It should address a gap in knowledge or provide a new perspective on the issue.

Advantages of Hypothesis

Hypotheses have several advantages in scientific research and experimentation:

Guides research: A hypothesis provides a clear and specific direction for research. It helps to focus the research question, select appropriate methods and variables, and interpret the results.
Predictive powe r: A hypothesis makes predictions about the outcome of research, which can be tested through experimentation. This allows researchers to evaluate the validity of the hypothesis and make new discoveries.
Facilitates communication: A hypothesis provides a common language and framework for scientists to communicate with one another about their research. This helps to facilitate the exchange of ideas and promotes collaboration.
Efficient use of resources: A hypothesis helps researchers to use their time, resources, and funding efficiently by directing them towards specific research questions and methods that are most likely to yield results.
Provides a basis for further research: A hypothesis that is supported by data provides a basis for further research and exploration. It can lead to new hypotheses, theories, and discoveries.
Increases objectivity: A hypothesis can help to increase objectivity in research by providing a clear and specific framework for testing and interpreting results. This can reduce bias and increase the reliability of research findings.

Limitations of Hypothesis

Some Limitations of the Hypothesis are as follows:

Limited to observable phenomena: Hypotheses are limited to observable phenomena and cannot account for unobservable or intangible factors. This means that some research questions may not be amenable to hypothesis testing.
May be inaccurate or incomplete: Hypotheses are based on existing knowledge and research, which may be incomplete or inaccurate. This can lead to flawed hypotheses and erroneous conclusions.
May be biased: Hypotheses may be biased by the researcher’s own beliefs, values, or assumptions. This can lead to selective interpretation of data and a lack of objectivity in research.
Cannot prove causation: A hypothesis can only show a correlation between variables, but it cannot prove causation. This requires further experimentation and analysis.
Limited to specific contexts: Hypotheses are limited to specific contexts and may not be generalizable to other situations or populations. This means that results may not be applicable in other contexts or may require further testing.
May be affected by chance : Hypotheses may be affected by chance or random variation, which can obscure or distort the true relationship between variables.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

Data Collection – Methods Types and Examples

Delimitations in Research – Types, Examples and...

Research Process – Steps, Examples and Tips

Research Design – Types, Methods and Examples

Institutional Review Board – Application Sample...

Evaluating Research – Process, Examples and...

Developing the research hypothesis

Affiliation.

1 Division of Abdominal Transplantation, Department of Surgery, University of North Carolina at Chapel Hill, USA. [email protected]
PMID: 21867386
DOI: 10.3109/08941939.2011.609449

The research hypothesis is needed for a sound and well-developed research study. The research hypothesis contributes to the solution of the research problem. Types of research hypotheses include inductive and deductive, directional and non-directional, and null and alternative hypotheses. Rejecting the null hypothesis and accepting the alternative hypothesis is the basis for building a good research study. This work reviews the most important aspects of organizing and establishing an efficient and complete hypothesis.

Biomedical Research / methods*
Data Interpretation, Statistical
Research Design*

Chapter 6 - Hypothesis Development

Chapter 6 overview.

This chapter discusses the third step of the SGAM, highlighted below in gold, Hypothesis Development.

Depiction of correlation betwen knowledge and effort in SGAM, highlighting step 3: hypothesis development

A hypothesis is often defined as an educated guess because it is informed by what you already know about a topic. This step in the process is to identify all hypotheses that merit detailed examination, keeping in mind that there is a distinction between the hypothesis generation and hypothesis evaluation .

If the analysis does not begin with the correct hypothesis, it is unlikely to get the correct answer. Psychological research into how people go about generating hypotheses shows that people are actually rather poor at thinking of all the possibilities. Therefore, at the hypothesis generation stage, it is wise to bring together a group of analysts with different backgrounds and perspectives for a brainstorming session. Brainstorming in a group stimulates the imagination and usually brings out possibilities that individual members of the group had not thought of. Experience shows that initial discussion in the group elicits every possibility, no matter how remote, before judging likelihood or feasibility. Only when all the possibilities are on the table, is the focus on judging them and selecting the hypotheses to be examined in greater detail in subsequent analysis.

When screening out the seemingly improbable hypotheses, it is necessary to distinguish hypotheses that appear to be disproved (i.e., improbable) from those that are simply unproven. For an unproven hypothesis, there is no evidence that it is correct. For a disproved hypothesis, there is positive evidence that it is wrong. Early rejection of unproven, but not disproved, hypotheses biases the analysis, because one does not then look for the evidence that might support them. Unproven hypotheses should be kept alive until they can be disproved. One example of a hypothesis that often falls into this unproven but not disproved category is the hypothesis that an opponent is trying to deceive us. You may reject the possibility of denial and deception because you see no evidence of it, but rejection is not justified under these circumstances. If deception is planned well and properly implemented, one should not expect to find evidence of it readily at hand. The possibility should not be rejected until it is disproved, or, at least, until after a systematic search for evidence has been made, and none has been found.

There is no "correct" number of hypotheses to be considered. The number depends upon the nature of the analytical problem and how advanced you are in the analysis of it. As a general rule, the greater your level of uncertainty, or the greater the impact of your conclusion, the more alternatives you may wish to consider. More than seven hypotheses may be unmanageable; if there are this many alternatives, it may be advisable to group several of them together for your initial cut at the analysis.

Developing Multiple Hypotheses

Developing good hypotheses requires divergent thinking to ensure that all hypotheses are considered. It also requires convergent thinking to ensure that redundant and irrational hypotheses are eliminated. A hypothesis is stated as an "if … then" statement. There are two important qualities about a hypothesis expressed as an "if … then" statement. These are:

Is the hypothesis testable; in other words, could evidence be found to test the validity of the statement?
Is the hypothesis falsifiable; in other words, could evidence reveal that such an idea is not true?

Hypothesis development is ultimately experience-based. In this experienced-based reasoning, new knowledge is compared to previous knowledge. New knowledge is added to this internal knowledge base. Before long, an analyst has developed an internal set of spatial rules. These rules are then used to develop possible hypotheses.

Looking Forward

Developing hypotheses and evidence is the beginning of the sensemaking and Analysis of Competing Hypotheses (ACH) process. ACH is a general purpose intelligence analysis methodology developed by Richards Heuer while he was an analyst at the Central Intelligence Agency (CIA). ACH draws on the scientific method, cognitive psychology, and decision analysis. ACH became widely available when the CIA published Heuer’s The Psychology of Intelligence Analysis . The ACH methodology can help the geospatial analyst overcome cognitive biases common to analysis in national security, law enforcement, and competitive intelligence. ACH forces analysts to disprove hypotheses rather than jump to conclusions and permit biases and mindsets to determine the outcome. ACH is a very logical step-by-step process that has been incorporated into our Structured Geospatial Analytical Method. A complete discussion of ACH is found in Chapter 8 of Heuer’s book.

General Approaches to Problem Solving Utilizing Hypotheses

Science follows at least three general methods of problem solving using hypotheses. These can be called the:

method of the ruling theory
method of the working hypothesis
method of multiple working hypotheses

The first two are the most popular but they can lead to overlooking relevant perspectives, data, and encourage biases. It has been suggested that multiple hypotheses offers a more effective way of overcoming this problem.

Ruling Theories and Working Hypotheses

Our desire to reach an explanation commonly leads us to a tentative interpretation that is based on a single case. The explanation can blind us to other possibilities that we ignored at first glance. This premature explanation can become a ruling theory, and our research becomes focused on proving that ruling theory. The result is a bias to evidence that disproves the ruling theory or supports an alternate explanation. Only if the original hypothesis was by chance correct does our analysis lead to any meaningful intelligence work. The working hypothesis is supposed to be a hypothesis to be tested, not in order to prove the hypothesis, but as a stimulus for study and fact-finding. Nonetheless, the single working hypothesis can become a ruling theory, and the desire to prove the working hypothesis, despite evidence to the contrary, can become as strong as the desire to prove the ruling theory.

Multiple Hypotheses

The method of multiple working hypotheses involves the development, prior to our search for evidence, of several hypotheses that might explain what are attempting to explain. Many of these hypotheses should be contradictory, so that many will prove to be improbable. However, the development of multiple hypotheses prior to the intelligence analysis lets us avoid the trap of the ruling hypothesis and thus makes it more likely that our intelligence work will lead to meaningful results. We open-mindedly envision all the possible explanations of the events, including the possibility that none of the hypotheses are plausible and the possibility that more research and hypothesis development is needed. The method of multiple working hypotheses has several other beneficial effects on intelligence analysis. Human actions are often the result of several factors, not just one, and multiple hypotheses make it more likely that we will see the interaction of the several factors. The beginning with multiple hypotheses also promotes much greater thoroughness than analysis directed toward one hypothesis, leading to analytic lines that we might otherwise overlook, and thus to evidence and insights that might never have been considered. Thirdly, the method makes us much more likely to see the imperfections in our understanding and thus to avoid the pitfall of accepting weak or flawed evidence for one hypothesis when another provides a more possible explanation.

Drawbacks of Multiple Hypotheses

Multiple hypotheses have drawbacks. One is that it is difficult to express multiple hypotheses simultaneously, and therefore there is a natural tendency to favor one. Another problem is developing a large number of hypotheses that can be tested. A third possible problem is that of the indecision that arises as an analyst balances the evidence for various hypotheses, which is likely preferable to the premature rush to a false conclusion.

Actions That Help the Analyst Develop Hypotheses

Action 1: Brainstorming . Begin with a brainstorming session with your knowledge team to identify a set of alternative hypotheses. Focus on the hypotheses that are:

logically consistent with the theories and data uncovered in your grounding;
address the quality and relationships of spaces.

State the hypotheses stated in an "if ... then" format, for example:

If the DC Shooter is a terrorist, then the geospatial pattern of events would be similar to other terrorist acts.
If the DC Shooter is a serial killer, then the geospatial pattern of events would be similar to other serial killers.

Action 2: Review the hypotheses for testability , i.e., can evidence be could found to test the validity of the statement.

Action 3: Check the hypotheses for falsifiability , i.e., could evidence reveal that such an idea is not true.

Action 4: Combine redundant hypotheses.

Action 5:Consider the elimination of improbable and unproven hypotheses.

how-implement-hypothesis-driven-development

How to Implement Hypothesis-Driven Development

Remember back to the time when we were in high school science class. Our teachers had a framework for helping us learn – an experimental approach based on the best available evidence at hand. We were asked to make observations about the world around us, then attempt to form an explanation or hypothesis to explain what we had observed. We then tested this hypothesis by predicting an outcome based on our theory that would be achieved in a controlled experiment – if the outcome was achieved, we had proven our theory to be correct.

We could then apply this learning to inform and test other hypotheses by constructing more sophisticated experiments, and tuning, evolving or abandoning any hypothesis as we made further observations from the results we achieved.

Experimentation is the foundation of the scientific method, which is a systematic means of exploring the world around us. Although some experiments take place in laboratories, it is possible to perform an experiment anywhere, at any time, even in software development.

Practicing Hypothesis-Driven Development is thinking about the development of new ideas, products and services – even organizational change – as a series of experiments to determine whether an expected outcome will be achieved. The process is iterated upon until a desirable outcome is obtained or the idea is determined to be not viable.

We need to change our mindset to view our proposed solution to a problem statement as a hypothesis, especially in new product or service development – the market we are targeting, how a business model will work, how code will execute and even how the customer will use it.

We do not do projects anymore, only experiments. Customer discovery and Lean Startup strategies are designed to test assumptions about customers. Quality Assurance is testing system behavior against defined specifications. The experimental principle also applies in Test-Driven Development – we write the test first, then use the test to validate that our code is correct, and succeed if the code passes the test. Ultimately, product or service development is a process to test a hypothesis about system behaviour in the environment or market it is developed for.

The key outcome of an experimental approach is measurable evidence and learning.

Learning is the information we have gained from conducting the experiment. Did what we expect to occur actually happen? If not, what did and how does that inform what we should do next?

In order to learn we need use the scientific method for investigating phenomena, acquiring new knowledge, and correcting and integrating previous knowledge back into our thinking.

As the software development industry continues to mature, we now have an opportunity to leverage improved capabilities such as Continuous Design and Delivery to maximize our potential to learn quickly what works and what does not. By taking an experimental approach to information discovery, we can more rapidly test our solutions against the problems we have identified in the products or services we are attempting to build. With the goal to optimize our effectiveness of solving the right problems, over simply becoming a feature factory by continually building solutions.

The steps of the scientific method are to:

Make observations
Formulate a hypothesis
Design an experiment to test the hypothesis
State the indicators to evaluate if the experiment has succeeded
Conduct the experiment
Evaluate the results of the experiment
Accept or reject the hypothesis
If necessary, make and test a new hypothesis

Using an experimentation approach to software development

We need to challenge the concept of having fixed requirements for a product or service. Requirements are valuable when teams execute a well known or understood phase of an initiative, and can leverage well understood practices to achieve the outcome. However, when you are in an exploratory, complex and uncertain phase you need hypotheses.

Handing teams a set of business requirements reinforces an order-taking approach and mindset that is flawed.

Business does the thinking and ‘knows’ what is right. The purpose of the development team is to implement what they are told. But when operating in an area of uncertainty and complexity, all the members of the development team should be encouraged to think and share insights on the problem and potential solutions. A team simply taking orders from a business owner is not utilizing the full potential, experience and competency that a cross-functional multi-disciplined team offers.

Framing hypotheses

The traditional user story framework is focused on capturing requirements for what we want to build and for whom, to enable the user to receive a specific benefit from the system.

As A…. <role>

I Want… <goal/desire>

So That… <receive benefit>

Behaviour Driven Development (BDD) and Feature Injection aims to improve the original framework by supporting communication and collaboration between developers, tester and non-technical participants in a software project.

In Order To… <receive benefit>

As A… <role>

When viewing work as an experiment, the traditional story framework is insufficient. As in our high school science experiment, we need to define the steps we will take to achieve the desired outcome. We then need to state the specific indicators (or signals) we expect to observe that provide evidence that our hypothesis is valid. These need to be stated before conducting the test to reduce biased interpretations of the results.

If we observe signals that indicate our hypothesis is correct, we can be more confident that we are on the right path and can alter the user story framework to reflect this.

Therefore, a user story structure to support Hypothesis-Driven Development would be;

We believe < this capability >

What functionality we will develop to test our hypothesis? By defining a ‘test’ capability of the product or service that we are attempting to build, we identify the functionality and hypothesis we want to test.

Will result in < this outcome >

What is the expected outcome of our experiment? What is the specific result we expect to achieve by building the ‘test’ capability?

We will know we have succeeded when < we see a measurable signal >

What signals will indicate that the capability we have built is effective? What key metrics (qualitative or quantitative) we will measure to provide evidence that our experiment has succeeded and give us enough confidence to move to the next stage.

The threshold you use for statistically significance will depend on your understanding of the business and context you are operating within. Not every company has the user sample size of Amazon or Google to run statistically significant experiments in a short period of time. Limits and controls need to be defined by your organization to determine acceptable evidence thresholds that will allow the team to advance to the next step.

For example if you are building a rocket ship you may want your experiments to have a high threshold for statistical significance. If you are deciding between two different flows intended to help increase user sign up you may be happy to tolerate a lower significance threshold.

The final step is to clearly and visibly state any assumptions made about our hypothesis, to create a feedback loop for the team to provide further input, debate and understanding of the circumstance under which we are performing the test. Are they valid and make sense from a technical and business perspective?

Hypotheses when aligned to your MVP can provide a testing mechanism for your product or service vision. They can test the most uncertain areas of your product or service, in order to gain information and improve confidence.

Examples of Hypothesis-Driven Development user stories are;

Business story

We Believe That increasing the size of hotel images on the booking page

Will Result In improved customer engagement and conversion

We Will Know We Have Succeeded When we see a 5% increase in customers who review hotel images who then proceed to book in 48 hours.

It is imperative to have effective monitoring and evaluation tools in place when using an experimental approach to software development in order to measure the impact of our efforts and provide a feedback loop to the team. Otherwise we are essentially blind to the outcomes of our efforts.

In agile software development we define working software as the primary measure of progress.

By combining Continuous Delivery and Hypothesis-Driven Development we can now define working software and validated learning as the primary measures of progress.

Ideally we should not say we are done until we have measured the value of what is being delivered – in other words, gathered data to validate our hypothesis.

Examples of how to gather data is performing A/B Testing to test a hypothesis and measure to change in customer behaviour. Alternative testings options can be customer surveys, paper prototypes, user and/or guerrilla testing.

One example of a company we have worked with that uses Hypothesis-Driven Development is lastminute.com . The team formulated a hypothesis that customers are only willing to pay a max price for a hotel based on the time of day they book. Tom Klein, CEO and President of Sabre Holdings shared the story of how they improved conversion by 400% within a week.

Combining practices such as Hypothesis-Driven Development and Continuous Delivery accelerates experimentation and amplifies validated learning. This gives us the opportunity to accelerate the rate at which we innovate while relentlessly reducing cost, leaving our competitors in the dust. Ideally we can achieve the ideal of one piece flow: atomic changes that enable us to identify causal relationships between the changes we make to our products and services, and their impact on key metrics.

As Kent Beck said, “Test-Driven Development is a great excuse to think about the problem before you think about the solution”. Hypothesis-Driven Development is a great opportunity to test what you think the problem is, before you work on the solution.

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What is Public Health?

Is the Hygiene Hypothesis True?

Did Covid shutdowns stunt kids' immune systems?

Caitlin Rivers

The hygiene hypothesis is the idea that kids need to be exposed to germs in order to develop healthy immune systems. We know that many common viruses did not circulate as widely during the pandemic, thanks to social distancing, masking, and other COVID mitigation measures. Are there downsides to those missed infections?

In this Q&A, Caitlin Rivers speaks with Marsha Wills-Karp, PhD, MHS , professor and chair of Environmental Health and Engineering , about the role of household microbiomes, birth, and vaccines in the development of kids’ immune systems—and whether early exposure really is the best medicine.

This Q&A is adapted from Rivers’ Substack blog, Force of Infection .

I think there’s some concern among parents who have heard about the hygiene hypothesis that there is a downside to all those stuffy noses that didn’t happen [during the COVID-19 pandemic]. Are there any upsides to viral infections? Do they help the immune system in some meaningful way?

I don’t think so.

You mentioned the hygiene hypothesis, which was postulated back in the ‘80s. German scientists noticed that families with fewer children tended to have more allergic disease. This was interpreted [to mean] that allergic disease was linked to experiencing fewer infections. I have explored this idea in my research for a couple of decades now.

This phenomenon has helped us to understand the immune system, but our interpretation of it has grown and expanded—particularly with respect to viruses. Almost no virus is protective against allergic disease or other immune diseases. In fact, infections with viruses mostly either contribute to the development of those diseases or worsen them.

The opposite is true of bacteria. There are good bacteria and there are bad bacteria. The good bacteria we call commensals . Our bodies actually have more bacterial cells than human cells. What we’ve learned over the years is that the association with family life and the environment probably has more to do with the microbiome. So one thing I would say is sanitizing every surface in your home to an extreme is probably not a good thing. Our research team showed in animals that sterile environments don’t allow the immune system to develop at all. We don’t want that.

What does contribute to the development of the immune system, if not exposure to viruses?

There are a number of factors that we’ve associated with the hygiene hypothesis over the last 20 years, and these exposures start very early in life. Cesarean sections, which do not allow the baby to travel through the birth canal and get exposed to the mother’s really healthy bacterial content, is a risk factor for many different immune diseases. Getting that early seeding with good bacteria is critical for setting up the child going forward. Breastfeeding also contributes to the development of a healthy immune system.

There are other factors. Our diets have changed dramatically over the years. We eat a lot of processed food that doesn’t have the normal components of a healthy microbiome, like fiber. These healthy bacteria in our gut need that fiber to maintain themselves. They not only are important for our immune system but they’re absolutely critical to us deriving calories and nutrients from our food. All these things contribute to a healthy child.

We’ve also noticed that people who live on farms have fewer of these diseases because they’re exposed to—for lack of a better term—the fecal material of animals. And what we have found is that it’s due to these commensal bacteria. That is one of the components that help us keep a healthy immune system. Most of us will probably not adopt farm life. But we can have a pet, we can have a dog.

I think all the pet lovers out there will be pleased to hear that.

There’s a lot of evidence that owning a pet in early childhood is very protective.

What about the idea that you need to be exposed to viruses in early life because if you get them as an adult, you’ll get more severely ill? We know that’s true for chickenpox, for example. Do you have any concerns about that?

We should rely on vaccines for those exposures because we can never predict who is going to be susceptible to severe illness, even in early childhood. If we look back before vaccines, children under 4 often succumbed to infections. I don’t think we want to return to that time in history.

Let me just give you one example. There’s a virus called RSV, it’s a respiratory virus. Almost all infants are positive for it by the age of 2. But those who get severe disease are more likely to develop allergic disease and other problems. So this idea that we must become infected with a pathogenic virus to be healthy is not a good one.

Even rhinovirus, which is the common cold, most people recover fine. But there’s a lot of evidence that for somebody who is allergic, rhinovirus exposures make them much worse. In fact, most allergic or asthmatic kids suffer through the winter months when these viruses are more common.

And that’s particularly salient because there is a lot of rhinovirus and enterovirus circulating right now.

From my point of view, right now, avoiding flu and COVID-19 is a priority. Those are not going to help you develop a healthy immune response, and in fact, they can do a lot of damage to the lungs during that critical developmental time. Data [show] that children that have more infections in the first 6 months to a year of life go on to have more problems.

It’s always surprising to me when I look at the data of the fraction of time that young children spend with these common colds—and this is pre-pandemic—it’s not uncommon for kids to be sick 50% of the time. That feels right as a parent, but it’s startling.

The other thing people don’t know is that the GI tract is where you get tolerized to all of your foods, allergens and things. Without those healthy bacteria in your gut, you can’t tolerate common allergens.

How does that relate to the guidance that’s changed over the years—that you should withhold peanuts in early life and now you’re supposed to offer them in early life?

The guidance to delay exposure to peanuts didn’t consider the fact that oral exposure to peanuts was not the only exposure kids were getting. There were peanut oils in all kinds of skin creams and other things. So kids got exposed through their skin, but they had no gut protection—and the GI tract is important for a tolerant system. If you have a healthy immune response, you get tolerized in early life.

This concept is a little bit different for those families who may already have a predisposition to allergies. But for the general public, exposure is key to protecting them in early life.

I think some parents look at the guidance that you should now offer peanuts in early life and say, “Are we not doing that with rhinovirus by masking kids or improving ventilation?” How should people think about the development of the immune system for food allergies compared to infections?

The thing about rhinoviruses is that after recovering, you’re not protected from the next infection. There is no real immune protection there. Most of us suffer from colds throughout our whole life. Like I said, bacterial exposure is what’s key to priming the immune response.

Also, we forget that a lot of kids die from the flu. Unlike COVID-19, where younger kids are not quite as susceptible to severe illness, that’s not true for flu. RSV, too, can be quite severe in young children and older adults.

Caitlin Rivers, PhD, MPH , is a senior scholar at the Johns Hopkins Center for Health Security and an assistant professor in Environmental Health and Engineering at the Johns Hopkins Bloomberg School of Public Health.

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Overview of the Scientific Method

10 Developing a Hypothesis

Learning objectives.

Distinguish between a theory and a hypothesis.
Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
Understand the characteristics of a good hypothesis.

Theories and Hypotheses

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.

Theory Testing

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).

Incorporating Theory into Your Research

Characteristics of a Good Hypothesis

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.

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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.

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.

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7 Main Developmental Theories

Child Development Theories of Freud, Erickson, and More

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk, "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

Verywell / JR Bee

Top Theories

Child development theories focus on explaining how children change and grow over the course of childhood. These developmental theories center on various aspects of growth, including social, emotional, and cognitive development.

The study of human development is a rich and varied subject. We all have personal experience with development, but it is sometimes difficult to understand how and why people grow, learn, and act as they do.

Why do children behave in certain ways? Is their behavior related to their age, family relationships, or individual temperaments? Developmental psychologists strive to answer such questions as well as to understand, explain, and predict behaviors that occur throughout the lifespan.

In order to understand human development, a number of different theories of child development have arisen to explain various aspects of human growth.

History of Developmental Theories

Child development that occurs from birth to adulthood was largely ignored throughout much of human history. Children were often viewed simply as small versions of adults and little attention was paid to the many advances in cognitive abilities, language usage, and physical growth that occur during childhood and adolescence.

Interest in the field of child development finally began to emerge early in the 20th century, but it tended to focus on abnormal behavior. Eventually, researchers became increasingly interested in other topics including typical child development as well as the influences on development.

More recent theories outline the developmental stages of children and identify the typical ages at which these growth milestones occur.

Why Developmental Theories are Important

Developmental theories provide a framework for thinking about human growth and learning. But why do we study development? What can we learn from psychological theories of development? If you have ever wondered about what motivates human thought and behavior, understanding these theories can provide useful insight into individuals and society.

An understanding of child development is essential because it allows us to fully appreciate the cognitive, emotional, physical, social, and educational growth that children go through from birth and into early adulthood.

Why is it important to study how children grow, learn, and change? An understanding of child development is essential because it allows us to fully appreciate the cognitive, emotional, physical, social, and educational growth that children go through from birth and into early adulthood.

7 Best-Known Developmental Theories

There are many child development theories that have been proposed by theorists and researchers. Some of the major theories of child development are known as grand theories; they attempt to describe every aspect of development, often using a stage approach. Others are known as mini-theories; they instead focus only on a fairly limited aspect of development such as cognitive or social growth.

Freud's Psychosexual Developmental Theory

Psychoanalytic theory originated with the work of Sigmund Freud . Through his clinical work with patients suffering from mental illness, Freud came to believe that childhood experiences and unconscious desires influenced behavior.

According to Freud, conflicts that occur during each of these stages can have a lifelong influence on personality and behavior. Freud proposed one of the best-known grand theories of child development.

According to Freud’s psychosexual theory, child development occurs in a series of stages focused on different pleasure areas of the body. During each stage, the child encounters conflicts that play a significant role in the course of development.

His theory suggested that the energy of the libido was focused on different erogenous zones at specific stages. Failure to progress through a stage can result in fixation at that point in development, which Freud believed could have an influence on adult behavior.

So what happens as children complete each stage? And what might result if a child does poorly during a particular point in development? Successfully completing each stage leads to the development of a healthy adult personality.

Failing to resolve the conflicts of a particular stage can result in fixations that can then have an influence on adult behavior.

While some other child development theories suggest that personality continues to change and grow over the entire lifetime, Freud believed that it was early experiences that played the greatest role in shaping development. According to Freud, personality is largely set in stone by the age of five.

Erikson's Psychosocial Developmental Theory

Psychoanalytic theory was an enormously influential force during the first half of the twentieth century. Those inspired and influenced by Freud went on to expand upon Freud's ideas and develop theories of their own. Of these neo-Freudians, Erik Erikson's ideas have become perhaps the best known.

Erikson's eight-stage theory of psychosocial development describes growth and change throughout life, focusing on social interaction and conflicts that arise during different stages of development.

While Erikson’s theory of psychosocial development shared some similarities with Freud's, it is dramatically different in many ways. Rather than focusing on sexual interest as a driving force in development, Erikson believed that social interaction and experience played decisive roles.

His eight-stage theory of human development described this process from infancy through death. During each stage, people are faced with a developmental conflict that impacts later functioning and further growth.

Unlike many other developmental theories, Erik Erikson's psychosocial theory focuses on development across the entire lifespan. At each stage, children and adults face a developmental crisis that serves as a major turning point.

Successfully managing the challenges of each stage leads to the emergence of a lifelong psychological virtue.

Behavioral Child Development Theories

During the first half of the twentieth century, a new school of thought known as behaviorism rose to become a dominant force within psychology. Behaviorists believed that psychology needed to focus only on observable and quantifiable behaviors in order to become a more scientific discipline.

According to the behavioral perspective, all human behavior can be described in terms of environmental influences. Some behaviorists, such as John B. Watson and B.F. Skinner , insisted that learning occurs purely through processes of association and reinforcement.

Behavioral theories of child development focus on how environmental interaction influences behavior and is based on the theories of theorists such as John B. Watson, Ivan Pavlov, and B. F. Skinner. These theories deal only with observable behaviors. Development is considered a reaction to rewards, punishments, stimuli, and reinforcement.

This theory differs considerably from other child development theories because it gives no consideration to internal thoughts or feelings. Instead, it focuses purely on how experience shapes who we are.

Two important types of learning that emerged from this approach to development are classical conditioning and operant conditioning . Classical conditioning involves learning by pairing a naturally occurring stimulus with a previously neutral stimulus. Operant conditioning utilizes reinforcement and punishment to modify behaviors.

Piaget's Cognitive Developmental Theory

Cognitive theory is concerned with the development of a person's thought processes. It also looks at how these thought processes influence how we understand and interact with the world.

Theorist Jean Piaget proposed one of the most influential theories of cognitive development.

Piaget proposed an idea that seems obvious now, but helped revolutionize how we think about child development: Children think differently than adults .

His cognitive theory seeks to describe and explain the development of thought processes and mental states. It also looks at how these thought processes influence the way we understand and interact with the world.

Piaget then proposed a theory of cognitive development to account for the steps and sequence of children's intellectual development.

Sensorimotor Stage: A period of time between birth and age two during which an infant's knowledge of the world is limited to his or her sensory perceptions and motor activities. Behaviors are limited to simple motor responses caused by sensory stimuli.
Pre-Operational Stage: A period between ages 2 and 6 during which a child learns to use language. During this stage, children do not yet understand concrete logic, cannot mentally manipulate information, and are unable to take the point of view of other people.
Concrete Operational Stage: A period between ages 7 and 11 during which children gain a better understanding of mental operations. Children begin thinking logically about concrete events but have difficulty understanding abstract or hypothetical concepts.
Formal Operational Stage: A period between age 12 to adulthood when people develop the ability to think about abstract concepts. Skills such as logical thought, deductive reasoning, and systematic planning also emerge during this stage.

Bowlby's Attachment Theory

There is a great deal of research on the social development of children. John Bowbly proposed one of the earliest theories of social development. Bowlby believed that early relationships with caregivers play a major role in child development and continue to influence social relationships throughout life.

Bowlby's attachment theory suggested that children are born with an innate need to form attachments. Such attachments aid in survival by ensuring that the child receives care and protection. Not only that but these attachments are characterized by clear behavioral and motivational patterns.

In other words, both children and caregivers engage in behaviors designed to ensure proximity. Children strive to stay close and connected to their caregivers who in turn provide a safe haven and a secure base for exploration.

Researchers have also expanded upon Bowlby's original work and have suggested that a number of different attachment styles exist. Children who receive consistent support and care are more likely to develop a secure attachment style, while those who receive less reliable care may develop an ambivalent, avoidant, or disorganized style.

Bandura's Social Learning Theory

Social learning theory is based on the work of psychologist Albert Bandura . Bandura believed that the conditioning and reinforcement process could not sufficiently explain all of human learning.

For example, how can the conditioning process account for learned behaviors that have not been reinforced through classical conditioning or operant conditioning According to social learning theory, behaviors can also be learned through observation and modeling.

By observing the actions of others, including parents and peers, children develop new skills and acquire new information.

Bandura's child development theory suggests that observation plays a critical role in learning, but this observation does not necessarily need to take the form of watching a live model.

Instead, people can also learn by listening to verbal instructions about how to perform a behavior as well as through observing either real or fictional characters displaying behaviors in books or films.

Vygotsky's Sociocultural Theory

Another psychologist named Lev Vygotsky proposed a seminal learning theory that has gone on to become very influential, especially in the field of education. Like Piaget, Vygotsky believed that children learn actively and through hands-on experiences.

His sociocultural theory also suggested that parents, caregivers, peers, and the culture at large were responsible for developing higher-order functions. In Vygotsky's view, learning is an inherently social process. Through interacting with others, learning becomes integrated into an individual's understanding of the world.

This child development theory also introduced the concept of the zone of proximal development, which is the gap between what a person can do with help and what they can do on their own. It is with the help of more knowledgeable others that people are able to progressively learn and increase their skills and scope of understanding.

A Word From Verywell

As you can see, some of psychology's best-known thinkers have developed theories to help explore and explain different aspects of child development. While not all of these theories are fully accepted today, they all had an important influence on our understanding of child development.

Today, contemporary psychologists often draw on a variety of theories and perspectives in order to understand how kids grow, behave, and think. These theories represent just a few of the different ways of thinking about child development.

In reality, fully understanding how children change and grow over the course of childhood requires looking at many different factors that influence physical and psychological growth. Genes, the environment, and the interactions between these two forces determine how kids grow physically as well as mentally.

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By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Natural Disaster, Tax Avoidance, and Corporate Pollution Emissions: Evidence from China

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Published: 23 May 2024

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Rui Xu 1 , 2 &
Liuyang Ren 1

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Our study explores how climate risk affects the tax behavior of governments and local firms, subsequently affecting corporate pollution emissions. Using data on Chinese non-state-owned industrial enterprises from 1998 to 2014, we empirically investigate the impact of natural disasters on corporate tax avoidance. The results indicate that companies in earthquake-damaged areas are less likely to avoid taxes than those in unaffected areas. Furthermore, companies that pay more taxes after a disaster can secure favorable government environmental policies, as indicated by a rise in pollution emissions. Moreover, this effect is more pronounced for less polluting firms and firms with higher financial constraints. Our study contributes to the literature on taxation and ESG from the perspective of favor-exchange in government–firm relationships.

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Do Natural Disasters Affect Corporate Tax Avoidance? The Case of Drought

The environmental cost of tax administration: evidence from a regression discontinuity design in China

Tax incentives and environmental protection: evidence from china’s taxpayer-level data, data availability.

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

The risk appears to be manifesting itself along several physical dimensions: a) earthquake risk, which can cause extensive damages in a relatively short period; b) hurricane risk, which has increased in intensity and frequency in different parts of the world; c) drought risk, occur in some particular regions; d) flood risk, affecting predominantly some regions; e) heat risk, which refers to increase in average temperatures over time.

Tax-sharing system gives Chinese local governments tax autonomy to control local corporate taxes.

See the Chinese National Earthquake Response Plan on this page https://www.gov.cn/yjgl/2012-09/21/content_ 2,230,337.htm. (Notice this page is in Chinese; Google Translate can be used to view the content.).

See Earthquake Response Plan in Huangshan City on this page https://www.huangshan.gov.cn/zwgk/public /6615714/10703207.htm. (Notice this page is in Chinese; Google Translate can be used to view the content.).

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Acknowledgements

This work was supported by the National Natural Science Foundation Project of China (Grant No.72302061), the Guangdong Office of Philosophy and Social Science (Project GD23YGL21) and Philosophy and Social Science Foundation of Guangzhou (Project 2023GZGJ58). The corresponding author is Liuyang Ren. All errors remain ours. All co-authors make equal contributions to the formation of this paper.

Guangdong Office of Philosophy and Social Science, GD23YGL21, Liuyang Ren, National Natural Science Foundation of China, 72302061, Liuyang Ren, Philosophy and Social Science Foundation of Guangzhou, 2023GZGJ58, Rui Xu.

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Xu, R., Ren, L. Natural Disaster, Tax Avoidance, and Corporate Pollution Emissions: Evidence from China. J Bus Ethics (2024). https://doi.org/10.1007/s10551-024-05716-w

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MSU’s Folk exposes new symbiosis origin theories, identifies experimental systems for plant life

Contact: Sarah Nicholas

STARKVILLE, Miss.—A Mississippi State faculty member’s work on symbiosis—a mutually beneficial relationship between living organisms—is pushing back against the newer theory of a “single-origin” of root nodule symbiosis (RNS)—that all symbiosis between plant root nodules and nitrogen-fixing bacteria stems from one point—instead suggesting a “multiple-origin” theory of symbiosis which opens a better understanding for genetically engineering crops.

Ryan A. Folk, an assistant professor in the MSU Department of Biological Sciences and herbarium curator, is an author on a paper published this month in Nature Communications examining RNS , which allows plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. He joins investigators at the University of Florida and an international team.

“A story of a single origin has become very popular in recent years, particularly among those hoping to genetically engineer symbiosis in crop plants, but using genomic data from 13,000 species and sophisticated statistical models, we confidently identified a scenario involving multiple origins. Symbiosis is a complex trait and our work identifies ideal experimental systems for better understanding the molecular mechanisms that led to the gain of symbiosis,” Folk said. “Our work is the first major push-back against the idea of a single origin as advocated by those working on genome comparisons.”

Folk said the single origin idea would suggest that the genetic engineering of crops such as rice and maize to work with nitrogen-fixing bacteria is a “lower hurdle” to cross.

“Our results, which point to multiple origins, complicates the picture because it suggests a lesser role for shared genetic machinery,” Folk said. “This would make it harder to transform crop plants that are not legumes to engage in a similar nitrogen-fixing symbiosis, but multiple origins also means diverse machinery, or as we argue, an enhanced ‘evolutionary palette’ to guide such experiments,” he said.

Folk’s paper laid the groundwork for his fall 2023 $1.6 National Science Foundation grant for detailed study of nitrogen conversions in nature.

Folk’s MSU lab uses genomic and bioinformatic techniques to document the origins of plant diversity from evolutionary and ecological perspectives using a variety of plant groups and habitats. His work is based in MSU’s herbarium, housing approximately 38,000 vascular plant specimens from around the world with an emphasis on the Southeastern U.S.

For more details about MSU’s College of Arts and Sciences or the Department of Biological Sciences, visit www.cas.msstate.edu or www.biology.msstate.edu .

Mississippi State University is taking care of what matters. Learn more at www.msstate.edu .

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Lauren Brown named professional development director

Lauren Brown is the new director of professional development for the Division of Student Affairs of Academic Support. In this role – a new one for the division – she will contribute to the professional growth and career development of Student Affairs and Academic Support staff members.

Brown has more than a decade of experience in higher education, including roles in student success; wellness education; and orientation, transition and parent programs.

Most recently, she served as associate director of early alert and intervention for the University of South Carolina Student Success Center.

Brown earned a master’s degree in higher education administration from the University at Buffalo, State University of New York, and a bachelor’s degree in human development from the State University of New York at Oswego.

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Impact Criteria for Faculty Career Development

Business faculty often find their schools’ expectations for societal impact unclear, especially in relation to their intellectual contributions.
Guided by AACSB accreditation standards, Aalborg University Business School adopted more comprehensive faculty development strategies to generate impact in four areas: academic, educational, business, and public .
The success of this strategy rests on taking three steps: clarifying criteria for promotion and tenure, adopting data collection systems, and assigning staff managers to support faculty’s impact activities.

Business schools have been increasingly expected to demonstrate tangible societal impact. It’s clear that schools can achieve positive impact by educating their students in principles such as leadership, strategy, and business ethics. But to truly make a positive difference in the world, we also must foster research that contributes to economic, environmental, and societal development.

One of the most effective ways that schools can achieve this goal is by closely aligning their faculty’s career development with the requirements of societal impact. Unfortunately, faculty often remain unclear about their institutions’ impact-focused goals and requirements that relate not only to teaching and project management, but also to publishing, disseminating, and securing funding for their research. Even after professors achieve tenure, they are likely to find it difficult to discern how they can most effectively contribute to the broader purpose of their business schools while advancing their academic careers.

As we worked toward initial AACSB accreditation at Aalborg University Business School (AAUBS) in Denmark, the challenge of aligning societal impact with faculty development was a recurring theme. But we soon realized that we could achieve our impact ambitions if we aligned our faculty development with the AACSB Business Accreditation Standards .

For this strategy to be successful, we knew that we needed to take three essential steps: clarify our criteria for faculty promotion and tenure, be disciplined about gathering and analyzing data regarding the impact of faculty research, and assign staff managers to support faculty as they pursue impact-focused scholarship.

Connecting Impact With Intellectual Contributions

Given that societal impact is a fundamental pillar of AACSB accreditation, we could leverage our accreditation activities as a foundation for impact. For instance, AACSB accreditation Standards 8 and 9 focus on establishing a framework for assessing impact that is closely aligned with an institution’s mission, vision, and expectations regarding thought leadership, as described in Standard 1. While the interlinking of Standards 1, 8, and 9 is evident, we discovered additional value in connecting our activities directly to the assessment of faculty classiﬁcations, as outlined in Standard 3.

One of the most effective ways that schools can make a positive difference in the world is by closely aligning their faculty’s career development with the requirements of societal impact.

Traditionally, academic peer-reviewed publications have served as the primary metric for faculty classiﬁcations. For faculty to maintain their classification as Scholarly Academics under the AACSB standards, they must produce a certain number of publications within a set number of years. However, once we integrated our expectations for societal impact into the faculty classiﬁcation process, we strengthened the connection between the accreditation standards and the narrative of our impact-driven business school.

We were also helped by the fact that Standards 8 and 9 take a holistic approach that supports the evolution of purpose-led business schools. The AACSB accreditation standards offer individual schools the ﬂexibility to tailor their faculty portfolios and associated measures to their unique missions. Unlike the more standardized structures of other impact rankings, the ﬂexibility of Standards 8 and 9 enables business schools to demonstrate how they create impact along several dimensions.

Four Dimensions of Impact

As we delved into the interplay between Standards 1, 8, and 9, we asked our seven research groups to outline group-based research strategies that align with the overarching business school mission and vision.

The groups drafted their research strategies in 2022. However, as they completed this undertaking, it became evident that we needed to be much clearer about how we would integrate societal impact at the levels of the business school, research groups, and individual researchers.

Furthermore, many research groups highlighted that academic impact is merely one aspect of a modern business school’s focus, which underscored the need to consider broader strategic priorities. Ultimately, we identiﬁed the four dimensions of our school’s impact: academic, educational, business , and public .

We then outlined how each dimension uniquely contributes to our strategic objectives:

Academic Impact (AI) produces internationally recognized and often interdisciplinary research on contemporary issues that push the boundaries of knowledge toward new and enhanced business practices.
Educational Impact (EI) transforms students into lifelong learners through problem-based learning that teaches fundamental and advanced economics and business knowledge in interdisciplinary contexts.
Business Impact (BI) turns our school into a regional hub of knowledge that facilitates learning and the exchange of ideas with private, public, and third-sector organizations through cooperation and networks, while exposing students to international perspectives.
Public Impact (PI) allows us to be recognized as a business school that has societal relevance and that is engaged in broader public debate, as well as national and international policy development.

Diagram of four dark green teardrop shapes coming together at their points and going outward up, down, and to each side. In each teardrop, in lime green, are icons and words linked to the four types of busines school impact: The upper teardrop has a book icon with the words "Academic Impact" underneath the icon.; the teardrop going to the right has a briefcase icon with the words "Business Impact" above the icon; the teardrop pointing downward has a globe icon with the words "Public Impact" above the icon; the teardrop going to the left has a graduate cap icon and the words "Educational Impact" beneath the icon.

To construct a clearer and more comprehensive faculty development strategy, we needed to integrate all four areas of impact into the business school’s requirements for faculty intellectual contributions.

Enhancing Impact Through Faculty Classification

After we identified our dimensions of impact, we delineated the four areas into 24 subcategories, each reﬂecting different dimensions of scholarly excellence (see table below). This categorization offers a nuanced understanding of faculty ’s collective contributions across academic, educational, business, and public dimensions.

Next, we classified all activities into these subcategories documented by faculty members in PURE , our school’s research management system. This research portal serves as a full-text repository, a platform for research dissemination, and a collaborative showcase for faculty activities on local, national, and international levels.

In practice, this categorization requires that faculty members at least annually update their contributions to impact in PURE to maintain their faculty classiﬁcation for AACSB accreditation. With our expanded focus on impact, our qualiﬁcation criteria now extend beyond targets for research published in recognized peer-reviewed journals. The criteria also mandate that faculty make a speciﬁc number of additional intellectual contributions within the 24 subcategories to underscore the diverse nature of the school’s overall impact.

At the business school level, metrics based on intellectual contributions are integral to the school’s annual strategic assessment. These metrics help in continually refining the university’s target agreement, for which the business school must specify the impact targets it aims to achieve in the upcoming period.

On an individual level, the registrations of intellectual contributions form the basis of the annual development dialogues between employees and staff managers. During these meetings, staff managers engage in constructive dialogues with faculty members about their contributions, identify areas of strength, and pinpoint opportunities for improvement that are aligned with each academic’s career progression aspirations.

The data drawn from the research management system provides a comprehensive view of our faculty members’ work. We can determine if they have met the minimum requirement of academic peer-reviewed publications to retain their status as Scholarly Academics and create impact profiles for each professor.

We can illustrate this process by examining the impact profiles of three hypothetical faculty members. For example, the data might show that, over the last year, Professor A earned 150 citations in the press, published in 3 practitioner- or industry-focused outlets, and consulted with companies (categories 24, 17, and 18). Professor B disseminated research via 15 webinars and podcasts, received external research funding, and taught courses at an international university (categories 13, 4, and 14). Professor C has published several articles in peer-reviewed journals, organized two conferences, and served on a company’s advisory board (categories 1, 11, and 19).

Our staff managers will take different approaches to professional development, depending on the impact profile reflected in each professor’s intellectual contribution portfolio:

Given Professor A’s focus on business and public impact, the staff manager might encourage her to promote her expertise to a larger audience via participation in expert groups and committees, or even position her to act as a public representative of the school.
Because of Professor B’s focus on educational and academic impact, his staff manager might suggest that he better balance his external teaching with internal responsibilities, while offering him greater administrative support to develop new project proposals.
Inspired by Professor C’s more traditional intellectual profile, based on academic and business impact, her staff manager might suggest that she leverage her advisory board involvement to attract more external funding, which she might use to create a more specialized research environment within the business school.

These examples illustrate how business schools can use impact profiles to design personalized development plans, ensuring that faculty members continue to grow in areas that align with both their individual strengths and the school’s efforts to generate broader societal impact.

Three Steps to Drive Faculty Impact

When more closely linking societal impact and faculty career development, business schools should consider addressing three important areas of their promotion and tenure processes:

Clarity of promotion criteria and faculty requirements. In academia, conducting research is often a solo endeavor, with no precise output measures or deﬁned requirements. But a lack of specificity regarding promotion criteria and expectations for impact reduces transparency and hinders the advancement of a school’s impact-focused mission.

By leveraging accreditation activities to set clear criteria and requirements, schools can support individual researchers in their career advancement in ways that align with larger institutional objectives.

It is essential that business schools implement research management systems that facilitate easy documentation of impact-related activities.

Disciplined recording of data relating to impact. To enable the school to measure the full range of faculty’s impact-related intellectual contributions, professors will need to consistently submit their individual data to the school’s tracking system. While many researchers are used to reporting their journal publications and books, they may overlook the importance of registering these and other activities with societal impact in mind.

For that reason, it is essential that business schools implement research management systems that facilitate easy documentation of these efforts and promote impact-oriented outcomes.

Ongoing faculty development support. Based on insights gleaned from our research management system, we know that staff managers provide valuable personalized support that nurtures the development of individual researchers. This approach mirrors the employee development programs at industrial organizations, where managers foster the professional progress of employees.

Staff managers do not just offer a more comprehensive view of our faculty’s job performance. They also cultivate the leadership potential of professors who are proﬁcient in different forms of impact.

By integrating aspirations for societal impact into faculty development, we can achieve three critical goals: living up to the accreditation requirements, supporting faculty as they pursue their chosen career paths, and ensuring that the business school makes a positive difference in society.

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Housing Supports - Including Boarders’ Contributions in the Calculation of Subsidies for Private and Social Housing

Initiative Sponsors:

Ministry of Social Development and Ministry of Housing & Urban Development.

This policy adjustment ensures that the board payments an individual receives are counted when calculating their eligibility for housing subsidies. Only those receiving board payments are affected by this change because they can use these payments to offset their housing costs.

Currently, if a person has three or more boarders, the board payments are considered when determining that person’s entitlements to housing subsidies. This adjustment extends this consideration to the first and second boarders too.

This change also makes the welfare system fairer by treating boarders' contributions more consistently with how other earnings impact beneficiaries’ entitlements. It also prevents the double counting of accommodation costs within a single household where the primary tenant and the boarder are both receiving a housing subsidy.

$150.957 million in operating funding is expected to be saved by adjusting how contributions from boarders are considered when calculating the Accommodation Supplement, Temporary Additional Support, Special Benefit, and the Income-Related Rent Subsidy. These savings are partially offset by a capital implementation cost of $6.894 million.

This policy adjustment will not change the housing subsidies of impacted individuals until 2026. Legislative amendment, and further policy design work, is required to implement this adjustment.

The financial impacts are:

OPEX Savings

$129.541 million in Vote Social Development, and
$21.416 million in Vote Housing and Urban Development

CAPEX costs

$6.894 million in Vote Social Development.

Vote Social Development Opex:

Vote Social Development Capex:

Vote Housing and Urban Development Opex:

Why is the Government adjusting how housing subsidies are calculated for those who receive board payments?

The adjustment means the earnings a person receives from board payments will be considered when calculating their housing subsidies. It recognises that people who can reduce their housing costs by taking on a boarder have an advantage over those without boarders who cannot utilise board payments to offset housing costs.
Currently, the treatment of board payments is unfair and inconsistent. Beneficiaries can have their entitlements reduced if they receive other earnings, but board payments a person receives are not factored into the calculation of their housing subsidy if they have one or two boarders.
This adjustment prevents accommodation costs from being double counted in the calculation of multiple housing subsidies where both a homeowner or primary tenant and their boarder receive Government housing subsidies.

Which housing subsidies will this adjustment affect?

Accommodation Supplement, Temporary Additional Support, Grand-parented Special Benefit, Student Allowance Accommodation Benefit for Sole Parents (as calculated using the Accommodation Supplement rules), Away from Home Allowance (as calculated using the Accommodation Supplement rules) and the Income-Related Rent Subsidy.

When will the adjustment be implemented?

It will begin to impact Accommodation Supplement, Temporary Additional Support, and Special Benefit recipients in early to mid-2026.
Changes to the Income-Related Rent Subsidy will begin to impact recipients with any boarders over the course of a 12-month rollout, commencing early to mid-2026. The full effect of these changes will be realised after 14 months, due to the 60-day notice period required for changes to the Income-Related Rent that a social housing tenant pays.

How many people will be impacted by the adjustment?

It is estimated that approximately 12,300 Accommodation Supplement recipients and 6,300 Income-Related Rent Subsidy recipients currently have boarders.
Note these are only estimates, as an exact head count of people with boarders is not currently available.

How are payments from boarders currently treated?

One or Two Boarders: If a person has one or two boarders, these board payments are not considered currently when calculating the person’s housing subsidies.
Three or More Boarders: If a person has three or more boarders, the board payments of the third and subsequent boarders are considered when calculating the person’s housing subsidies.

Policy Adjustment

The changes being made through this initiative will mean that the board payments from all boarders a person has will be considered when calculating the person’s housing subsidies.

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General Assembly Pays Tribute to Late President of Iran, Hailing His Visionary Leadership, Contributions for Multilateralism, Development

The General Assembly convened today to pay tribute to Seyyed Ebrahim Raisi, the late President of Iran, and his entourage, all of whom perished in a tragic helicopter accident on 19 May.

Following the observing of a minute of silence in their memory, Dennis Francis (Trinidad and Tobago), President of the General Assembly, offered “our deepest condolences to the Government and people of Iran”, recalling that President Raisi “led his country’s contribution to shape the tenets of our multilateral system and international cooperation”. Just 10 months before his demise, President Raisi addressed the General Debate of the seventy-eighth session in September — clearly articulating his country’s priorities.

The General Assembly President also honoured the memory of Foreign Minister Hossein Amirabdollahian — “a consummate diplomat who faithfully stood alongside President Raisi in representing Iran on the global stage”. Recalling a bilateral meeting with the Foreign Minister on 21 September 2023, he expressed his great appreciation for his diplomatic acumen. Encouraging “the Iranian people to gather courage and come to terms with their profound loss”, he voiced confidence that “their resilience will guide them to demonstrate remarkable strength in this difficult time of mourning”.

Also extending his condolences to the families, the Government and people of Iran, António Guterres, Secretary-General of the United Nations, observed that President Raisi “led Iran at a challenging time for the country, the region and globally”. He recalled that just hours before his death, President Raisi met with his Azerbaijani counterpart to inaugurate the Qiz Qalasi dam, the largest joint water project between the two countries.

“In these difficult times, international and regional cooperation are needed more than ever,” Secretary-General Guterres stated, in order to build confidence, prevent conflict and resolve disputes. To this end, he assured the Iranian people that the United Nations stands in solidarity with them and in the quest for peace, development and fundamental freedoms.

Echoing those sentiments, the representative of Burundi, speaking for the African Group, noted that President Raisi “was a visionary leader” dedicated to the principles of brotherhood, solidarity and multilateralism. Under his leadership, the relationship between Iran and Africa expanded across various sectors, including trade, education and health — collaborations that “have had a lasting impact on the development and progress” of African nations and people who have been historically left behind.

Pakistan’s representative, speaking for the Organization of Islamic Cooperation (OIC), took solace in the late President’s historical contributions to the vision and mission of that body — notably its central codes of restoring the inalienable rights of the Palestinian people and protecting the sanctity of the holy mosque of Al-Quds. Thanks to his leadership, wisdom and consensus politics, the OIC has become stronger in promoting global peace, security and prosperity, he noted.

For his part, the representative of Uganda, speaking for the Non-Aligned Movement, emphasized that President Raisi and Foreign Minister Abdollahian were instrumental in strengthening cooperation among members of the bloc. Under their guidance, Iran played a crucial role in enhancing cooperation among developing countries, with vision and leadership.

Other speakers also highlighted the late President and Foreign Minister’s career achievements in promoting Iranian growth, justice and progress, and crucial roles in fostering collaboration among developing countries, including the representative of Haiti, speaking for the Group of Latin American and Caribbean States (GRULAC), the representative of Qatar, for the Gulf Cooperation Council, and Vanuatu’s representative, for the Group of Asia-Pacific States.

Expressing deep gratitude to President Francis, the Secretary-General and all speakers, the representative of Iran stressed that President Raisi and Minister Abdollahian “were visionary leaders” whose terms were “dedicated to promoting peace, stability, and sustainable security in our region and beyond”. Under President Raisi’s leadership, the Government of Iran consistently participated in all efforts to preserve peace and security in the Persian Gulf region, building “bridges of brotherhood” while emphasizing development and enhancing ties with other parts of the world, particularly Africa and Latin America.

He also hailed Foreign Minister Amirabdollahian as a distinguished diplomat, whose work on the regional and international stage was characterized by a deep understanding of the complexities of international relations and a relentless pursuit of mutual respect. Citing both the President and the Foreign Minister as “not just figures of authority but also symbols of hope, resilience and the enduring power of good governance and diplomacy”, he said that Iran would continue its journey under the next President’s leadership to be selected at the upcoming election set for 28 June.

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Developing Theories & Hypotheses

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2.5: Developing a Hypothesis

Learning objectives.

Distinguish between a theory and a hypothesis.
Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
Understand the characteristics of a good hypothesis.

Theories and Hypotheses

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.

Theory Testing

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 $\PageIndex{1}$ 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).

Incorporating Theory into Your Research

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.

Zajonc, R. B. (1965). Social facilitation. Science, 149 , 269–274 ↵
Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61 , 195–202. ↵
Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach. Journal of Personality and Social Psychology, 13 , 83–92. ↵
Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

How the freshly selected regional centres will bolster the implementation of the Biodiversity Plan

At the fourth meeting of the Subsidiary Body on Implementation (SBI 4) of the Convention on Biological Diversity (CBD), the Parties selected 18 regional organizations spanning the globe in a multilateral push to bolster the implementation of the Kunming-Montreal Global Biodiversity Framework, also known as the Biodiversity Plan , through science, technology and innovation:

Africa: The Central African Forest Commission (COMIFAC), the Ecological Monitoring Center (CSE), the Regional Centre for Mapping of Resources for Development (RCMRD), the Sahara and Sahel Observatory (OSS), and the South African National Biodiversity Institute (SANBI).
Americas: The Alexander von Humboldt Biological Resources Research Institute, the Secretariat of the Caribbean Community (CARICOM), and the Central American Commission on Environment and Development (CCAD).
Asia: ASEAN Centre for Biodiversity (ACB); IUCN Asia Regional Office; IUCN Regional Office for West Asia (ROWA); Nanjing Institute of Environmental Sciences (NIES); Regional Environmental Centre for Central Asia (CAREC).
Europe: European Commission - Joint Research Centre of the European Commission (JRC); IUCN Centre for Mediterranean Cooperation; IUCN Regional Office for Eastern Europe and Central Asia (ECARO); Royal Belgian Institute for Natural Sciences (RBINS).
Oceania: The Secretariat of the Pacific Regional Environment Programme (SPREP).

Here are five facts about the selection of these centres and the way they will bring the Parties to the CBD closer to halting and reversing biodiversity loss by 2030 :

1. Nested in existing institutions for efficiency and rapid deployment

The selected centres are hosted by existing institutions that have responded to the CBD Secretariat’s call for expression of interest. The applications received translate a global commitment to implementing the Biodiversity Plan. This global network of centres forms part of the technical and scientific cooperation mechanism under the CBD. They will contribute to filling gaps in international cooperation and catering to the needs of countries in the regions that they cover.

2. One-stop-shop for scientific, technical and technological support

The mandate of the centres is to catalyse technical and scientific cooperation among the Parties to the Convention in the geographical regions they cover. The support they offer may include the sharing of scientific knowledge, data, expertise, resources, technologies, including indigenous and traditional technologies, and technical know-how with relevance to the national implementation of the 23 targets of the Biodiversity Plan. Other forms of capacity building and development may also be provided.

3. Complementarity with existing initiatives

The expected contributions of the centres will constitute a surge of capacity, complementing small-scale initiatives for technical and scientific cooperation among its Parties through programmes such as the Bio-Bridge Initiative . The newly selected centres will expand, scale-up and accelerate efforts in support of the implementation of the Biodiversity Plan.

4. Delivering field support tailored to regional specificities

Countries around the world face well recognized challenges in aligning with universally agreed targets while considering biophysical specificities and national circumstances. The regional centres will provide regionally appropriate solutions.

5. Building on and amplifying existing cooperation

Many examples around the world demonstrate the benefits of transboundary cooperation. In South Africa, the “Black Mambas” Anti-Poaching Unit has benefited from Dutch expertise in fitting rhinoceros with subcutaneous sensors and horn transmitters to track their movements across the Greater Kruger National Park.

On the other side of the Atlantic Ocean, non-governmental organization Corales de Paz (Colombia) shared their “Caribbean Reef Check” methodology and “Reef Repair Diver “programs with Ecuador-based CONMAR. Participants in CONMAR-organized training camps could thus benefit from expertise in coral reef monitoring and coral gardening.

The newly selected centres will seek to expand this constellation of bright spots of cooperation for nature and for people.

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2.4 Developing a Hypothesis
A theory is broad in nature and explains larger bodies of data. A hypothesis is more specific and makes a prediction about the outcome of a particular study. Working with theories is not "icing on the cake." It is a basic ingredient of psychological research. Like other scientists, psychologists use the hypothetico-deductive method.
Developing a Hypothesis
Theories and Hypotheses. 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 ...
Hypothesis
A hypothesis is a short statement that can be tested and gives a possible reason for a phenomenon or a possible link between two variables. In the setting of scientific research, a hypothesis is a tentative explanation or statement that can be proven wrong and is used to guide experiments and empirical research. Figure 1: What is Hypothesis.
Research Hypothesis In Psychology: Types, & Examples
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.
2.4: Developing a Hypothesis
A theory is broad in nature and explains larger bodies of data. A hypothesis is more specific and makes a prediction about the outcome of a particular study. Working with theories is not "icing on the cake." It is a basic ingredient of psychological research. Like other scientists, psychologists use the hypothetico-deductive method.
Scientific Hypotheses: Writing, Promoting, and Predicting Implications
A snapshot analysis of citation activity of hypothesis articles may reveal interest of the global scientific community towards their implications across various disciplines and countries. As a prime example, Strachan's hygiene hypothesis, published in 1989,10 is still attracting numerous citations on Scopus, the largest bibliographic database ...
What is a Hypothesis
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 ...
Developing the research hypothesis
The research hypothesis is needed for a sound and well-developed research study. The research hypothesis contributes to the solution of the research problem. Types of research hypotheses include inductive and deductive, directional and non-directional, and null and alternative hypotheses. Rejecting the null hypothesis and accepting the ...
Chapter 6
Chapter 6 Overview. This chapter discusses the third step of the SGAM, highlighted below in gold, Hypothesis Development. A hypothesis is often defined as an educated guess because it is informed by what you already know about a topic. This step in the process is to identify all hypotheses that merit detailed examination, keeping in mind that ...
3.5: Developing A Hypothesis
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 it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical.
Developing the Research Hypothesis
The research hypothesis is needed for a sound and well-developed research study. The research hypothesis contributes to the solution of the research problem. Types of research hypotheses include inductive and deductive, directional and non-directional, and null and alternative hypotheses. Rejecting the null hypothesis and accepting the ...
Reviewing the Literature, Developing a Hypothesis, Study Design
Abstract. Rigorous research investigation requires a thorough review of the literature on the topic of interest. This promotes development of an original, relevant and feasible hypothesis. Design of an optimal study to test the hypothesis then requires adequate power, freedom from bias, and conduct within a reasonable timeframe with resources ...
The Role of Hypotheses in Research Studies: A Simple Guide
Essentially, a hypothesis is a tentative statement that predicts the relationship between two or more variables in a research study. It is usually derived from a theoretical framework or previous ...
How to Implement Hypothesis-Driven Development
Practicing Hypothesis-Driven Development is thinking about the development of new ideas, products and services - even organizational change - as a series of experiments to determine whether an expected outcome will be achieved. The process is iterated upon until a desirable outcome is obtained or the idea is determined to be not viable.
Developing a Theory in Academic Research: A Review of Experts' Advice
This paper reviews and collates the views of scholars on what a theory is and how a good theory can be developed. It explains the concept of a theory, and the different components that make up a ...
PDF Chapter 3: Development of Hypotheses and Research Methodology
3.1 Introduction. This chapter will illustrates how the research was designed and implemented. gathering and data analysis used for the study. It will start with the. development of the four hypothesis based on the previous literature. Subsequently it followed with the development of the research framework.
Is the Hygiene Hypothesis True?
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Developing a Hypothesis
Theories and Hypotheses. 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 ...
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7 Main Developmental Theories. Child development theories focus on explaining how children change and grow over the course of childhood. These developmental theories center on various aspects of growth, including social, emotional, and cognitive development. The study of human development is a rich and varied subject.
A Hypothesis contributes to the development of
Answer» A. Theory. 2.8k. 0. Do you find this helpful? 36. View all MCQs in. Research Methodology (RM)
Natural Disaster, Tax Avoidance, and Corporate Pollution ...
Natural disasters not only directly affect the economic development of the affected area but also affect the stability of the local social order (Pelling et al., 2002). ... Finally, our study contributes to social exchange theory by examining the economic consequences of climate risk. We extend the social exchange theory by using it to explain ...
A Hypothesis contributes to the development of
A good hypothesis should be Hypothesis cannot be stated in Which of the following is not the requirement of a hypothesis? What type of research would be least likely to include a research hypothesis? A null hypothesis is Research hypothesis are
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Contact: Sarah Nicholas Ryan A. Folk (OPA photo) STARKVILLE, Miss.—A Mississippi State faculty member's work on symbiosis—a mutually beneficial relationship between living organisms—is pushing back against the newer theory of a "single-origin" of root nodule symbiosis (RNS)—that all symbiosis between plant root nodules and nitrogen-fixing bacteria stems from one point—instead ...
Lauren Brown named professional development director
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Impact Criteria for Faculty Career Development
Guided by AACSB accreditation standards, Aalborg University Business School adopted more comprehensive faculty development strategies to generate impact in four areas: academic, educational, business, and public. The success of this strategy rests on taking three steps: clarifying criteria for promotion and tenure, adopting data collection ...
Housing Supports
This change also makes the welfare system fairer by treating boarders' contributions more consistently with how other earnings impact beneficiaries' entitlements. It also prevents the double counting of accommodation costs within a single household where the primary tenant and the boarder are both receiving a housing subsidy.
General Assembly Pays Tribute to Late President of Iran, Hailing His
Pakistan's representative, speaking for the Organization of Islamic Cooperation (OIC), took solace in the late President's historical contributions to the vision and mission of that body — notably its central codes of restoring the inalienable rights of the Palestinian people and protecting the sanctity of the holy mosque of Al-Quds.
Developing Theories & Hypotheses
Theories and Hypotheses. 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 ...
How the freshly selected regional centres will bolster the
Other forms of capacity building and development may also be provided. 3. Complementarity with existing initiatives The expected contributions of the centres will constitute a surge of capacity, complementing small-scale initiatives for technical and scientific cooperation among its Parties through programmes such as the Bio-Bridge Initiative.

2.4 Developing a Hypothesis

Theories and Hypotheses

Theory Testing

Incorporating Theory into Your Research

Characteristics of a Good Hypothesis

Key Takeaways

Share This Book

Developing a Hypothesis

Learning Objectives

Theories and Hypotheses

Theory Testing

Incorporating Theory into Your Research

Characteristics of a Good Hypothesis

Share This Book

What Is Hypothesis?

Characteristics Of Hypothesis

Sources Of Hypothesis

Types Of Hypothesis

Simple Hypothesis

Complex Hypothesis

Directional Hypothesis

Non-directional Hypothesis

Null Hypothesis

Associative and Causal Hypothesis

Examples Of Hypothesis

Functions Of Hypothesis

Importance Of Hypothesis

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Research Hypothesis In Psychology: Types, & Examples

Some key points about hypotheses:

Types of Research Hypotheses

Null Hypothesis

Nondirectional Hypothesis

Directional Hypothesis

Falsifiability

Can a Hypothesis be Proven?

How to Write a Hypothesis

More Examples

Scientific Hypotheses: Writing, Promoting, and Predicting Implications

Lilit Ayvazyan

Ulzhan Mukanova

Marlen Yessirkepov

George D. Kitas

INTRODUCTION

EXAMPLES OF INFLUENTIAL SCIENTIFIC HYPOTHESES

WRITING SCIENTIFIC HYPOTHESES

ETHICAL IMPLICATIONS

WHERE TO PUBLISH HYPOTHESES

CITATIONS AND SOCIAL MEDIA ATTENTION

What is a Hypothesis – Types, Examples and Writing Guide

Types of Hypothesis

Research Hypothesis

Null Hypothesis

Alternative Hypothesis

Directional Hypothesis

Non-directional Hypothesis

Statistical Hypothesis

Composite Hypothesis

Empirical Hypothesis

Simple Hypothesis

Complex Hypothesis

Applications of Hypothesis

How to write a Hypothesis

Identify the Research Question

Conduct a Literature Review

Determine the Variables

Formulate the Hypothesis

Write the Null Hypothesis

Refine the Hypothesis

Examples of Hypothesis

Purpose of Hypothesis

When to use Hypothesis

Characteristics of Hypothesis