after creating a hypothesis janis

Professionalism/Irving Janis and Groupthink

“	A mode of thinking that people engage in when they are deeply involved in a cohesive in-group, when the members' strivings for unanimity override their motivation to realistically appraise alternative courses of action. 1]	”

Groupthink is a phenomenon that occurs when members of a cohesive group are concerned with quickly reaching a consensus in their decision making without critically analyzing and evaluating ideas. The term was coined by William H. Whyte in 1952 and was studied extensively by Irving Janis . Janis analyzed numerous foreign policy disasters such as Japanese attack on Pearl Harbor and Bay of Pigs and found group cohesion to be the cause.

1 Causes and Symptoms of Groupthink
2.1 Challenger
2.2 Pearl Harbor
2.3.1 Cuban Missile Crisis
2.4.1 Janis' Symptoms of Groupthink Demonstrated by Religion
3 Research Findings and Laboratory Tests
4 Preventing Groupthink
6 References

Causes and Symptoms of Groupthink

Irving Janis identified a number of group properties that would lead to the emergence of groupthink:

Directive and promotional leadership
Cohesiveness of the group
Insulation of the group from the outside
Lack of methodical decision-making procedures [ 2 ]

Groupthink encompasses a number of symptoms which frequently lead to poor decision making:

Illusions of invulnerability
Illusions of unanimity
Rationalization of the warnings
Intolerance to those opposed to the group and whistle-blowers
Self-censorship of ideas deviating from the group consensus
Complete faith in the morality of the group

Case Studies of Groupthink

These case studies highlight the importance of recognizing and avoiding groupthink as a professional engineer.

Challenger was destroyed in a launching accident on January 28, 1986. Cause of the accident was attributed to a faulty O-ring on the solid-fuel rocket booster which failed in the cold weather. All seven crew members died on board, including a woman who would have been the first teacher in space .

From Janis’s perspective, groupthink was responsible for the Challenger disaster, specifically cohesiveness, directive leadership, and group insulation. This case exhibited many symptoms of groupthink: launch crew members rationalized warnings from the engineers, they had an illusion of invulnerability based on their past success, and the managers belittled the engineers for always wearing their "engineering hats" and stereotyped them as ignorant.

Pearl Harbor

Pearl Harbor demonstrates two symptoms of groupthink: illusions of invulnerability creating excessive optimism and encouraging risk taking, and rationalizing warnings that might challenge the group’s assumptions. Americans ignored the fact that Japan had a tendency to launch brutal attacks before declaring war. [ 3 ] In fact, the US government underestimated the Japanese' intentions and continued sending scrap iron, oil, and other raw materials to Japan well into 1940. [ 3 ] Nine years before the bombing of Pearl Harbor, Admiral Frank Schofield anticipated a possible attack on Hawaii from the Pacific. The military confirmed his theory that aircrafts attacking from the Pacific would be undetected and would wreak havoc on the harbor. Despite these results, the military refused to re-examine their defenses.

Bay of Pigs

The Bay of Pigs Invasion was an assault on Cuba in 1961 by approximately 1400 United States trained Cuban exiles. The invasion was an utter failure when about 20,000 Cuban soldiers ended the assault within three days. Irving Janis attributed the cause of the disaster to groupthink.

Janis attributed the causes of groupthink in the Bay of Pigs to cohesion, secrecy, biased leadership, and lack of critical methodology [ 1 ] . One group would make decisions started by another group--which contributed to cohesion--since many considered a good start to the presidential term to be more important than the decision. The Bay of Pigs was meant to be a surprise invasion, so secret meetings were held with little outside communication. Kennedy 's presence at meetings inspired biased leadership since no one wanted to question his statements. Finally, they lacked methodical decision-making procedures. These factors all led to illusions of invulnerability, illusions of unanimity and suppression of personal doubt among advisers.

Cuban Missile Crisis

Irving Janis used the Cuban Missile Crisis to contrast the disaster at the Bay of Pigs. The Cuban Missile Crisis was a thirteen day long diplomatic crisis where the United States fought to keep Soviet missiles from being set up in Cuba.

After witnessing the failure of his administration at the Bay of Pigs, Kennedy made significant changes to the way that decisions were made within his offices.

Advisers were asked to join discussions, not only as representatives with narrow responsibilities, but ready to think critically about all aspects of policy.
Meetings were more open and less formal. Guests were invited frequently and explicitly asked to voice detailed opinions.
Rather than always meeting as a full Executive Committee, meetings consisted of subgroups which included various White House Staff.
Kennedy frequently chose to not attend meetings so he would not influence the opinions of group members.

These changes significantly improved the decision-making process of Kennedy's administration and enabled them to successfully negotiate the removal of the missiles. When Janis evaluated the new decision making process, he determined that no symptoms of groupthink were evident.

Religion is “a specific fundamental set of beliefs and practices generally agreed upon by a number of persons or sects,” [ 4 ] . It is a group belief system, which involves organized behaviors and rituals. Directive leadership is a fundamental part of many religions, and homogeneity of members’ social background and ideology is inherent to religion in general, [ 5 ] which are both causes of groupthink.

Janis' Symptoms of Groupthink Demonstrated by Religion

Unquestioned belief in the morality of the group, causing members to ignore the consequences of their actions : As Charles Selengut states, “the history and scriptures of the world’s religions tell stories of violence and war as they speak of peace and love.” [ 6 ] This is demonstrated in 1063 when Pope Alexander II granted a papal standard and an indulgence to those killed in the Crusades. [ 7 ]

Stereotyping those who are opposed to the group as weak, evil, biased, spiteful, impotent, or stupid : Muslims and Christians use the word infidel as a slur against those of different faiths. [ 4 ]

Direct pressure to conform placed on any member who questions the group, couched in terms of "disloyalty“ : Members of the Baha’i faith must shun those who are declared as “covenant breakers” and expelled from the religion [ 8 ] ; and Jewish communities can declare Cherem on members, which is an exclusion of a person from the community, although since the Enlightenment this is a rare occurrence.

Mind guards, who are self appointed members who shield the group from dissenting information : The 1925 Butler Act was a Tennessee law prohibiting public school teachers from denying Biblical Creationism , which forbade the teaching of evolution and other theories of man’s origin. [ 9 ]

Research Findings and Laboratory Tests

“	Questions can be raised as to the utility of using groupthink for research.	”
10]

According to Clark McCauley [ 5 ] , groupthink occurs due to directive leadership, members’ homogeneous background and ideology, and isolation of the group from outside sources of information and analysis. A concept of groupthink has been extensively studied and challenged by the researchers.

In his book, Janis considered group cohesion to be the most important antecedent of groupthink [ 1 ] . Based on laboratory studies, many researchers such as Mullen, Anthony, Salas, and Driskell [ 11 ] found weak or no support for the hypothesized relationship between cohesion and groupthink symptoms. Esser [ 2 ] , McCauley [ 5 ] and Tetlock [ 12 ] also found that the group cohesion is not predictive of groupthink. Hogg [ 13 ] argue that cohesiveness is not cause of groupthink because one cannot distinguish cohesiveness from friendship or social attraction.

In a study of variables such as cohesiveness, leadership, dominance, accountability, and threat, only two variables were supported to be causes of groupthink symptoms [ 14 ] . It was found that the insulated groups has tendency to consider fewer alternatives and groups with directive leaders use less available information [ 15 ] .

Preventing Groupthink

After concluding his case studies, Janis proposed some techniques to prevent groupthink [ 1 ] . Awareness of the causes and symptoms of groupthink helps group members limit its negative effects.

The group leader should assign each member the role of "critical evaluator" and encourage objections and criticism.
Group leaders must describe the problem using unbiased statements to avoid partiality.
The organization should set up several independent groups to tackle each problem.
The group should periodically split into subgroups with different leaders to discuss ideas then reconvene to work out issues.
Each group member should discuss issues with trusted associates outside of group meetings.
Each meeting, one or more qualified outside experts should attend meetings and challenge ideas of group members.
One member each meeting should be given the role of Devil's Advocate .
The group should analyze all possible intentions of involved parties.
After reaching preliminary consensus, each member should vividly voice all residual doubts about the decision

Janis' prevention proposals were based on his experience and observations but not scientifically validated. Although his suggestions make sense, they have not been scientifically proven. Overall, there is startlingly little research done on the practical applications of groupthink. [ 16 ] In the limited practical research on groupthink, Hart proposes adding 'group accountability' to the list of preventions [ 17 ] . The end goal in preventing groupthink is in positive decision outcomes, so even beyond preventing groupthink, the following suggestions are valuable.

Create backup plans in case of failures
Hold the decision making group accountable for their decisions [ 18 ]

Group decision-making or cohesion is not always a bad thing. Collective wisdom or Group wisdom is when shared knowledge by individuals and groups are used to solve problems and conflicts. As long as the group does not fall into the trap of groupthink, cohesiveness of a group is useful especially during decision-making in the military.

The following example cases are recommended for further studies:

North Korea
Marshall Plan
Northern Rock
Vietnam War

Related words:

Abilene paradox
Bandwagon effect
Collective behavior
Communal reinforcement
Group polarization
Group serving bias
Herd behavior
Spiral of silence
↑ a b c d Janis, Irving L. Victims of Groupthink. Boston. Houghton Mifflin Company, 1972.
↑ a b Esser, James K. (1998). Alive and well after 25 years: A review of Groupthink research. Organizational Behavior and Human Decision Processes. Vol 73. pp. 116-141.
↑ a b Walsh, H. (1989). Groupthink (pp. 16). Hartland Publications.
↑ a b (2011) Dictionary.com. http://dictionary.reference.com/
↑ a b c McCauley, C. (1989). The nature of social influence in groupthink: Compliance and internalization. Journal of Personality and Social Psychology, 57, 250–260.
↑ Selengut, Charles (2008-04-28). Sacred fury: understanding religious violence. p. 1. ISBN 9780742560840 . http://books.google.com/?id=mOqtEkGlq0cC&pg=PR7&dq=%22sectarian+violence%22+%22religious+violence%22#v=onepage&q=%22sectarian%20violence%22%20%22religious%20violence%22&f=false .
↑ Handy, R., Lotz, D., Norris, R.,Walker, W. (1918). A History of the Christian Church (4th ed.), pp. 347. New York City: Scribner. Retrieved April 24, 2011, from http://books.google.com/books?id=bFw8PtQhpVoC&pg=PA347&lpg=PA347&dq=pope+alexander+ii+indulgences&source=bl&ots=JfFG5REnDu&sig=cIs8iixL8ijVxPHQB3QsPfgpnqw&hl=en&ei=qXC0Td-VN8K5tgfO5-zpDg&sa=X&oi=book_result&ct=result&resnum=2&ved=0CCEQ6AEwAQ#v=onepage&q=pope%20alexander%20ii%20indulgences&f=false
↑ Abdu'l-Bahá. (1992). The Will And Testament of ‘Abdu’l-Bahá. Mona Vale: Bahá'í Publications Australia. Retrieved April 26, 2011 from http://reference.bahai.org/en/t/ab/WT/
↑ Moore, R. (2002). Evolution in the Courtroom: A Reference Guide (pp. 117). Santa Barbara: ABC-CLIO.
↑ Henningsen, D. D., Henningsen, M. L. M., Eden, J., & Cruz, M. G. (2006). Examining the Symptoms of Groupthink and Retrospective Sensemaking. Small Group Research, 37, 36-64.
↑ Mullen, B., Anthony, T., Salas, E., & Driskell, J. E. (1994). Group cohesiveness and quality of decision making: An integration of tests of the groupthink hypothesis. Small Group Research, 25, 189–204.
↑ Tetlock, P. E., Peterson, R. S., McGuire, C., Chang, S., & Feld, P. (1992). Assessing political group dynamics: A test of the groupthink model. Journal of Personality and Social Psychology, 63, 403–425.
↑ Hogg, M., Hains, S. 1998. "Friendship and group identification: a new look at the role of cohesiveness in groupthink." European Journal of Social Psychology. Vol. 28. pp 323-341.
↑ Park, W. (2000). A comprehensive empirical investigation of the relationships among variables of the groupthink model. Journal of Organizational Behavior, 21, 873–887
↑ Flowers, M. L. (1977). A laboratory test of some implications of Janis’s groupthink hypothesis. Journal of Personality and Social Psychology, 35, 888–896.
↑ Rose (2011). Diverse Perspectives on the Groupthink Theory. Emerging Leadership Journeys, Vol. 4 Iss. 1, 2011, pp. 37- 57.
↑ Mohamed, A. A., & Wiebe, F. A. (1996). Toward a process theory of groupthink. Small Group Research, 27(3), 416-430.
↑ Hart, P. (1998). Preventing groupthink revisited: Evaluating and reforming groups in government. Organizational Behavior and Human Decision Processes, 73, 306-326.

Book:Professionalism

Group Dynamics in Janis's Theory of Groupthink: Backward and Forward

1998, Organizational behavior and human decision processes

Janis's groupthink theory is an appealing explanation of how group process can get in the way of optimal decision making. Unfortunately, Janis was selective and not always consistent in his application of research in group dynamics. This paper traces groupthink to its theoretical roots in order to suggest how a broader and more consistent use of research in group dynamics can advance understanding of decision-making problems. In particular, the paper explores and reinterprets the groupthink prediction that poor decision making is most likely when group cohesion is based on the personal attractiveness of group members. Copyright 1998 Academic Press.

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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.

Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.

A hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observations before we can develop a broader theory.

Theories and hypotheses always have this if-then relationship. “ If drive theory is correct, then cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.

But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this question is an interesting one on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.

Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [2] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the number of examples they bring to mind and the other was that people base their judgments on how easily they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.

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

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 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.

Research Methods in Psychology Copyright © 2019 by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Verywell / Alex Dos Diaz

The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

Operationalization

Hypothesis Types

Hypotheses examples.

Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

Forming a question
Performing background research
Creating a hypothesis
Designing an experiment
Collecting data
Analyzing the results
Drawing conclusions
Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you expect to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

Is your hypothesis based on your research on a topic?
Can your hypothesis be tested?
Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the journal articles you read . Many authors will suggest questions that still need to be explored.

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

Collect as many observations about a topic or problem as you can.
Evaluate these observations and look for possible causes of the problem.
Create a list of possible explanations that you might want to explore.
After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method , falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that if something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Importance of Operational Definitions

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

Hypothesis Checklist

Does your hypothesis focus on something that you can actually test?
Does your hypothesis include both an independent and dependent variable?
Can you manipulate the variables?
Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the dependent variable if you change the independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

"Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
"Students who experience test anxiety before an English exam 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."
"Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

Examples of a complex hypothesis include:

"People with high-sugar diets and sedentary activity levels are more likely to develop depression."
"Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

"There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
"There is no difference in scores on a memory recall task between children and adults."
"There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

"People who take St. John's wort supplements will have less anxiety than those who do not."
"Adults will perform better on a memory task than children."
"Children who play first-person shooter games will show higher levels of aggression than children who do not."

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as case studies , naturalistic observations , and surveys are often used when conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a correlational study can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually cause another to change.

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Thompson WH, Skau S. On the scope of scientific hypotheses . R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:]. Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ? PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies . Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

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

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

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

Theory Testing

Incorporating Theory into Your Research

Characteristics of a Good Hypothesis

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.

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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Knowledge Base

Hypothesis Testing | A Step-by-Step Guide with Easy Examples

Published on November 8, 2019 by Rebecca Bevans . Revised on June 22, 2023.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics . It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.

There are 5 main steps in hypothesis testing:

State your research hypothesis as a null hypothesis and alternate hypothesis (H o ) and (H a or H 1 ).
Collect data in a way designed to test the hypothesis.
Perform an appropriate statistical test .
Decide whether to reject or fail to reject your null hypothesis.
Present the findings in your results and discussion section.

Though the specific details might vary, the procedure you will use when testing a hypothesis will always follow some version of these steps.

Step 1: state your null and alternate hypothesis, step 2: collect data, step 3: perform a statistical test, step 4: decide whether to reject or fail to reject your null hypothesis, step 5: present your findings, other interesting articles, frequently asked questions about hypothesis testing.

After developing your initial research hypothesis (the prediction that you want to investigate), it is important to restate it as a null (H o ) and alternate (H a ) hypothesis so that you can test it mathematically.

The alternate hypothesis is usually your initial hypothesis that predicts a relationship between variables. The null hypothesis is a prediction of no relationship between the variables you are interested in.

H 0 : Men are, on average, not taller than women. H a : Men are, on average, taller than women.

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For a statistical test to be valid , it is important to perform sampling and collect data in a way that is designed to test your hypothesis. If your data are not representative, then you cannot make statistical inferences about the population you are interested in.

There are a variety of statistical tests available, but they are all based on the comparison of within-group variance (how spread out the data is within a category) versus between-group variance (how different the categories are from one another).

If the between-group variance is large enough that there is little or no overlap between groups, then your statistical test will reflect that by showing a low p -value . This means it is unlikely that the differences between these groups came about by chance.

Alternatively, if there is high within-group variance and low between-group variance, then your statistical test will reflect that with a high p -value. This means it is likely that any difference you measure between groups is due to chance.

Your choice of statistical test will be based on the type of variables and the level of measurement of your collected data .

an estimate of the difference in average height between the two groups.
a p -value showing how likely you are to see this difference if the null hypothesis of no difference is true.

Based on the outcome of your statistical test, you will have to decide whether to reject or fail to reject your null hypothesis.

In most cases you will use the p -value generated by your statistical test to guide your decision. And in most cases, your predetermined level of significance for rejecting the null hypothesis will be 0.05 – that is, when there is a less than 5% chance that you would see these results if the null hypothesis were true.

In some cases, researchers choose a more conservative level of significance, such as 0.01 (1%). This minimizes the risk of incorrectly rejecting the null hypothesis ( Type I error ).

The results of hypothesis testing will be presented in the results and discussion sections of your research paper , dissertation or thesis .

In the results section you should give a brief summary of the data and a summary of the results of your statistical test (for example, the estimated difference between group means and associated p -value). In the discussion , you can discuss whether your initial hypothesis was supported by your results or not.

In the formal language of hypothesis testing, we talk about rejecting or failing to reject the null hypothesis. You will probably be asked to do this in your statistics assignments.

However, when presenting research results in academic papers we rarely talk this way. Instead, we go back to our alternate hypothesis (in this case, the hypothesis that men are on average taller than women) and state whether the result of our test did or did not support the alternate hypothesis.

If your null hypothesis was rejected, this result is interpreted as “supported the alternate hypothesis.”

These are superficial differences; you can see that they mean the same thing.

You might notice that we don’t say that we reject or fail to reject the alternate hypothesis . This is because hypothesis testing is not designed to prove or disprove anything. It is only designed to test whether a pattern we measure could have arisen spuriously, or by chance.

If we reject the null hypothesis based on our research (i.e., we find that it is unlikely that the pattern arose by chance), then we can say our test lends support to our hypothesis . But if the pattern does not pass our decision rule, meaning that it could have arisen by chance, then we say the test is inconsistent with our hypothesis .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Normal distribution
Descriptive statistics
Measures of central tendency
Correlation coefficient

Methodology

Cluster sampling
Stratified sampling
Types of interviews
Cohort study
Thematic analysis

Research bias

Implicit bias
Cognitive bias
Survivorship bias
Availability heuristic
Nonresponse bias
Regression to the mean

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

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