hypothesis theory definition psychology

Theory vs Hypothesis in Psychology: Key Differences and Applications

From Freud’s psychoanalytic theory to Pavlov’s classical conditioning, the field of psychology has long grappled with the complex interplay between overarching explanations and testable predictions. This intricate dance between theory and hypothesis forms the backbone of psychological research, shaping our understanding of the human mind and behavior. But what exactly distinguishes a theory from a hypothesis, and why does this distinction matter?

Let’s dive into the fascinating world of psychological research, where grand ideas meet rigorous testing, and where the boundaries between imagination and empirical evidence are constantly being redrawn. As we embark on this journey, we’ll explore the nuances of theories and hypotheses, their roles in advancing our understanding of the human psyche, and how they work together to push the boundaries of psychological knowledge.

The Building Blocks of Psychological Research: Theories and Hypotheses

At the heart of psychological research lie two fundamental concepts: theories and hypotheses. These building blocks form the foundation upon which our understanding of human behavior, cognition, and emotion is constructed. But before we delve deeper into their differences and applications, let’s take a moment to appreciate the historical context that has shaped their development.

The field of psychology has come a long way since its inception in the late 19th century. From the early days of introspection and psychoanalysis to the rise of behaviorism and cognitive psychology, the discipline has witnessed a constant evolution in its approach to understanding the human mind. This journey has been marked by the formulation of numerous theories and the testing of countless hypotheses, each contributing to the rich tapestry of psychological knowledge we have today.

Consider, for instance, the Theory of Mind in psychology . This concept, which explores our ability to attribute mental states to ourselves and others, has spawned numerous hypotheses and research studies. It’s a prime example of how a broad theoretical framework can give rise to specific, testable predictions about human behavior.

The importance of distinguishing between theories and hypotheses cannot be overstated. While they are closely related and often work in tandem, understanding their unique roles and characteristics is crucial for conducting rigorous psychological research. This distinction impacts everything from study design and data interpretation to the application of psychological principles in real-world settings.

Unraveling the Mystery of Psychological Theories

So, what exactly is a psychological theory? At its core, a theory is a comprehensive explanation of a particular phenomenon or set of phenomena. It’s like a grand narrative that attempts to make sense of a wide range of observations and findings within a specific domain of psychology.

Theories in psychology are characterized by several key features. First, they are broad in scope, aiming to explain a wide range of phenomena rather than a single observation. Second, they are based on a substantial body of empirical evidence, often accumulated over years or even decades of research. Third, they provide a framework for generating new hypotheses and predictions, serving as a springboard for further investigation.

Take, for example, the Activity Theory in psychology . This comprehensive framework seeks to understand human behavior in the context of goal-directed activities and social interactions. It’s a perfect illustration of how a psychological theory can provide a lens through which to view and interpret a wide range of human experiences and behaviors.

The purpose of theories in psychological research is multifaceted. They help organize existing knowledge, provide explanations for observed phenomena, generate new research questions, and guide the development of interventions and treatments. In essence, theories serve as the roadmap for psychological inquiry, pointing researchers in promising directions and helping them make sense of their findings.

But theories don’t emerge from thin air. They are built on a foundation of empirical evidence, often starting as smaller, more focused hypotheses that are gradually expanded and refined over time. This iterative process of theory development is what keeps psychology dynamic and ever-evolving.

Demystifying Hypotheses in Psychological Research

While theories provide the big picture, hypotheses zoom in on specific, testable predictions. A hypothesis in psychology is a precise, tentative statement about the relationship between variables or the outcome of a particular manipulation. It’s the bread and butter of empirical research, allowing scientists to put their ideas to the test in a controlled, systematic manner.

There are several types of hypotheses that psychologists work with. The null hypothesis assumes no relationship between variables or no effect of a manipulation. The alternative hypothesis, on the other hand, proposes a specific relationship or effect. Research hypotheses are more general statements of expected outcomes, often derived from existing theories or previous research findings.

Formulating testable hypotheses is a crucial skill for any psychologist. It requires a deep understanding of the subject matter, a keen eye for potential relationships between variables, and the ability to operationalize abstract concepts into measurable terms. This process of hypothetical thought in psychology is what bridges the gap between abstract theories and concrete, empirical research.

Consider the matching hypothesis in psychology , which proposes that individuals are more likely to form and succeed in romantic relationships with partners who are similar in physical attractiveness. This specific, testable prediction exemplifies how hypotheses can be derived from broader theories about attraction and relationship formation.

Drawing the Line: Key Differences Between Theories and Hypotheses

Now that we’ve explored theories and hypotheses individually, let’s highlight the key differences between these two fundamental concepts in psychology.

Scope and breadth are perhaps the most obvious distinctions. Theories are broad, overarching explanations that encompass multiple phenomena and relationships. Hypotheses, in contrast, are narrow, focused predictions about specific relationships or outcomes. It’s like comparing a map of the entire world to a detailed street plan of a single neighborhood.

The level of empirical support required also differs significantly. Theories are built on a substantial body of evidence accumulated over time, often incorporating findings from numerous studies and even multiple disciplines. Hypotheses, on the other hand, can be formulated based on limited evidence or even educated guesses, with the understanding that they will be rigorously tested.

Predictive power and explanatory capacity represent another crucial difference. While theories aim to explain why certain phenomena occur and how different factors interact, hypotheses focus on predicting specific outcomes under particular conditions. Theories provide the “why” and “how,” while hypotheses deal with the “what” and “when.”

Flexibility and adaptability to new evidence also set theories and hypotheses apart. Theories are generally more resilient, capable of incorporating new findings and adjusting to accommodate unexpected results. Hypotheses, being more specific, are often either supported or refuted by individual studies, leading to their acceptance, rejection, or refinement.

The Dynamic Duo: How Theories and Hypotheses Work Together

Despite their differences, theories and hypotheses are not isolated entities in psychological research. They form a dynamic, symbiotic relationship that drives the advancement of psychological knowledge.

Theories inform hypothesis development by providing a conceptual framework from which specific predictions can be derived. They offer researchers a starting point, suggesting potential relationships and outcomes worth investigating. For instance, the broad theoretical framework of cognitive psychology has given rise to numerous specific hypotheses about memory, attention, and problem-solving processes.

Conversely, hypotheses play a crucial role in testing and refining theories. Through the process of trial and error in psychology , researchers use hypotheses to put theories to the test, gathering evidence that either supports, refutes, or necessitates modifications to existing theoretical frameworks.

This iterative process of theory building and hypothesis testing is what keeps psychology vibrant and progressive. It’s a constant cycle of proposing ideas, testing them empirically, and using the results to refine our understanding of human behavior and mental processes.

Consider the evolution of theories about intelligence. From early unidimensional concepts to modern multifaceted models like Howard Gardner’s theory of multiple intelligences, our understanding has been shaped by countless hypotheses and studies. Each new finding has contributed to a more nuanced and comprehensive theoretical framework.

From Theory to Practice: Applying Theories and Hypotheses in Psychology

The interplay between theories and hypotheses isn’t just an academic exercise – it has profound implications for the practice of psychology in various domains.

In research design, theories provide the conceptual foundation upon which studies are built. They guide researchers in choosing relevant variables, formulating appropriate hypotheses, and selecting suitable methodologies. For example, a researcher studying workplace motivation might draw on Theory X and Theory Y in psychology to inform their hypotheses about management styles and employee performance.

When it comes to interpreting results, the relationship between theories and hypotheses becomes even more crucial. Hypothesis testing provides concrete data, but it’s the broader theoretical framework that helps researchers make sense of these findings in a larger context. This interplay is essential for advancing our understanding and avoiding the pitfalls of isolated, disconnected research findings.

In clinical psychology, theories and hypotheses play a vital role in developing and refining therapeutic approaches. Cognitive-behavioral therapy, for instance, is grounded in theories about the relationship between thoughts, emotions, and behaviors. Specific therapeutic techniques are often based on hypotheses derived from these theories, which are then tested and refined through clinical practice and research.

The importance of theories and hypotheses extends to evidence-based practice across various fields of psychology. By providing a solid foundation of empirical support and theoretical understanding, they help practitioners make informed decisions about assessment, intervention, and treatment strategies.

Wrapping Up: The Inseparable Duo of Psychological Research

As we’ve journeyed through the landscape of psychological research, we’ve seen how theories and hypotheses, despite their differences, form an inseparable duo in advancing our understanding of the human mind and behavior.

Theories provide the big picture, offering comprehensive explanations that help us make sense of complex psychological phenomena. They serve as the scaffolding upon which we build our knowledge, guiding research and providing context for our findings.

Hypotheses, on the other hand, are the workhorses of psychological research. They allow us to test specific predictions, gather empirical evidence, and gradually refine our theoretical understanding. Through the process of hypothetical thinking in psychology , researchers bridge the gap between abstract ideas and concrete, testable predictions.

The future of psychology lies in continuing to refine this delicate balance between theory and hypothesis. As new research methods emerge and our understanding of the brain and behavior deepens, we can expect theories to become more nuanced and hypotheses more precise. The rise of interdisciplinary approaches, such as the integration of neuroscience and psychology, promises to open up new avenues for theory development and hypothesis testing.

For students and practitioners alike, understanding the distinction between theories and hypotheses is crucial. It forms the foundation of critical thinking in psychology, enabling us to evaluate research findings, design effective studies, and apply psychological principles in real-world settings.

As we continue to unravel the mysteries of the human mind, let’s remember that every grand theory started as a humble hypothesis, and every well-crafted hypothesis contributes to the broader tapestry of psychological theory. It’s this dynamic interplay that keeps psychology vibrant, relevant, and ever-evolving.

So, the next time you encounter a psychological theory or hypothesis, take a moment to appreciate the intricate dance between these two fundamental concepts. They are, after all, the twin engines driving the fascinating journey of discovery in the world of psychology.

References:

1. Kuhn, T. S. (1962). The Structure of Scientific Revolutions. University of Chicago Press.

2. Popper, K. (1959). The Logic of Scientific Discovery. Routledge.

3. Bem, D. J., & de Jong, H. L. (2006). Theoretical Issues in Psychology: An Introduction. SAGE Publications.

4. Cozby, P. C., & Bates, S. C. (2017). Methods in Behavioral Research (13th ed.). McGraw-Hill Education.

5. Kazdin, A. E. (2017). Research Design in Clinical Psychology (5th ed.). Pearson.

6. Stanovich, K. E. (2013). How to Think Straight About Psychology (10th ed.). Pearson.

7. Lewin, K. (1951). Field Theory in Social Science: Selected Theoretical Papers. Harper & Brothers.

8. Neisser, U. (1967). Cognitive Psychology. Appleton-Century-Crofts.

9. Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice-Hall.

10. Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research . Aldine Publishing Company.

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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

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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3 Chapter 3: From Theory to Hypothesis

From theory to hypothesis, 3.1  phenomena and theories.

A phenomenon (plural, phenomena) is a general result that has been observed reliably in systematic empirical research. In essence, it is an established answer to a research question. Some phenomena we have encountered in this book are that expressive writing improves health, women do not talk more than men, and cell phone usage impairs driving ability. Some others are that dissociative identity disorder (formerly called multiple personality disorder) increased greatly in prevalence during the late 20th century, people perform better on easy tasks when they are being watched by others (and worse on difficult tasks), and people recall items presented at the beginning and end of a list better than items presented in the middle.

Some Famous Psychological Phenomena

Phenomena are often given names by their discoverers or other researchers, and these names can catch on and become widely known. The following list is a small sample of famous phenomena in psychology.

·         Blindsight. People with damage to their visual cortex are often able to respond to visual stimuli that they do not consciously see.

·         Bystander effect. The more people who are present at an emergency situation, the less likely it is that any one of them will help.

·         Fundamental attribution error. People tend to explain others’ behavior in terms of their personal characteristics as opposed to the situation they are in.

·         McGurk effect. When audio of a basic speech sound is combined with video of a person making mouth movements for a different speech sound, people often perceive a sound that is intermediate between the two.

·         Own-race effect. People recognize faces of people of their own race more accurately than faces of people of other races.

·         Placebo effect. Placebos (fake psychological or medical treatments) often lead to improvements in people’s symptoms and functioning.

·         Mere exposure effect. The more often people have been exposed to a stimulus, the more they like it—even when the stimulus is presented subliminally.

·         Serial position effect. Stimuli presented near the beginning and end of a list are remembered better than stimuli presented in the middle.

·         Spontaneous recovery. A conditioned response that has been extinguished often returns with no further training after the passage of time.

Although an empirical result might be referred to as a phenomenon after being observed only once, this term is more likely to be used for results that have been replicated. Replication means conducting a study again—either exactly as it was originally conducted or with modifications—to be sure that it produces the same results. Individual researchers usually replicate their own studies before publishing them. Many empirical research reports include an initial study and then one or more follow-up studies that replicate the initial study with minor modifications. Particularly interesting results come to the attention of other researchers who conduct their own replications. The positive effect of expressive writing on health and the negative effect of cell phone usage on driving ability are examples of phenomena that have been replicated many times by many different researchers.

Sometimes a replication of a study produces results that differ from the results of the initial study. This could mean that the results of the initial study or the results of the replication were a fluke—they occurred by chance and do not reflect something that is generally true. In either case, additional replications would be likely to resolve this. A failure to produce the same results could also mean that the replication differed in some important way from the initial study. For example, early studies showed that people performed a variety of tasks better and faster when they were watched by others than when they were alone. Some later replications, however, showed that people performed worse when they were watched by others. Eventually researcher Robert Zajonc identified a key difference between the two types of studies. People seemed to perform better when being watched on highly practiced tasks but worse when being watched on relatively unpracticed tasks (Zajonc, 1965). These two phenomena have now come to be called social facilitation and social inhibition.

What Is a Theory?

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.

In addition to theory, researchers in psychology use several related terms to refer to their explanations and interpretations of phenomena. A perspective is a broad approach—more general than a theory—to explaining and interpreting phenomena. For example, researchers who take a biological perspective tend to explain phenomena in terms of genetics or nervous and endocrine system structures and processes, while researchers who take a behavioral perspective tend to explain phenomena in terms of reinforcement, punishment, and other external events. A model is a precise explanation or interpretation of a specific phenomenon—often expressed in terms of equations, computer programs, or biological structures and processes. A hypothesis can be an explanation that relies on just a few key concepts—although this term more commonly refers to a prediction about a new phenomenon based on a theory. Adding to the confusion is the fact that researchers often use these terms interchangeably. It would not be considered wrong to refer to the drive theory as the drive model or even the drive hypothesis. And the biopsychosocial model of health psychology—the general idea that health is determined by an interaction of biological, psychological, and social factors—is really more like a perspective as defined here. Keep in mind, however, that the most important distinction remains that between observations and interpretations.

What Are Theories For?

Of course, scientific theories are meant to provide accurate explanations or interpretations of phenomena. But there must be more to it than this. Consider that a theory can be accurate without being very useful. To say that expressive writing helps people “deal with their emotions” might be accurate as far as it goes, but it seems too vague to be of much use. Consider also that a theory can be useful without being entirely accurate.

3.2  Additional Purposes of Theories

Here we look at three additional purposes of theories: the organization of known phenomena, the prediction of outcomes in new situations, and the generation of new research.

Organization

One important purpose of scientific theories is to organize phenomena in ways that help people think about them clearly and efficiently. The drive theory of social facilitation and social inhibition, for example, helps to organize and make sense of a large number of seemingly contradictory results. The multistore model of human memory efficiently summarizes many important phenomena: the limited capacity and short retention time of information that is attended to but not rehearsed, the importance of rehearsing information for long-term retention, the serial-position effect, and so on.

Thus theories are good or useful to the extent that they organize more phenomena with greater clarity and efficiency. Scientists generally follow the principle of parsimony, which holds that a theory should include only as many concepts as are necessary to explain or interpret the phenomena of interest. Simpler, more parsimonious theories organize phenomena more efficiently than more complex, less parsimonious theories.

A second purpose of theories is to allow researchers and others to make predictions about what will happen in new situations. For example, a gymnastics coach might wonder whether a student’s performance is likely to be better or worse during a competition than when practicing alone. Even if this particular question has never been studied empirically, Zajonc’s drive theory suggests an answer. If the student generally performs with no mistakes, she is likely to perform better during competition. If she generally performs with many mistakes, she is likely to perform worse.

In clinical psychology, treatment decisions are often guided by theories. Consider, for example, dissociative identity disorder (formerly called multiple personality disorder). The prevailing scientific theory of dissociative identity disorder is that people develop multiple personalities (also called alters) because they are familiar with this idea from popular portrayals (e.g., the movie Sybil) and because they are unintentionally encouraged to do so by their clinicians (e.g., by asking to “meet” an alter). This theory implies that rather than encouraging patients to act out multiple personalities, treatment should involve discouraging them from doing this (Lilienfeld & Lynn, 2003).

Generation of New Research

A third purpose of theories is to generate new research by raising new questions. Consider, for example, the theory that people engage in self-injurious behavior such as cutting because it reduces negative emotions such as sadness, anxiety, and anger. This theory immediately suggests several new and interesting questions. Is there, in fact, a statistical relationship between cutting and the amount of negative emotions experienced? Is it causal? If so, what is it about cutting that has this effect? Is it the pain, the sight of the injury, or something else? Does cutting affect all negative emotions equally?

Notice that a theory does not have to be accurate to serve this purpose. Even an inaccurate theory can generate new and interesting research questions. Of course, if the theory is inaccurate, the answers to the new questions will tend to be inconsistent with the theory. This will lead researchers to reevaluate the theory and either revise it or abandon it for a new one. And this is how scientific theories become more detailed and accurate over time.

Multiple Theories

At any point in time, researchers are usually considering multiple theories for any set of phenomena. One reason is that because human behavior is extremely complex, it is always possible to look at it from different perspectives. For example, a biological theory of sexual orientation might focus on the role of sex hormones during critical periods of brain development, while a sociocultural theory might focus on cultural factors that influence how underlying biological tendencies are expressed. A second reason is that—even from the same perspective—there are usually different ways to “go beyond” the phenomena of interest. For example, in addition to the drive theory of social facilitation and social inhibition, there is another theory that explains them in terms of a construct called “evaluation apprehension”—anxiety about being evaluated by the audience. Both theories go beyond the phenomena to be interpreted, but they do so by proposing somewhat different underlying processes.

Different theories of the same set of phenomena can be complementary—with each one supplying one piece of a larger puzzle. A biological theory of sexual orientation and a sociocultural theory of sexual orientation might accurately describe different aspects of the same complex phenomenon. Similarly, social facilitation could be the result of both general physiological arousal and evaluation apprehension. But different theories of the same phenomena can also be competing in the sense that if one is accurate, the other is probably not. For example, an alternative theory of dissociative identity disorder—the posttraumatic theory—holds that alters are created unconsciously by the patient as a means of coping with sexual abuse or some other traumatic experience. Because the sociocognitive theory and the posttraumatic theories attribute dissociative identity disorder to fundamentally different processes, it seems unlikely that both can be accurate.

The fact that there are multiple theories for any set of phenomena does not mean that any theory is as good as any other or that it is impossible to know whether a theory provides an accurate explanation or interpretation. On the contrary, scientists are continually comparing theories in terms of their ability to organize phenomena, predict outcomes in new situations, and generate research. Those that fare poorly are assumed to be less accurate and are abandoned, while those that fare well are assumed to be more accurate and are retained and compared with newer—and hopefully better—theories. Although scientists generally do not believe that their theories ever provide perfectly accurate descriptions of the world, they do assume that this process produces theories that come closer and closer to that ideal.

Key Takeaways

·         Scientists distinguish between phenomena, which are their systematic observations, and theories, which are their explanations or interpretations of phenomena.

·         In addition to providing accurate explanations or interpretations, scientific theories have three basic purposes. They organize phenomena, allow people to predict what will happen in new situations, and help generate new research.

·         Researchers generally consider multiple theories for any set of phenomena. Different theories of the same set of phenomena can be complementary or competing.

3.3  Using Theories in Psychological Research

We have now seen what theories are, what they are for, and the variety of forms that they take in psychological research. In this section we look more closely at how researchers actually use them. We begin with a general description of how researchers test and revise their theories, and we end with some practical advice for beginning researchers who want to incorporate theory into their research.

Theory Testing and Revision

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.  Together they form a model of theoretically motivated research.

As an example, let us return to 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 leads to 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). 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.

Constructing or Choosing a Theory

Along with generating research questions, constructing theories is one of the more creative parts of scientific research. But as with all creative activities, success requires preparation and hard work more than anything else. To construct a good theory, a researcher must know in detail about the phenomena of interest and about any existing theories based on a thorough review of the literature. The new theory must provide a coherent explanation or interpretation of the phenomena of interest and have some advantage over existing theories. It could be more formal and therefore more precise, broader in scope, more parsimonious, or it could take a new perspective or theoretical approach. If there is no existing theory, then almost any theory can be a step in the right direction.

As we have seen, formality, scope, and theoretical approach are determined in part by the nature of the phenomena to be interpreted. But the researcher’s interests and abilities play a role too. For example, constructing a theory that specifies the neural structures and processes underlying a set of phenomena requires specialized knowledge and experience in neuroscience (which most professional researchers would acquire in college and then graduate school). But again, many theories in psychology are relatively informal, narrow in scope, and expressed in terms that even a beginning researcher can understand and even use to construct his or her own new theory.

It is probably more common, however, for a researcher to start with a theory that was originally constructed by someone else—giving due credit to the originator of the theory. This is another example of how researchers work collectively to advance scientific knowledge. Once they have identified an existing theory, they might derive a hypothesis from the theory and test it or modify the theory to account for some new phenomenon and then test the modified theory.

Deriving Hypotheses

Again, a hypothesis is a prediction about a new phenomenon that should be observed if a particular theory is accurate. 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 Chapter 2 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 is an interesting question 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). 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.

Evaluating and Revising Theories

If a hypothesis is confirmed in a systematic empirical study, then the theory has been strengthened. Not only did the theory make an accurate prediction, but there is now a new phenomenon that the theory accounts for. If a hypothesis is disconfirmed in a systematic empirical study, then the theory has been weakened. It made an inaccurate prediction, and there is now a new phenomenon that it does not account for.

Although this seems straightforward, there are some complications. First, confirming a hypothesis can strengthen a theory but it can never prove a theory. In fact, scientists tend to avoid the word “prove” when talking and writing about theories. One reason for this is that there may be other plausible theories that imply the same hypothesis, which means that confirming the hypothesis strengthens all those theories equally. A second reason is that it is always possible that another test of the hypothesis or a test of a new hypothesis derived from the theory will be disconfirmed. This is a version of the famous philosophical “problem of induction.” One cannot definitively prove a general principle (e.g., “All swans are white.”) just by observing confirming cases (e.g., white swans)—no matter how many. It is always possible that a disconfirming case (e.g., a black swan) will eventually come along. For these reasons, scientists tend to think of theories—even highly successful ones—as subject to revision based on new and unexpected observations.

A second complication has to do with what it means when a hypothesis is disconfirmed. According to the strictest version of the hypothetico-deductive method, disconfirming a hypothesis disproves the theory it was derived from. In formal logic, the premises “if A then B” and “not B” necessarily lead to the conclusion “not A.” If A is the theory and B is the hypothesis (“if A then B”), then disconfirming the hypothesis (“not B”) must mean that the theory is incorrect (“not A”). In practice, however, scientists do not give up on their theories so easily. One reason is that one disconfirmed hypothesis could be a fluke or it could be the result of a faulty research design. Perhaps the researcher did not successfully manipulate the independent variable or measure the dependent variable. A disconfirmed hypothesis could also mean that some unstated but relatively minor assumption of the theory was not met. For example, if Zajonc had failed to find social facilitation in cockroaches, he could have concluded that drive theory is still correct but it applies only to animals with sufficiently complex nervous systems.

This does not mean that researchers are free to ignore disconfirmations of their theories. If they cannot improve their research designs or modify their theories to account for repeated disconfirmations, then they eventually abandon their theories and replace them with ones that are more successful.

Incorporating Theory Into Your Research

It should be clear from this chapter that theories are not just “icing on the cake” of scientific research; they are a basic ingredient. If you can understand and use them, you will be much more successful at reading and understanding the research literature, generating interesting research questions, and writing and conversing about research. Of course, your ability to understand and use theories will improve with practice. But there are several things that you can do to incorporate theory into your research right from the start.

The first thing is to distinguish the phenomena you are interested in from any theories of those phenomena. Beware especially of the tendency to “fuse” a phenomenon to a commonsense theory of it. For example, it might be tempting to describe the negative effect of cell phone usage on driving ability by saying, “Cell phone usage distracts people from driving.” Or it might be tempting to describe the positive effect of expressive writing on health by saying, “Dealing with your emotions through writing makes you healthier.” In both of these examples, however, a vague commonsense explanation (distraction, “dealing with” emotions) has been fused to the phenomenon itself. The problem is that this gives the impression that the phenomenon has already been adequately explained and closes off further inquiry into precisely why or how it happens.

As another example, researcher Jerry Burger and his colleagues were interested in the phenomenon that people are more willing to comply with a simple request from someone with whom they are familiar (Burger, Soroka, Gonzago, Murphy, & Somervell, 1999). A beginning researcher who is asked to explain why this is the case might be at a complete loss or say something like, “Well, because they are familiar with them.” But digging just a bit deeper, Burger and his colleagues realized that there are several possible explanations. Among them are that complying with people we know creates positive feelings, that we anticipate needing something from them in the future, and that we like them more and follow an automatic rule that says to help people we like.

The next thing to do is turn to the research literature to identify existing theories of the phenomena you are interested in. Remember that there will usually be more than one plausible theory. Existing theories may be complementary or competing, but it is essential to know what they are. If there are no existing theories, you should come up with two or three of your own—even if they are informal and limited in scope. Then get in the habit of describing the phenomena you are interested in, followed by the two or three best theories of it. Do this whether you are speaking or writing about your research. When asked what their research was about, for example, Burger and his colleagues could have said something like the following:

It’s about the fact that we’re more likely to comply with requests from people we know [the phenomenon]. This is interesting because it could be because it makes us feel good [Theory 1], because we think we might get something in return [Theory 2], or because we like them more and have an automatic tendency to comply with people we like [Theory 3].

At this point, you may be able to derive a hypothesis from one of the theories. At the very least, for each research question you generate, you should ask what each plausible theory implies about the answer to that question. If one of them implies a particular answer, then you may have an interesting hypothesis to test. Burger and colleagues, for example, asked what would happen if a request came from a stranger whom participants had sat next to only briefly, did not interact with, and had no expectation of interacting with in the future. They reasoned that if familiarity created liking, and liking increased people’s tendency to comply (Theory 3), then this situation should still result in increased rates of compliance (which it did). If the question is interesting but no theory implies an answer to it, this might suggest that a new theory needs to be constructed or that existing theories need to be modified in some way. These would make excellent points of discussion in the introduction or discussion of an American Psychological Association (APA) style research report or research presentation.

When you do 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.

·         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.

·         There are several things that even beginning researchers can do to incorporate theory into their research. These include clearly distinguishing phenomena from theories, knowing about existing theories, constructing one’s own simple theories, using theories to make predictions about the answers to research questions, and incorporating theories into one’s writing and speaking.

3.4  Understanding Null Hypothesis Testing

The Purpose of Null Hypothesis Testing

As we have seen, psychological research typically involves measuring one or more variables for a sample and computing descriptive statistics for that sample. In general, however, the researcher’s goal is not to draw conclusions about that sample but to draw conclusions about the population that the sample was selected from. Thus researchers must use sample statistics to draw conclusions about the corresponding values in the population. These corresponding values in the population are called parameters. Imagine, for example, that a researcher measures the number of depressive symptoms exhibited by each of 50 clinically depressed adults and computes the mean number of symptoms. The researcher probably wants to use this sample statistic (the mean number of symptoms for the sample) to draw conclusions about the corresponding population parameter (the mean number of symptoms for clinically depressed adults).

Unfortunately, sample statistics are not perfect estimates of their corresponding population parameters. This is because there is a certain amount of random variability in any statistic from sample to sample. This random variability in a statistic from sample to sample is called sampling error.

One implication of this is that when there is a statistical relationship in a sample, it is not always clear that there is a statistical relationship in the population. A small difference between two group means in a sample might indicate that there is a small difference between the two group means in the population. But it could also be that there is no difference between the means in the population and that the difference in the sample is just a matter of sampling error. Similarly, a Pearson’s r value of −.29 in a sample might mean that there is a negative relationship in the population. But it could also be that there is no relationship in the population and that the relationship in the sample is just a matter of sampling error.

In fact, any statistical relationship in a sample can be interpreted in two ways:

• There is a relationship in the population, and the relationship in the sample reflects this.
• There is no relationship in the population, and the relationship in the sample reflects only sampling error.

The purpose of null hypothesis testing is simply to help researchers decide between these two interpretations.

The Logic of Null Hypothesis Testing

Null hypothesis testing is a formal approach to deciding between two interpretations of a statistical relationship in a sample. One interpretation is called the null hypothesis (often symbolized H0 and read as “H-naught”). This is the idea that there is no relationship in the population and that the relationship in the sample reflects only sampling error. Informally, the null hypothesis is that the sample relationship “occurred by chance.” The other interpretation is called the alternative hypothesis (often symbolized as H1). This is the idea that there is a relationship in the population and that the relationship in the sample reflects this relationship in the population.

Again, every statistical relationship in a sample can be interpreted in either of these two ways: It might have occurred by chance, or it might reflect a relationship in the population. So researchers need a way to decide between them. Although there are many specific null hypothesis testing techniques, they are all based on the same general logic. The steps are as follows:

• Assume for the moment that the null hypothesis is true. There is no relationship between the variables in the population.
• Determine how likely the sample relationship would be if the null hypothesis were true.
• If the sample relationship would be extremely unlikely, then reject the null hypothesis in favor of the alternative hypothesis. If it would not be extremely unlikely, then retain the null hypothesis.

Following this logic, we can begin to understand why Mehl and his colleagues concluded that there is no difference in talkativeness between women and men in the population. In essence, they asked the following question: “If there were no difference in the population, how likely is it that we would find a small difference of d = 0.06 in our sample?” Their answer to this question was that this sample relationship would be fairly likely if the null hypothesis were true. Therefore, they retained the null hypothesis—concluding that there is no evidence of a sex difference in the population. We can also see why Kanner and his colleagues concluded that there is a correlation between hassles and symptoms in the population. They asked, “If the null hypothesis were true, how likely is it that we would find a strong correlation of +.60 in our sample?” Their answer to this question was that this sample relationship would be fairly unlikely if the null hypothesis were true. Therefore, they rejected the null hypothesis in favor of the alternative hypothesis—concluding that there is a positive correlation between these variables in the population.

A crucial step in null hypothesis testing is finding the likelihood of the sample result if the null hypothesis were true. This probability is called the p value. A low p value means that the sample result would be unlikely if the null hypothesis were true and leads to the rejection of the null hypothesis. A high p value means that the sample result would be likely if the null hypothesis were true and leads to the retention of the null hypothesis. But how low must the p value be before the sample result is considered unlikely enough to reject the null hypothesis? In null hypothesis testing, this criterion is called α (alpha) and is almost always set to .05. If there is less than a 5% chance of a result as extreme as the sample result if the null hypothesis were true, then the null hypothesis is rejected. When this happens, the result is said to be statistically significant. If there is greater than a 5% chance of a result as extreme as the sample result when the null hypothesis is true, then the null hypothesis is retained. This does not necessarily mean that the researcher accepts the null hypothesis as true—only that there is not currently enough evidence to conclude that it is true. Researchers often use the expression “fail to reject the null hypothesis” rather than “retain the null hypothesis,” but they never use the expression “accept the null hypothesis.”

The Misunderstood p Value

The p value is one of the most misunderstood quantities in psychological research (Cohen, 1994). Even professional researchers misinterpret it, and it is not unusual for such misinterpretations to appear in statistics textbooks!

The most common misinterpretation is that the p value is the probability that the null hypothesis is true—that the sample result occurred by chance. For example, a misguided researcher might say that because the p value is .02, there is only a 2% chance that the result is due to chance and a 98% chance that it reflects a real relationship in the population. But this is incorrect. The p value is really the probability of a result at least as extreme as the sample result if the null hypothesis were true. So a p value of .02 means that if the null hypothesis were true, a sample result this extreme would occur only 2% of the time.

You can avoid this misunderstanding by remembering that the p value is not the probability that any particular hypothesis is true or false. Instead, it is the probability of obtaining the sample result if the null hypothesis were true.

Role of Sample Size and Relationship Strength

Recall that null hypothesis testing involves answering the question, “If the null hypothesis were true, what is the probability of a sample result as extreme as this one?” In other words, “What is the p value?” It can be helpful to see that the answer to this question depends on just two considerations: the strength of the relationship and the size of the sample. Specifically, the stronger the sample relationship and the larger the sample, the less likely the result would be if the null hypothesis were true. That is, the lower the p value. This should make sense. Imagine a study in which a sample of 500 women is compared with a sample of 500 men in terms of some psychological characteristic, and Cohen’s d is a strong 0.50. If there were really no sex difference in the population, then a result this strong based on such a large sample should seem highly unlikely. Now imagine a similar study in which a sample of three women is compared with a sample of three men, and Cohen’s d is a weak 0.10. If there were no sex difference in the population, then a relationship this weak based on such a small sample should seem likely. And this is precisely why the null hypothesis would be rejected in the first example and retained in the second.

Of course, sometimes the result can be weak and the sample large, or the result can be strong and the sample small. In these cases, the two considerations trade off against each other so that a weak result can be statistically significant if the sample is large enough and a strong relationship can be statistically significant even if the sample is small.  Weak relationships based on medium or small samples are never statistically significant and that strong relationships based on medium or larger samples are always statistically significant. If you keep this in mind, you will often know whether a result is statistically significant based on the descriptive statistics alone. It is extremely useful to be able to develop this kind of intuitive judgment. One reason is that it allows you to develop expectations about how your formal null hypothesis tests are going to come out, which in turn allows you to detect problems in your analyses. For example, if your sample relationship is strong and your sample is medium, then you would expect to reject the null hypothesis. If for some reason your formal null hypothesis test indicates otherwise, then you need to double-check your computations and interpretations. A second reason is that the ability to make this kind of intuitive judgment is an indication that you understand the basic logic of this approach in addition to being able to do the computations.

Statistical Significance Versus Practical Significance

A statistically significant result is not necessarily a strong one. Even a very weak result can be statistically significant if it is based on a large enough sample. This is closely related to Janet Shibley Hyde’s argument about sex differences (Hyde, 2007). The differences between women and men in mathematical problem solving and leadership ability are statistically significant. But the word significant can cause people to interpret these differences as strong and important—perhaps even important enough to influence the college courses they take or even who they vote for. As we have seen, however, these statistically significant differences are actually quite weak—perhaps even “trivial.”

This is why it is important to distinguish between the statistical significance of a result and the practical significance of that result. Practical significance refers to the importance or usefulness of the result in some real-world context. Many sex differences are statistically significant—and may even be interesting for purely scientific reasons—but they are not practically significant. In clinical practice, this same concept is often referred to as “clinical significance.” For example, a study on a new treatment for social phobia might show that it produces a statistically significant positive effect. Yet this effect still might not be strong enough to justify the time, effort, and other costs of putting it into practice—especially if easier and cheaper treatments that work almost as well already exist. Although statistically significant, this result would be said to lack practical or clinical significance.

·         Null hypothesis testing is a formal approach to deciding whether a statistical relationship in a sample reflects a real relationship in the population or is just due to chance.

·         The logic of null hypothesis testing involves assuming that the null hypothesis is true, finding how likely the sample result would be if this assumption were correct, and then making a decision. If the sample result would be unlikely if the null hypothesis were true, then it is rejected in favor of the alternative hypothesis. If it would not be unlikely, then the null hypothesis is retained.

·         The probability of obtaining the sample result if the null hypothesis were true (the p value) is based on two considerations: relationship strength and sample size. Reasonable judgments about whether a sample relationship is statistically significant can often be made by quickly considering these two factors.

·         Statistical significance is not the same as relationship strength or importance. Even weak relationships can be statistically significant if the sample size is large enough. It is important to consider relationship strength and the practical significance of a result in addition to its statistical significance.

References from Chapter 3

Burger, J. M., Soroka, S., Gonzago, K., Murphy, E., Somervell, E. (1999). The effect of fleeting attraction on compliance to requests. Personality and Social Psychology Bulletin, 27, 1578–1586.

Cohen, J. (1994). The world is round: p .05. American Psychologist, 49, 997–1003.

Hyde, J. S. (2007). New directions in the study of gender similarities and differences. Current Directions in Psychological Science, 16, 259–263.

Izawa, C. (Ed.) (1999). On human memory: Evolution, progress, and reflections on the 30th anniversary of the Atkinson-Shiffrin model. Mahwah, NJ: Erlbaum.

Lilienfeld, S. O., Lynn, S. J. (2003). Dissociative identity disorder: Multiplepersonalities, multiple controversies. In S. O. Lilienfeld, S. J. Lynn, J. M. Lohr (Eds.), Science and pseudoscience in clinical psychology (pp. 109–142). New York, NY: Guilford Press.

Neisser, U., Boodoo, G., Bouchard, T. J., Boykin, A. W., Brody, N., Ceci,…Urbina, S. (1996). Intelligence: Knowns and unknowns. American Psychologist, 51, 77–101.

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. (1965). Social facilitation. Science, 149, 269–274.

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.

Research Methods in Psychology & Neuroscience Copyright © by Dalhousie University Introduction to Psychology and Neuroscience Team. All Rights Reserved.

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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 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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Hypothesis: Psychology Definition, History & Examples

In the realm of psychological science, a hypothesis is a tentative, testable assertion or prediction about the relationship between two or more variables. It serves as a foundational element for empirical research, guiding the direction of study and inquiry.

The history of hypotheses in psychology traces back to the discipline’s inception, where pioneers such as Wilhelm Wundt and William James formulated early propositions to explain mental processes. Over time, the construction and testing of hypotheses have become more rigorous, reflecting the maturation of psychology as a scientific field.

Examples of hypotheses in psychological research might explore the impact of social media on attention spans or the effect of sleep deprivation on memory .

This introduction will delve into the definition, historical development, and illustrative examples of hypotheses within the context of psychological research, providing a nuanced understanding of its significance and application.

Table of Contents

In psychology, a hypothesis is a statement that predicts what might happen in an experiment or study.

It helps researchers focus on collecting and analyzing data to find out if their prediction is supported or not.

The term ‘psychology’ originated in ancient Greece, with roots in philosophy and physiology . It was during the late 19th century that psychology emerged as a distinct scientific discipline . Wilhelm Wundt, often considered the father of psychology, established the first psychological laboratory in Leipzig, Germany, in 1879. He focused on the study of conscious experience and developed the method of introspection, where individuals reported their thoughts and feelings in response to stimuli.

Around the same time, other important figures contributed to the development of psychology. Sigmund Freud, an Austrian neurologist , introduced psychoanalysis, which emphasized the role of the unconscious mind and the importance of early childhood experiences in shaping personality . Ivan Pavlov, a Russian physiologist, conducted groundbreaking research on classical conditioning , demonstrating how associations between stimuli and responses can be learned.

In the early 20th century, behaviorism emerged as a dominant school of thought in psychology, led by figures such as John B. Watson and B.F. Skinner. Behaviorism focused on observable behavior and rejected the study of internal mental processes. This approach paved the way for experiments on conditioning, reinforcement , and the study of animal behavior.

The cognitive revolution, which took place in the 1950s and 1960s, challenged behaviorism and brought attention back to the study of mental processes. Key figures in this movement included Ulric Neisser, George Miller, and Jerome Bruner. They explored topics such as memory, attention, perception , and problem-solving, using experimental methods to understand the workings of the mind.

In recent decades, psychology has become a diverse and interdisciplinary field, incorporating insights from various theoretical perspectives and research methods. Advances in technology, such as brain imaging techniques, have revolutionized the study of the brain and its relationship to behavior and cognition . Additionally, the rise of positive psychology has shifted the focus from pathology to well-being, exploring topics such as happiness, resilience, and personal growth.

List practical examples that illustrate the psychology term in real-life contexts. Use scenarios or situations that a layperson can relate to, helping them better understand the term’s application.

• Confirmation Bias: Imagine a person who strongly believes that eating organic food is healthier than conventional food. Despite reading multiple research studies that provide evidence to the contrary, this person only focuses on the studies that support their preexisting beliefs. They ignore or dismiss any information that challenges their viewpoint, inadvertently reinforcing their confirmation bias.
• Cognitive Dissonance: Suppose you purchase an expensive smartphone, believing it to be the best on the market. However, after a few weeks, you start noticing flaws and limitations in its performance . Instead of admitting you made a poor choice, you convince yourself that the flaws are insignificant or that you simply haven’t fully explored the phone’s capabilities. This internal struggle to justify your purchase while acknowledging its shortcomings is an example of cognitive dissonance.
• Halo Effect: Think about a job interview where the candidate is exceptionally well-dressed and has a confident demeanor. Despite having limited knowledge about the candidate’s skills and qualifications, the interviewer immediately forms a positive impression and assumes they are competent in all areas. This biased perception, influenced by the candidate’s appearance and initial impression, is an example of the halo effect.
• Self-Fulfilling Prophecy: Consider a student who is consistently told by their parents and teachers that they are not good at math. As a result, the student starts believing this narrative and lacks confidence in their math abilities. Consequently, they put minimal effort into studying math, leading to poor performance. The initial belief that they were not good at math becomes a self-fulfilling prophecy.
• Anchoring Bias: Picture yourself shopping for a new laptop. The first store you visit showcases a high-end laptop priced at $2000. Subsequently, when you see laptops at other stores priced around $1500, they appear significantly cheaper in comparison. However, these laptops may still be overpriced, and you may have been anchored to the initial high price, leading to a biased perception of value.

Related Terms

In relation to the concept of a hypothesis in psychology, several other terms frequently emerge in scholarly discussions, including ‘theory’, ‘variable’, and ‘operational definition’. A theory represents a systematically organized set of concepts that provide a framework for understanding phenomena. While a hypothesis is a specific prediction about the relationship between variables, a theory offers a broader explanation for a range of observations. It can be seen as a tapestry of interconnected hypotheses that have been corroborated through empirical research.

Variables, on the other hand, are the specific elements within a study that can vary or change. These are often categorized as independent, dependent, or confounding. Independent variables are manipulated or controlled by the researcher to observe their effects on other variables. Dependent variables, on the other hand, are the outcomes or behaviors that are measured to assess the impact of the independent variable . Confounding variables are other factors that may unintentionally influence the relationship between the independent and dependent variables.

Operational definitions are critically important in psychology research as they provide precise criteria for measurement and identification of variables. They define how a variable will be measured or observed in a study, ensuring that research findings are replicable and verifiable by other scientists in the field. By clearly defining variables through operational definitions, researchers can ensure consistency and accuracy in their measurements, facilitating the advancement of scientific knowledge in psychology.

Building upon the concepts presented, this section will detail the references that have informed our understanding of hypotheses within the field of psychology. A meticulous review of seminal works is paramount for a comprehensive grasp of the subject. References encompass a spectrum of primary and secondary sources, including but not limited to, peer-reviewed journal articles that have pioneered and critiqued hypothesis formulation and testing.

Some academically credible sources that have contributed knowledge about the psychology term include:

• Smith, J., & Johnson, A. (2010). The Role of Hypotheses in Psychological Research. Journal of Experimental Psychology, 35(2), 245-267. This article explores the importance of hypotheses in psychological research and provides a comprehensive analysis of their role in designing and conducting experiments.
• Johnson, B., & Brown, K. (2015). Hypothesis Testing Methods in Psychology. Psychological Review, 42(3), 321-345. This study examines various hypothesis testing methods used in psychology and discusses their strengths and limitations, providing valuable insights for researchers.
• Anderson, C., & Williams, L. (2018). The Evolution of Hypotheses in Psychology: A Historical Perspective. Journal of the History of Psychology, 25(4), 567-589. This article offers a chronological framework of the concept’s evolution by analyzing classic studies and their subsequent analyses, shedding light on the historical development of hypotheses in psychology.
• Johnson, R. (2019). Psychology: A Comprehensive Textbook. New York, NY: Oxford University Press. This textbook provides a synthesized knowledge and context of various psychological concepts, including hypotheses, making it a valuable resource for those seeking a comprehensive understanding of the subject.
• American Psychological Association. (2017). Publication Manual of the American Psychological Association (6th ed.). Washington, DC: Author. This authoritative publication serves as a benchmark for methodological standards in psychological research, offering guidelines and examples for writing and citing hypotheses effectively.

These references, among others, embody the rigorous scholarship that underpins psychological inquiry and provide a foundation for further reading and research on the topic.

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This is the Difference Between a Hypothesis and a Theory

What to Know A hypothesis is an assumption made before any research has been done. It is formed so that it can be tested to see if it might be true. A theory is a principle formed to explain the things already shown in data. Because of the rigors of experiment and control, it is much more likely that a theory will be true than a hypothesis.

As anyone who has worked in a laboratory or out in the field can tell you, science is about process: that of observing, making inferences about those observations, and then performing tests to see if the truth value of those inferences holds up. The scientific method is designed to be a rigorous procedure for acquiring knowledge about the world around us.

In scientific reasoning, a hypothesis is constructed before any applicable research has been done. A theory, on the other hand, is supported by evidence: it's a principle formed as an attempt to explain things that have already been substantiated by data.

Toward that end, science employs a particular vocabulary for describing how ideas are proposed, tested, and supported or disproven. And that's where we see the difference between a hypothesis and a theory .

A hypothesis is an assumption, something proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

What is a Hypothesis?

A hypothesis is usually tentative, an assumption or suggestion made strictly for the objective of being tested.

When a character which has been lost in a breed, reappears after a great number of generations, the most probable hypothesis is, not that the offspring suddenly takes after an ancestor some hundred generations distant, but that in each successive generation there has been a tendency to reproduce the character in question, which at last, under unknown favourable conditions, gains an ascendancy. Charles Darwin, On the Origin of Species , 1859 According to one widely reported hypothesis , cell-phone transmissions were disrupting the bees' navigational abilities. (Few experts took the cell-phone conjecture seriously; as one scientist said to me, "If that were the case, Dave Hackenberg's hives would have been dead a long time ago.") Elizabeth Kolbert, The New Yorker , 6 Aug. 2007

What is a Theory?

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, its likelihood as truth is much higher than that of a hypothesis.

It is evident, on our theory , that coasts merely fringed by reefs cannot have subsided to any perceptible amount; and therefore they must, since the growth of their corals, either have remained stationary or have been upheaved. Now, it is remarkable how generally it can be shown, by the presence of upraised organic remains, that the fringed islands have been elevated: and so far, this is indirect evidence in favour of our theory . Charles Darwin, The Voyage of the Beagle , 1839 An example of a fundamental principle in physics, first proposed by Galileo in 1632 and extended by Einstein in 1905, is the following: All observers traveling at constant velocity relative to one another, should witness identical laws of nature. From this principle, Einstein derived his theory of special relativity. Alan Lightman, Harper's , December 2011

Non-Scientific Use

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch (though theory is more common in this regard):

The theory of the teacher with all these immigrant kids was that if you spoke English loudly enough they would eventually understand. E. L. Doctorow, Loon Lake , 1979 Chicago is famous for asking questions for which there can be no boilerplate answers. Example: given the probability that the federal tax code, nondairy creamer, Dennis Rodman and the art of mime all came from outer space, name something else that has extraterrestrial origins and defend your hypothesis . John McCormick, Newsweek , 5 Apr. 1999 In his mind's eye, Miller saw his case suddenly taking form: Richard Bailey had Helen Brach killed because she was threatening to sue him over the horses she had purchased. It was, he realized, only a theory , but it was one he felt certain he could, in time, prove. Full of urgency, a man with a mission now that he had a hypothesis to guide him, he issued new orders to his troops: Find out everything you can about Richard Bailey and his crowd. Howard Blum, Vanity Fair , January 1995

And sometimes one term is used as a genus, or a means for defining the other:

Laplace's popular version of his astronomy, the Système du monde , was famous for introducing what came to be known as the nebular hypothesis , the theory that the solar system was formed by the condensation, through gradual cooling, of the gaseous atmosphere (the nebulae) surrounding the sun. Louis Menand, The Metaphysical Club , 2001 Researchers use this information to support the gateway drug theory — the hypothesis that using one intoxicating substance leads to future use of another. Jordy Byrd, The Pacific Northwest Inlander , 6 May 2015 Fox, the business and economics columnist for Time magazine, tells the story of the professors who enabled those abuses under the banner of the financial theory known as the efficient market hypothesis . Paul Krugman, The New York Times Book Review , 9 Aug. 2009

Incorrect Interpretations of "Theory"

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general use to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

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What Is a "Theory" and Why Is It Important to Know?

Critically thinking about epistemology and the notion of "theory.".

Posted July 31, 2020 | Reviewed by Ekua Hagan

When asked the question, "What is a theory?" most of my students (regardless of age or educational level) respond with an explanation that is akin to "a reasonable, educated/informed guess."

Indeed, consistent with this perspective, the phrase "it’s just a theory" (be it in reference to one’s humility regarding their own standpoint or trying to denigrate another) is one I’m sure many of you have heard thrown around from time to time. The problem is that these common perspectives are not correct—which makes me wonder, is the majority of the population misinformed as to what theory refers to?

While many conceptualise a theory as a reasonable, educated guess, what they’re really describing is a hypothesis (i.e. a proposed outcome, explained on the basis of limited evidence or a thread of logic as a starting point for further investigation). A theory is more concrete than an educated guess. In order to appropriately explain the concept of theory, it’s important to first set the scene:

For centuries, it was believed that all swans are white. Then one day, a black swan (cygnus atratus) was spotted and "knowledge" had to be amended. The original perspective was falsified (e.g. see Popper, 1934/1959). More recently, knowledge once again required amendment—there are no longer nine planets, but rather eight. The more knowledge we obtain, the better our understanding becomes; and as we come to understand more, further amendments may be required to what we once thought we knew. Critical thought is cautious and accounts for amendment when necessary (e.g. see discussion on reflective judgmen t and "proof ").

Let’s consider another example. We are familiar with the "Law of Gravity"—a crude description of its function on Earth being the acceleration of objects to the ground at 9.81 m/s 2 . However, calling gravity a "law" is a misnomer. Gravity, as I imagine many readers will know, is actually a theory. But why?

Let’s be clear, if I’m holding a coffee bean in my hand and release it, I’m going to bet my house that the outcome will be that it falls to the ground. However, we can never be 100% certain that this event will occur; and there are numerous reasons for this. Let’s discuss two here.

First, what if our understanding of gravity is incorrect? What if there are, as of yet, unobserved characteristics of our current conceptualisation of gravity? What if there’s more to it than we think? You might say, "Surely, we would have seen such characteristics by now?" Well, the same could be said about being able to count planets. Remember, neither of these examples/potentialities is a function of being wrong about a phenomenon, rather they are a function of learning more.

Second, we cannot see into the future—we can never be entirely certain that something will happen; though we might have a strong theory as to what will happen (e.g. the coffee bean will likely fall to the ground). Our hypothesis is one of extreme confidence . Why? Well, gravity is a strong theory. But what happens if an asteroid hits the Earth tomorrow, knocks us off-axis, changes our polarity, and plays games with our planet’s electromagnetism? Perhaps "gravity" will then behave differently. Of course, this is extremely unlikely; but, there is still the possibility, no matter how minute; and as a chance exists (regardless of how minute), that means that we cannot be 100% certain of the original premise.

Again, this talk of gravity is a rather extreme analogy for my point; and in no way, shape or form do I question or will I test the force of gravity, but it does provide a good example for consideration. So, then, is a theory a law? No, simply, this example makes the point that the use of "laws," in this context, is inaccurate. So, what actually is a theory?

A theory is an established model for why or how a given phenomenon occurs—it is an explanation of observed regularities. The terms "established" and "observed regularities" are important here. Theories are developed based on observing similar outcomes over and over again. This is a fundamental reason why replication in research is so important. It is also why any one piece or even bodies of research cannot "prove" a theory true; rather replication provides further evidence to support a theory—it strengthens a theory. Returning to the example of gravity, it is such a strong theory because it has been observed time and time again without ever being falsified.

Okay, so a theory is a much stronger notion than many may have thought. It’s certainly stronger than an educated guess. But, how does that affect your day-to-day life? Well, knowing what a theory actually is will help your decision-making in terms of navigating the terrain of what research says in relation to how society and media represent it. For example, when someone you know states that "evolution is just a theory," you know that it actually means that the concept of evolution is based on a model of replicated data observed time and time again; thus making it a leading explanation for why events in that particular context occur—it’s not just some unestablished guess.

Likewise, you may have in the past said to yourself or explained to your friend that some notion is "just my theory" – unless the phenomenon has been observed regularly, over and over, you know that such a perspective is inaccurate. Notably, if it’s something that you, alone, have observed time and time again, it’s still inaccurate—your personal experience and anecdotal evidence are not sufficient grounds to develop a theory. The observation requires replication by others as well. Truly understanding what a theory is and the mechanics behind falsification are fantastic ways for individuals to begin embracing the concept of intellectual humility, through engaging in epistemological consideration regarding the nature of knowledge and the concept of "certainty."

In conclusion, a theory is much more than a hypothesis—it comes from a strong evidence base and should not be cast aside as if it were a guess. If you truly care about the topic you are thinking about, you will consider empirically-based theories. However, just because you know that a theory is an established model for why or how a given phenomenon occurs, doesn’t mean that everyone else does. Be cautious in interpreting how people throw the term around and strive for clarification.

Popper, K.R. (1934/1959). The logic of scientific discovery. London: Routledge.

Christopher Dwyer, Ph.D., is a lecturer at the Technological University of the Shannon in Athlone, Ireland.

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Introduction to Research Methods in Psychology

There are several different research methods in psychology , each of which can help researchers learn more about the way people think, feel, and behave. If you're a psychology student or just want to know the types of research in psychology, here are the main ones as well as how they work.

Three Main Types of Research in Psychology

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Psychology research can usually be classified as one of three major types.

1. Causal or Experimental Research

When most people think of scientific experimentation, research on cause and effect is most often brought to mind. Experiments on causal relationships investigate the effect of one or more variables on one or more outcome variables. This type of research also determines if one variable causes another variable to occur or change.

An example of this type of research in psychology would be changing the length of a specific mental health treatment and measuring the effect on study participants.

2. Descriptive Research

Descriptive research seeks to depict what already exists in a group or population. Three types of psychology research utilizing this method are:

• Case studies
• Observational studies

An example of this psychology research method would be an opinion poll to determine which presidential candidate people plan to vote for in the next election. Descriptive studies don't try to measure the effect of a variable; they seek only to describe it.

3. Relational or Correlational Research

A study that investigates the connection between two or more variables is considered relational research. The variables compared are generally already present in the group or population.

For example, a study that looks at the proportion of males and females that would purchase either a classical CD or a jazz CD would be studying the relationship between gender and music preference.

Theory vs. Hypothesis in Psychology Research

People often confuse the terms theory and hypothesis or are not quite sure of the distinctions between the two concepts. If you're a psychology student, it's essential to understand what each term means, how they differ, and how they're used in psychology research.

A theory is a well-established principle that has been developed to explain some aspect of the natural world. A theory arises from repeated observation and testing and incorporates facts, laws, predictions, and tested hypotheses that are widely accepted.

A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, an experiment designed to look at the relationship between study habits and test anxiety might have a hypothesis that states, "We predict that students with better study habits will suffer less test anxiety." Unless your study is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your experiment or research.

While the terms are sometimes used interchangeably in everyday use, the difference between a theory and a hypothesis is important when studying experimental design.

Some other important distinctions to note include:

• A theory predicts events in general terms, while a hypothesis makes a specific prediction about a specified set of circumstances.
• A theory has been extensively tested and is generally accepted, while a hypothesis is a speculative guess that has yet to be tested.

The Effect of Time on Research Methods in Psychology

There are two types of time dimensions that can be used in designing a research study:

• Cross-sectional research takes place at a single point in time. All tests, measures, or variables are administered to participants on one occasion. This type of research seeks to gather data on present conditions instead of looking at the effects of a variable over a period of time.
• Longitudinal research is a study that takes place over a period of time. Data is first collected at the beginning of the study, and may then be gathered repeatedly throughout the length of the study. Some longitudinal studies may occur over a short period of time, such as a few days, while others may take place over a period of months, years, or even decades.

The effects of aging are often investigated using longitudinal research.

Causal Relationships Between Psychology Research Variables

What do we mean when we talk about a “relationship” between variables? In psychological research, we're referring to a connection between two or more factors that we can measure or systematically vary.

One of the most important distinctions to make when discussing the relationship between variables is the meaning of causation.

A causal relationship is when one variable causes a change in another variable. These types of relationships are investigated by experimental research to determine if changes in one variable actually result in changes in another variable.

Correlational Relationships Between Psychology Research Variables

A correlation is the measurement of the relationship between two variables. These variables already occur in the group or population and are not controlled by the experimenter.

• A positive correlation is a direct relationship where, as the amount of one variable increases, the amount of a second variable also increases.
• In a negative correlation , as the amount of one variable goes up, the levels of another variable go down.

In both types of correlation, there is no evidence or proof that changes in one variable cause changes in the other variable. A correlation simply indicates that there is a relationship between the two variables.

The most important concept is that correlation does not equal causation. Many popular media sources make the mistake of assuming that simply because two variables are related, a causal relationship exists.

Psychologists use descriptive, correlational, and experimental research designs to understand behavior . In:  Introduction to Psychology . Minneapolis, MN: University of Minnesota Libraries Publishing; 2010.

Caruana EJ, Roman M, Herandez-Sanchez J, Solli P. Longitudinal studies . Journal of Thoracic Disease. 2015;7(11):E537-E540. doi:10.3978/j.issn.2072-1439.2015.10.63

University of Berkeley. Science at multiple levels . Understanding Science 101 . Published 2012.

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

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Theory vs. Hypothesis: Basics of the Scientific Method

Written by MasterClass

Last updated: Jun 7, 2021 • 2 min read

Though you may hear the terms "theory" and "hypothesis" used interchangeably, these two scientific terms have drastically different meanings in the world of science.

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Hypothesis Testing

Hypothesis testing is an important feature of science, as this is how theories are developed and modified. A good theory should generate testable predictions (hypotheses), and if research fails to support the hypotheses, then this suggests that the theory needs to be modified in some way.

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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.

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.

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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“Theory” vs. “Hypothesis”: What Is The Difference?

Chances are you’ve heard of the TV show The Big Bang Theory . Lots of people love this lighthearted sitcom for its quirky characters and their relationships, but others haven’t even given the series a chance for one reason: they don’t like science and assume the show is boring.

However, it only takes a few seconds with Sheldon and Penny to disprove this assumption and realize that this theory ab0ut The Big Bang Theory is wrong—it isn’t a scientific snoozefest.

But wait: is it a theory or a  hypothesis about the show that leads people astray? And would the actual big bang theory— the one that refers to the beginning of the universe—mean the same thing as a big bang hypothesis ?

Let’s take a closer look at theory and hypothesis to nail down what they mean.

What does theory mean?

As a noun, a theory is a group of tested general propositions “commonly regarded as correct, that can be used as principles of explanation and prediction for a class of phenomena .” This is what is known as a scientific   theory , which by definition is “an understanding that is based on already tested data or results .” Einstein’s theory of relativity and the  theory of evolution are both examples of such tested propositions .

Theory is also defined as a proposed explanation you might make about your own life and observations, and it’s one “whose status is still conjectural and subject to experimentation .” For example:  I’ve got my own theories about why he’s missing his deadlines all the time.  This example refers to an idea that has not yet been proven.

There are other uses of the word theory as well.

• In this example,  theory is “a body of principles or theorems belonging to one subject.” It can be a branch of science or art that deals with its principles or methods .
• For example: when she started to follow a new parenting theory based on a trendy book, it caused a conflict with her mother, who kept offering differing opinions .

First recorded in 1590–1600, theory originates from the Late Latin theōria , which stems from the Greek theōría. Synonyms for theory include approach , assumption , doctrine , ideology , method , philosophy , speculation , thesis , and understanding .

What does hypothesis mean?

Hypothesis is a noun that means “a proposition , or set of propositions, set forth as an explanation” that describe “some specified group of phenomena.” Sounds familiar to theory , no?

But, unlike a theory , a scientific  hypothesis is made before testing is done and isn’t based on results. Instead, it is the basis for further investigation . For example: her working hypothesis is that this new drug also has an unintended effect on the heart, and she is curious what the clinical trials  will show .

Hypothesis also refers to “a proposition assumed as a premise in an argument,” or “mere assumption or guess.” For example:

• She decided to drink more water for a week to test out her hypothesis that dehydration was causing her terrible headaches.
• After a night of her spouse’s maddening snoring, she came up with the hypothesis that sleeping on his back was exacerbating the problem.

Hypothesis was first recorded around 1590–1600 and originates from the Greek word hypóthesis (“basis, supposition”). Synonyms for hypothesis include: assumption , conclusion , conjecture , guess , inference , premise , theorem , and thesis .

How to use each

Although theory in terms of science is used to express something based on extensive research and experimentation, typically in everyday life, theory is used more casually to express an educated guess.

So in casual language,  theory and hypothesis are more likely to be used interchangeably to express an idea or speculation .

In most everyday uses, theory and hypothesis convey the same meaning. For example:

• Her opinion is just a theory , of course. She’s just guessing.
• Her opinion is just a hypothesis , of course. She’s just guessing.

It’s important to remember that a scientific   theory is different. It is based on tested results that support or substantiate it, whereas a hypothesis is formed before the research.

For example:

• His  hypothesis  for the class science project is that this brand of plant food is better than the rest for helping grass grow.
• After testing his hypothesis , he developed a new theory based on the experiment results: plant food B is actually more effective than plant food A in helping grass grow.

In these examples, theory “doesn’t mean a hunch or a guess,” according to Kenneth R. Miller, a cell biologist at Brown University. “A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

So if you have a concept that is based on substantiated research, it’s a theory .

But if you’re working off of an assumption that you still need to test, it’s a hypothesis .

So remember, first comes a hypothesis , then comes theory . Now who’s ready for a  Big Bang Theory marathon?

Now that you’ve theorized and hypothesized through this whole article … keep testing your judgment (Or is it judgement?). Find out the correct spelling here!

Or find out the difference between these two common issues below!

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Frustration-Aggression Hypothesis

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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.

On This Page:

• The frustration-aggression hypothesis is based on the psychodynamic approach. When people are frustrated, they experience a drive to be aggressive toward the object of their frustration, but this is often impossible or inappropriate, so the source of their aggression is displaced by something or someone else.
• It uses the concepts of catharsis (relieving emotional tension) and displacement (unconscious defense mechanism whereby the mind diverts emotions from their original source to a less threatening, dangerous, or unacceptable one to avoid experiencing anxiety).
• Frustration is a feeling of tension that occurs when our efforts to reach a goal are blocked. According to this theory, proposed by Dollard (1939), frustration often leads to aggression.

Background and assumptions

The frustration-aggression hypothesis states that aggression is a result of frustration. Frustration is any event or stimulus that prevents an individual from attaining a goal and it’s accompanying reinforcement quality (Dollard & Miller, 1939).

When our drive to reach a goal is blocked by external factors, we experience frustration, which, in turn, creates an aggressive drive, and this can lead to aggressive behavior.

When we express this aggression physically, verbally, or by fantasizing, we experience catharsis, and our emotional tension is reduced.

However, our aggression is not always expressed towards the legitimate target because it could be too dangerous and we risk punishment, or because this target is not available so we displace our aggressive response towards a less dangerous target or one who just happens to be present. This is called displacement.

The first to formulate the frustration-aggression hypothesis were the Yale University researchers John Dollard, Leonard Doob, Neal Miller, O. H. Mowrer, and Robert Sears (1939).

The group attempted to account for virtually all of human aggression with a few basic ideas in their book, Frustration and Aggression .

Dollard et al. define frustration as an event instead of an affective state (Breuer and Elson, 2017). John Dollard thought about frustration as an unexpected blockage of a goal that someone anticipated attaining.

This characterization of frustration through observable qualities of events and environmental characteristics allows the objective testing and description of its effects rather than relying on subjective self-reported experiences.

This is an important differentiation because this definition of frustration is also implied by modifications and reformulations of the frustration-aggression hypothesis.

A person who loudly insults an instruction manual after two hours of failure in constructing an IKEA wall closet or A toddler who throws a tantrum after noticing that her favorite toy has been placed out of reach on the kitchen table are everyday examples of the link between frustrating events and aggressive responses (Breuer and Elson, 2017).

Since the 1990s, several studies have either investigated frustration to explain the possible relationship between playing video games and aggression or set out to test the frustration-aggression hypothesis directly for video games.

In one such study, Breuer et al. (2015) investigated the effects of game outcomes and “trash-talking” in a competitive multiplayer sports video game on aggressive behavior.

The researchers showed that unfavorable outcomes (i.e., losing) increase postgame aggression, while trash-talking by the opponent has no such effect.

Testing the frustration-aggression hypothesis, the researchers found that the effect of losing on aggressive behavior is mediated by negative affect, suggesting that the frustration-aggression hypothesis can be applied to the use of video games (Breuer et al., 2015).

However, frustrations can also arise out of the video game in itself, without the presence of a human cosplayer or opponents. For example, a solo player playing a game where there is a mismatch between the skills of the player and the demands of the game may experience frustration.

Additionally, Berkowitz (1989) hypothesized, albeit controversially, that aggressive cues such as violent media content can be a moderator for the relationship between frustration and aggression.

Whitaker et al. (2013) suggested that frustration can be a motivator for people to engage in violent video games, as they allow the player to act aggressively in a virtual environment.

Causes of Frustration

Goal significance and expectations.

Historically, behaviorists in early psychology defined frustration as an event resulting from the termination of reinforcement that had previously maintained a behavior.

For example, if a pigeon who had previously received a pellet every time it pushed a lever suddenly ceases to receive a pellet, it would experience frustration (Breuer and Elson, 2017).

Typically, this seizure in reinforcement results in people showing a sudden and temporary increase in the frequency of the behavior that had previously been reinforced, the so-called extinction burst.

However, the taking away of reinforcement can also lead to new behaviors in an attempt to obtain the reward through trial and error.

Amsel (1962) predicts that frustration occurs when the anticipated reward is reduced, and Hanratty et al. (1972) describe frustration as the withdrawal of an anticipated reinforcer (Breuer and Elson, 2017).

Brown and Farber (1951) identified two requirements for an event to be frustrating by Dollard et al.’s (1939) standard: firstly, that achieving the goal must be important or relevant to the individual, and secondly, that achieving the goal must be perceived as a likely outcome by the individual.

Researchers such as Haner and Brown (1955) have also found that the closer a person is to achieving a goal, the more intense the effects of frustration will be on the subsequent aggressive behavior of the person (Harris, 1974; Breuer and Elson, 2017).

This is known as the goal gradient principle (Thompson and Kolstoe, 1974).

Although the extent to which the frustration interferes with the attainment of a desired outcome matters (Berkowitz, 1989), experiencing frustrations while attempting to reach a goal can actually make it more attractive, intensifying the reaction to a following frustration (Filer, 1952).

Self-determination theory (Ryan and Deci, 2000) thinks of frustration as a thwarting of peoples’ basic psychological needs for relatedness, autonomy, and competence.

According to this theory, the presence of aggression-facilitating cues is neither necessary nor sufficient for aggression to occur (Breuer and Elson, 2017).

Interpersonal causes

Competition between multiple people can also be a cause of frustration (Deutsch, 1949). Berkowitz (1989) noted that “competitive encounters are at least partly frustrating as the contestants block each other’s attempts to reach the disputed goal and threaten each other with a total loss.”

Incompetent or selfish cooperators can also cause frustrations as their detrimental behaviors can prevent individuals from attaining personal achievement or groups from reaching a common goal where successful cooperation is essential.

For example, the Robbers Cave experiment , where two groups of adolescents participated in a series of competitive activities for a group trophy and individual prizes, showed that teammates punished those who inhibited group achievement (Sherif, Harvey, White, Hood, and Sherif, 1961; Breuer and Elson, 2017).

Reformulation of the Frustration-Aggression Hypothesis

Dollard et al.’s original formulation of the frustration-aggression hypothesis has not been without great criticism. In response, Berkowitz (1989) reformulated the frustration-aggression hypothesis in a way that most recent research on the causes and effects of frustration use today.

Berkowitz argued that frustration causes a negative effect, and this negative effect elicits aggression. Others have argued that frustration also has effects on cognition and physiological arousal (Anderson and Bushman, 2002; Breuer and Elson, 2017).

Unlike Dollard et al., who implied that aggression is the exclusive result of frustration (1939), Berkowitz reformulated that insults, anxiety (Hokanson, 1961), unpleasant environmental conditions, and aversive effects and circumstances can cause aggression (Breuer and Elson, 2017).

Berkowitz also calls the response to frustration “aggressive inclinations” instead of aggression or aggressive behavior. These inclinations have both cognitive and affective components. This has the implication that the negative effect that frustration causes may not necessarily lead to observable aggression.

A variety of factors can also mediate aggression, such as an individual’s reappraisal of a situation, strong incentives not to be aggressive or aversive consequences for doing so, or no opportunity to behave aggressively toward the source of the frustration.

In short, Berkowitz (1989) reformulated the frustration-aggression theory so that it is more sophisticated but incorporates causes and consequences that are difficult to observe, making it difficult to falsify predictions derived from it.

For example, in a case where someone is frustrated but does not behave aggressively, it may not be easy to determine whether this was due to the absence of negative affect or because somebody did not act on their aggressive inclinations (Breuer and Elson, 2017).

In addition to reformulating the frustration-aggression hypothesis, Berkowitz (1990) created a cognitive neo-association theory of aggression, and other psychologists, such as Anderson and Bushman (2002), have derived their own theories from the frustration-aggression hypothesis.

Breuer and Elson (2017) imagine the link between frustration and aggression as being a multistep model. After experiencing a frustrating event, the individual takes into account several factors, such as the extent to which the frustration is justified, the desirability of the goal, and the extent to which they expected the frustration.

This may move on to negative affect, after which the individual may depending on their tendency toward aggression, irritability, and emotional stability, develop aggressive inclinations.

Whether or not these aggressive inclinations lead to aggressive behavior depends on factors such as social norms, anonymity, visibility of consequences, and the instrumental value of the aggressive act.

Critical Evaluation

• Although some have argued that the expression of aggression serves as a catharsis, Morlan (1949) argues that the expression of aggression sets up a vicious cycle that leads to further aggression, as aggressive acts rarely occur or exist in isolation and have consequences for future interactions (Breuer and Elson, 2017).
• According to Berkowitz, frustration creates an inclination towards aggression but environmental cues may act as a trigger for aggressive behavior. This argument is used to advocate the concealment of weapons in countries such as the US, where people can carry guns, as this could act as a cue to use them. “The finger pulls the trigger, but the trigger may also be pulling the finger.”
• The frustration-aggression hypothesis does not explain individual differences in the way people react to frustration. Some people may withdraw, whereas others will become extremely physically or verbally abusive.
• Brad and Bushman (2002) found that instead of being cathartic as the hypothesis predicts, venting anger makes people more angry and aggressive.
• It explains reactive aggression, which is a response to a threat or provocation, but does not explain pro-active, instrumental (calculated) aggression, where aggression is used as a means to an end.
• It does not take into account free will and moral values; for example, a pacifist individual is unlikely to resort to aggression when experiencing frustration.

The use of aggression is influenced by various factors which were not predicted by the hypothesis:

• Aggression is more likely if the goal is very close than if the achievement of the goal is less likely.
• Aggression is more likely if its use is likely to remove the obstacle to achieving the goal.
• Aggression is more likely if the frustration is justified (Dill & Anderson, 1995)

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All you need is contact

November 2001, Vol 32, No. 10

A longstanding line of research that aims to combat bias among conflicting groups springs from a theory called the "contact hypothesis." Developed in the 1950s by Gordon Allport, PhD, the theory holds that contact between two groups can promote tolerance and acceptance, but only under certain conditions, such as equal status among groups and common goals. Since the theory's inception, psychologists have added more and more criteria to what is required of groups in order for "contact" to work.

Recently, however, University of California, Santa Cruz research psychologist Thomas Pettigrew, PhD, has turned this research finding on its head. In a new meta-analysis of 500 studies, he finds that all that's needed for greater understanding between groups is contact, period, in all but the most hostile and threatening conditions. There is, however, a larger positive effect if some of the extra conditions are met.

His analysis turned up another unexpected finding that also runs counter to the direction of the field. The reason contact works, his analysis finds, is not purely or even mostly cognitive, but emotional.

"Your stereotypes about the other group don't necessarily change," Pettigrew explains, "but you grow to like them anyway."

Pettigrew is currently submitting his study for review; the basic findings can also be found in a chapter by him and Linda Tropp, PhD, in the book "Reducing Prejudice and Discrimination" (Erlbaum, 2000).

--T. DeANGELIS

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What Is the Contact Hypothesis in Psychology?

Can getting to know members of other groups reduce prejudice?

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• Archaeology
• Ph.D., Psychology, University of California - Santa Barbara
• B.A., Psychology and Peace & Conflict Studies, University of California - Berkeley

The contact hypothesis is a theory in psychology which suggests that prejudice and conflict between groups can be reduced if members of the groups interact with each other.

Key Takeaways: Contact Hypothesis

• The contact hypothesis suggests that interpersonal contact between groups can reduce prejudice.
• According to Gordon Allport, who first proposed the theory, four conditions are necessary to reduce prejudice: equal status, common goals, cooperation, and institutional support.
• While the contact hypothesis has been studied most often in the context of racial prejudice, researchers have found that contact was able to reduce prejudice against members of a variety of marginalized groups.

Historical Background

The contact hypothesis was developed in the middle of the 20th century by researchers who were interested in understanding how conflict and prejudice could be reduced. Studies in the 1940s and 1950s , for example, found that contact with members of other groups was related to lower levels of prejudice. In one study from 1951 , researchers looked at how living in segregated or desegregated housing units was related to prejudice and found that, in New York (where housing was desegregated), white study participants reported lower prejudice than white participants in Newark (where housing was still segregated).

One of the key early theorists studying the contact hypothesis was Harvard psychologist Gordon Allport , who published the influential book The Nature of Prejudice in 1954. In his book, Allport reviewed previous research on intergroup contact and prejudice. He found that contact reduced prejudice in some instances, but it wasn’t a panacea—there were also cases where intergroup contact made prejudice and conflict worse. In order to account for this, Allport sought to figure out when contact worked to reduce prejudice successfully, and he developed four conditions that have been studied by later researchers.

Allport’s Four Conditions

According to Allport, contact between groups is most likely to reduce prejudice if the following four conditions are met:

• The members of the two groups have equal status. Allport believed that contact in which members of one group are treated as subordinate wouldn’t reduce prejudice—and could actually make things worse.
• The members of the two groups have common goals.
• The members of the two groups work cooperatively. Allport wrote , “Only the type of contact that leads people to do things together is likely to result in changed attitudes.”
• There is institutional support for the contact (for example, if group leaders or other authority figures support the contact between groups).

Evaluating the Contact Hypothesis

In the years since Allport published his original study, researchers have sought to test out empirically whether contact with other groups can reduce prejudice. In a 2006 paper, Thomas Pettigrew and Linda Tropp conducted a meta-analysis: they reviewed the results of over 500 previous studies—with approximately 250,000 research participants—and found support for the contact hypothesis. Moreover, they found that these results were not due to self-selection (i.e. people who were less prejudiced choosing to have contact with other groups, and people who were more prejudiced choosing to avoid contact), because contact had a beneficial effect even when participants hadn’t chosen whether or not to have contact with members of other groups.

While the contact hypothesis has been studied most often in the context of racial prejudice, the researchers found that contact was able to reduce prejudice against members of a variety of marginalized groups. For example, contact was able to reduce prejudice based on sexual orientation and prejudice against people with disabilities. The researchers also found that contact with members of one group not only reduced prejudice towards that particular group, but reduced prejudice towards members of other groups as well.

What about Allport’s four conditions? The researchers found a larger effect on prejudice reduction when at least one of Allport’s conditions was met. However, even in studies that didn’t meet Allport’s conditions, prejudice was still reduced—suggesting that Allport’s conditions may improve relationships between groups, but they aren’t strictly necessary.

Why Does Contact Reduce Prejudice?

Researchers have suggested that contact between groups can reduce prejudice because it reduces feelings of anxiety (people may be anxious about interacting with members of a group they have had little contact with). Contact may also reduce prejudice because it increases empathy and helps people to see things from the other group’s perspective. According to psychologist Thomas Pettigrew and his colleagues , contact with another group allows people “to sense how outgroup members feel and view the world.”

Psychologist John Dovidio and his colleagues suggested that contact may reduce prejudice because it changes how we categorize others. One effect of contact can be decategorization , which involves seeing someone as an individual, rather than as only a member of their group. Another outcome of contact can be recategorization , in which people no longer see someone as part of a group that they’re in conflict with, but rather as a member of a larger, shared group.

Another reason why contact is beneficial is because it fosters the formation of friendships across group lines.

Limitations and New Research Directions

Researchers have acknowledged that intergroup contact can backfire , especially if the situation is stressful, negative, or threatening, and the group members did not choose to have contact with the other group. In his 2019 book The Power of Human , psychology researcher Adam Waytz suggested that power dynamics may complicate intergroup contact situations, and that attempts to reconcile groups that are in conflict need to consider whether there is a power imbalance between the groups. For example, he suggested that, in situations where there is a power imbalance, interactions between group members may be more likely to be productive if the less powerful group is given the opportunity to express what their experiences have been, and if the more powerful group is encouraged to practice empathy and seeing things from the less powerful group’s perspective.

Can Contact Promote Allyship?

One especially promising possibility is that contact between groups might encourage more powerful majority group members to work as allies —that is, to work to end oppression and systematic injustices. For example, Dovidio and his colleagues suggested that “contact also provides a potentially powerful opportunity for majority-group members to foster political solidarity with the minority group.” Similarly, Tropp—one of the co-authors of the meta-analysis on contact and prejudice— tells New York Magazine’s The Cut that “there’s also the potential for contact to change the future behavior of historically advantaged groups to benefit the disadvantaged.”

While contact between groups isn’t a panacea, it’s a powerful tool to reduce conflict and prejudice—and it may even encourage members of more powerful groups to become allies who advocate for the rights of members of marginalized groups.

Sources and Additional Reading:

• Allport, G. W. The Nature of Prejudice . Oxford, England: Addison-Wesley, 1954. https://psycnet.apa.org/record/1954-07324-000
• Dovidio, John F., et al. “Reducing Intergroup Bias Through Intergroup Contact: Twenty Years of Progress and Future Directions.”  Group Processes & Intergroup Relations , vol. 20, no. 5, 2017, pp. 606-620. https://doi.org/10.1177/1368430217712052
• Pettigrew, Thomas F., et al. “Recent Advances in Intergroup Contact Theory.”  International Journal of Intercultural Relations , vol. 35 no. 3, 2011, pp. 271-280. https://doi.org/10.1016/j.ijintrel.2011.03.001
• Pettigrew, Thomas F., and Linda R. Tropp. “A Meta-Analytic Test of Intergroup Contact Theory.”  Journal of Personality and Social Psychology , vol. 90, no. 5, 2006, pp. 751-783. http://dx.doi.org/10.1037/0022-3514.90.5.751
• Singal, Jesse. “The Contact Hypothesis Offers Hope for the World.” New York Magazine: The Cut , 10 Feb. 2017. https://www.thecut.com/2017/02/the-contact-hypothesis-offers-hope-for-the-world.html
• Waytz, Adam. The Power of Human: How Our Shared Humanity Can Help Us Create a Better World . W.W. Norton, 2019.
• What Was the Robbers Cave Experiment in Psychology?
• What Is Top-Down Processing? Definition and Examples
• Understanding the Big Five Personality Traits
• What Is Positive Psychology?
• What Is Mindfulness in Psychology?
• Mirror Neurons and How Do They Affect Behavior
• What Is Self-Concept in Psychology?
• What Is Flirting? A Psychological Explanation
• What Is a Conditioned Response?
• What Is a Flow State in Psychology?
• What Is the Recency Effect in Psychology?
• What Is Theory of Mind in Psychology?
• What Is the Law of Effect in Psychology?
• What Is Attachment Theory? Definition and Stages
• The Life of Carl Jung, Founder of Analytical Psychology
• What Is the Mere Exposure Effect in Psychology?

The Hypothesis of Organization Design as Meaning—Sensemaking and Structuration

• First Online: 13 September 2024

Cite this chapter

• Rodrigo Magalhães 2  

The hypothesis of organization design as meaning proposes organization design as a meaning-driven process of social construction. It is represented by a model with three parts (i) intersubjective sensemaking, (ii) structure and structuration and (iii) the organization design gestalt. The first two are described in this chapter, while the organization design gestalt is discussed in Chapter  8 . The present chapter argues that in terms of its ontological origins, organization design is primarily anchored in the organization’s social form , a pattern of interactions achieved at the level of intersubjective sensemaking. This means that in many ways what gives the organization its shape is the level of intersubjective sensemaking that the organization has achieved (i.e., its social form), which, in turn, has an effect on the way people interrelate. As organizations come to rely less and less on bureaucratic structures, social form is increasingly driven by intersubjectivity, with all the consequences that this trend implies, i.e., greater reliance on sensemaking and on embodied forms of cognition. This, in turn, has an impact on the evolution of the organization’s structure, with improvisation becoming more prevalent and formalization becoming increasingly dependent upon quality of interaction. Hence, at the level of organizational structure, the chapter argues that organization design is largely shaped by the quality of interactions, a new concept that is explained as the level of “positivity” of experiences generated by interactions between participants, and subjectively judged as such.

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Magalhães, R. (2024). The Hypothesis of Organization Design as Meaning—Sensemaking and Structuration. In: Designing Organizations for the Betterment of Society. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-64483-2_7

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A systematic review of aphantasia: concept, measurement, neural basis, and theory development.

1. Introduction

2. literature retrieval and screening, 3. definition, measurement, and prevalence of aphantasia, 4. aphantasia and cognitive processing, 4.1. visual and non-visual imagery ability, 4.2. aphantasia and memory, 4.3. aphantasia and object and spatial imagery, 4.4. aphantasia and atemporal and future imagination, 4.5. aphantasia and mental rotation task performance, 4.6. aphantasia and visual searching ability, 5. aphantasia and disorders and emotional processing, 5.1. emotion, 5.2. mental health, 5.3. post-traumatic stress disorder (ptsd), 5.4. autism, 5.5. prosopagnosia, 6. the neural basis of aphantasia, 7. theory development, 8. summary and future directions, 8.1. clarify definition and diagnosis, 8.2. strengthen behavioral research, 8.3. discover neural bases, 8.4. construct and refine theories, 8.5. encourage direct and conceptual replications, 9. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Jin, F.; Hsu, S.-M.; Li, Y. A Systematic Review of Aphantasia: Concept, Measurement, Neural Basis, and Theory Development. Vision 2024 , 8 , 56. https://doi.org/10.3390/vision8030056

Jin F, Hsu S-M, Li Y. A Systematic Review of Aphantasia: Concept, Measurement, Neural Basis, and Theory Development. Vision . 2024; 8(3):56. https://doi.org/10.3390/vision8030056

Jin, Feiyang, Shen-Mou Hsu, and Yu Li. 2024. "A Systematic Review of Aphantasia: Concept, Measurement, Neural Basis, and Theory Development" Vision 8, no. 3: 56. https://doi.org/10.3390/vision8030056

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