experiment in psychology definition

Experimental Psychology: 10 Examples & Definition

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

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Experimental psychology refers to studying psychological phenomena using scientific methods. Originally, the primary scientific method involved manipulating one variable and observing systematic changes in another variable.

Today, psychologists utilize several types of scientific methodologies.

Experimental psychology examines a wide range of psychological phenomena, including: memory, sensation and perception, cognitive processes, motivation, emotion, developmental processes, in addition to the neurophysiological concomitants of each of these subjects.

Studies are conducted on both animal and human participants, and must comply with stringent requirements and controls regarding the ethical treatment of both.

Definition of Experimental Psychology

Experimental psychology is a branch of psychology that utilizes scientific methods to investigate the mind and behavior.

It involves the systematic and controlled study of human and animal behavior through observation and experimentation .

Experimental psychologists design and conduct experiments to understand cognitive processes, perception, learning, memory, emotion, and many other aspects of psychology. They often manipulate variables ( independent variables ) to see how this affects behavior or mental processes (dependent variables).

The findings from experimental psychology research are often used to better understand human behavior and can be applied in a range of contexts, such as education, health, business, and more.

Experimental Psychology Examples

1. The Puzzle Box Studies (Thorndike, 1898) Placing different cats in a box that can only be escaped by pulling a cord, and then taking detailed notes on how long it took for them to escape allowed Edward Thorndike to derive the Law of Effect: actions followed by positive consequences are more likely to occur again, and actions followed by negative consequences are less likely to occur again (Thorndike, 1898).

2. Reinforcement Schedules (Skinner, 1956) By placing rats in a Skinner Box and changing when and how often the rats are rewarded for pressing a lever, it is possible to identify how each schedule results in different behavior patterns (Skinner, 1956). This led to a wide range of theoretical ideas around how rewards and consequences can shape the behaviors of both animals and humans.

3. Observational Learning (Bandura, 1980) Some children watch a video of an adult punching and kicking a Bobo doll. Other children watch a video in which the adult plays nicely with the doll. By carefully observing the children’s behavior later when in a room with a Bobo doll, researchers can determine if television violence affects children’s behavior (Bandura, 1980).

4. The Fallibility of Memory (Loftus & Palmer, 1974) A group of participants watch the same video of two cars having an accident. Two weeks later, some are asked to estimate the rate of speed the cars were going when they “smashed” into each other. Some participants are asked to estimate the rate of speed the cars were going when they “bumped” into each other. Changing the phrasing of the question changes the memory of the eyewitness.

5. Intrinsic Motivation in the Classroom (Dweck, 1990) To investigate the role of autonomy on intrinsic motivation, half of the students are told they are “free to choose” which tasks to complete. The other half of the students are told they “must choose” some of the tasks. Researchers then carefully observe how long the students engage in the tasks and later ask them some questions about if they enjoyed doing the tasks or not.

6. Systematic Desensitization (Wolpe, 1958) A clinical psychologist carefully documents his treatment of a patient’s social phobia with progressive relaxation. At first, the patient is trained to monitor, tense, and relax various muscle groups while viewing photos of parties. Weeks later, they approach a stranger to ask for directions, initiate a conversation on a crowded bus, and attend a small social gathering. The therapist’s notes are transcribed into a scientific report and published in a peer-reviewed journal.

7. Study of Remembering (Bartlett, 1932) Bartlett’s work is a seminal study in the field of memory, where he used the concept of “schema” to describe an organized pattern of thought or behavior. He conducted a series of experiments using folk tales to show that memory recall is influenced by cultural schemas and personal experiences.

8. Study of Obedience (Milgram, 1963) This famous study explored the conflict between obedience to authority and personal conscience. Milgram found that a majority of participants were willing to administer what they believed were harmful electric shocks to a stranger when instructed by an authority figure, highlighting the power of authority and situational factors in driving behavior.

9. Pavlov’s Dog Study (Pavlov, 1927) Ivan Pavlov, a Russian physiologist, conducted a series of experiments that became a cornerstone in the field of experimental psychology. Pavlov noticed that dogs would salivate when they saw food. He then began to ring a bell each time he presented the food to the dogs. After a while, the dogs began to salivate merely at the sound of the bell. This experiment demonstrated the principle of “classical conditioning.”

10, Piaget’s Stages of Development (Piaget, 1958) Jean Piaget proposed a theory of cognitive development in children that consists of four distinct stages: the sensorimotor stage (birth to 2 years), where children learn about the world through their senses and motor activities, through to the the formal operational stage (12 years and beyond), where abstract reasoning and hypothetical thinking develop. Piaget’s theory is an example of experimental psychology as it was developed through systematic observation and experimentation on children’s problem-solving behaviors .

Types of Research Methodologies in Experimental Psychology 

Researchers utilize several different types of research methodologies since the early days of Wundt (1832-1920).

1. The Experiment

The experiment involves the researcher manipulating the level of one variable, called the Independent Variable (IV), and then observing changes in another variable, called the Dependent Variable (DV).

The researcher is interested in determining if the IV causes changes in the DV. For example, does television violence make children more aggressive?

So, some children in the study, called research participants, will watch a show with TV violence, called the treatment group. Others will watch a show with no TV violence, called the control group.

So, there are two levels of the IV: violence and no violence. Next, children will be observed to see if they act more aggressively. This is the DV.

If TV violence makes children more aggressive, then the children that watched the violent show will me more aggressive than the children that watched the non-violent show.

A key requirement of the experiment is random assignment . Each research participant is assigned to one of the two groups in a way that makes it a completely random process. This means that each group will have a mix of children: different personality types, diverse family backgrounds, and range of intelligence levels.

2. The Longitudinal Study

A longitudinal study involves selecting a sample of participants and then following them for years, or decades, periodically collecting data on the variables of interest.

For example, a researcher might be interested in determining if parenting style affects academic performance of children. Parenting style is called the predictor variable , and academic performance is called the outcome variable .

Researchers will begin by randomly selecting a group of children to be in the study. Then, they will identify the type of parenting practices used when the children are 4 and 5 years old.

A few years later, perhaps when the children are 8 and 9, the researchers will collect data on their grades. This process can be repeated over the next 10 years, including through college.

If parenting style has an effect on academic performance, then the researchers will see a connection between the predictor variable and outcome variable.

Children raised with parenting style X will have higher grades than children raised with parenting style Y.

3. The Case Study

The case study is an in-depth study of one individual. This is a research methodology often used early in the examination of a psychological phenomenon or therapeutic treatment.

For example, in the early days of treating phobias, a clinical psychologist may try teaching one of their patients how to relax every time they see the object that creates so much fear and anxiety, such as a large spider.

The therapist would take very detailed notes on how the teaching process was implemented and the reactions of the patient. When the treatment had been completed, those notes would be written in a scientific form and submitted for publication in a scientific journal for other therapists to learn from.

There are several other types of methodologies available which vary different aspects of the three described above. The researcher will select a methodology that is most appropriate to the phenomenon they want to examine.

They also must take into account various practical considerations such as how much time and resources are needed to complete the study. Conducting research always costs money.

People and equipment are needed to carry-out every study, so researchers often try to obtain funding from their university or a government agency. 

Origins and Key Developments in Experimental Psychology

Wilhelm Maximilian Wundt (1832-1920) is considered one of the fathers of modern psychology. He was a physiologist and philosopher and helped establish psychology as a distinct discipline (Khaleefa, 1999).  

In 1879 he established the world’s first psychology research lab at the University of Leipzig. This is considered a key milestone for establishing psychology as a scientific discipline. In addition to being the first person to use the term “psychologist,” to describe himself, he also founded the discipline’s first scientific journal Philosphische Studien in 1883.

Another notable figure in the development of experimental psychology is Ernest Weber . Trained as a physician, Weber studied sensation and perception and created the first quantitative law in psychology.

The equation denotes how judgments of sensory differences are relative to previous levels of sensation, referred to as the just-noticeable difference (jnd). This is known today as Weber’s Law (Hergenhahn, 2009).    

Gustav Fechner , one of Weber’s students, published the first book on experimental psychology in 1860, titled Elemente der Psychophysik. His worked centered on the measurement of psychophysical facets of sensation and perception, with many of his methods still in use today.    

The first American textbook on experimental psychology was Elements of Physiological Psychology, published in 1887 by George Trumball Ladd .

Ladd also established a psychology lab at Yale University, while Stanley Hall and Charles Sanders continued Wundt’s work at a lab at Johns Hopkins University.

In the late 1800s, Charles Pierce’s contribution to experimental psychology is especially noteworthy because he invented the concept of random assignment (Stigler, 1992; Dehue, 1997).

Go Deeper: 15 Random Assignment Examples

This procedure ensures that each participant has an equal chance of being placed in any of the experimental groups (e.g., treatment or control group). This eliminates the influence of confounding factors related to inherent characteristics of the participants.

Random assignment is a fundamental criterion for a study to be considered a valid experiment.

From there, experimental psychology flourished in the 20th century as a science and transformed into an approach utilized in cognitive psychology, developmental psychology, and social psychology .

Today, the term experimental psychology refers to the study of a wide range of phenomena and involves methodologies not limited to the manipulation of variables.

The Scientific Process and Experimental Psychology

The one thing that makes psychology a science and distinguishes it from its roots in philosophy is the reliance upon the scientific process to answer questions. This makes psychology a science was the main goal of its earliest founders such as Wilhelm Wundt.

There are numerous steps in the scientific process, outlined in the graphic below.

1. Observation

First, the scientist observes an interesting phenomenon that sparks a question. For example, are the memories of eyewitnesses really reliable, or are they subject to bias or unintentional manipulation?

2. Hypothesize

Next, this question is converted into a testable hypothesis. For instance: the words used to question a witness can influence what they think they remember.

3. Devise a Study

Then the researcher(s) select a methodology that will allow them to test that hypothesis. In this case, the researchers choose the experiment, which will involve randomly assigning some participants to different conditions.

In one condition, participants are asked a question that implies a certain memory (treatment group), while other participants are asked a question which is phrased neutrally and does not imply a certain memory (control group).

The researchers then write a proposal that describes in detail the procedures they want to use, how participants will be selected, and the safeguards they will employ to ensure the rights of the participants.

That proposal is submitted to an Institutional Review Board (IRB). The IRB is comprised of a panel of researchers, community representatives, and other professionals that are responsible for reviewing all studies involving human participants.

4. Conduct the Study

If the IRB accepts the proposal, then the researchers may begin collecting data. After the data has been collected, it is analyzed using a software program such as SPSS.

Those analyses will either support or reject the hypothesis. That is, either the participants’ memories were affected by the wording of the question, or not.

5. Publish the study

Finally, the researchers write a paper detailing their procedures and results of the statistical analyses. That paper is then submitted to a scientific journal.

The lead editor of that journal will then send copies of the paper to 3-5 experts in that subject. Each of those experts will read the paper and basically try to find as many things wrong with it as possible. Because they are experts, they are very good at this task.

After reading those critiques, most likely, the editor will send the paper back to the researchers and require that they respond to the criticisms, collect more data, or reject the paper outright.

In some cases, the study was so well-done that the criticisms were minimal and the editor accepts the paper. It then gets published in the scientific journal several months later.

That entire process can easily take 2 years, usually more. But, the findings of that study went through a very rigorous process. This means that we can have substantial confidence that the conclusions of the study are valid.

Experimental psychology refers to utilizing a scientific process to investigate psychological phenomenon.

There are a variety of methods employed today. They are used to study a wide range of subjects, including memory, cognitive processes, emotions and the neurophysiological basis of each.

The history of psychology as a science began in the 1800s primarily in Germany. As interest grew, the field expanded to the United States where several influential research labs were established.

As more methodologies were developed, the field of psychology as a science evolved into a prolific scientific discipline that has provided invaluable insights into human behavior.

Bartlett, F. C., & Bartlett, F. C. (1995).  Remembering: A study in experimental and social psychology . Cambridge university press.

Dehue, T. (1997). Deception, efficiency, and random groups: Psychology and the gradual origination of the random group design. Isis , 88 (4), 653-673.

Ebbinghaus, H. (2013). Memory: A contribution to experimental psychology.  Annals of neurosciences ,  20 (4), 155.

Hergenhahn, B. R. (2009). An introduction to the history of psychology. Belmont. CA: Wadsworth Cengage Learning .

Khaleefa, O. (1999). Who is the founder of psychophysics and experimental psychology? American Journal of Islam and Society , 16 (2), 1-26.

Loftus, E. F., & Palmer, J. C. (1974).  Reconstruction of auto-mobile destruction : An example of the interaction between language and memory.  Journal of Verbal Learning and Verbal behavior , 13, 585-589.

Pavlov, I.P. (1927). Conditioned reflexes . Dover, New York.

Piaget, J. (1959).  The language and thought of the child  (Vol. 5). Psychology Press.

Piaget, J., Fraisse, P., & Reuchlin, M. (2014). Experimental psychology its scope and method: Volume I (Psychology Revivals): History and method . Psychology Press.

Skinner, B. F. (1956). A case history in scientlfic method. American Psychologist, 11 , 221-233

Stigler, S. M. (1992). A historical view of statistical concepts in psychology and educational research. American Journal of Education , 101 (1), 60-70.

Thorndike, E. L. (1898). Animal intelligence: An experimental study of the associative processes in animals. Psychological Review Monograph Supplement 2 .

Wolpe, J. (1958). Psychotherapy by reciprocal inhibition. Stanford, CA: Stanford University Press.

Appendix: Images reproduced as Text

Definition: Experimental psychology is a branch of psychology that focuses on conducting systematic and controlled experiments to study human behavior and cognition.

Overview: Experimental psychology aims to gather empirical evidence and explore cause-and-effect relationships between variables. Experimental psychologists utilize various research methods, including laboratory experiments, surveys, and observations, to investigate topics such as perception, memory, learning, motivation, and social behavior .

Example: The Pavlov’s Dog experimental psychology experiment used scientific methods to develop a theory about how learning and association occur in animals. The same concepts were subsequently used in the study of humans, wherein psychology-based ideas about learning were developed. Pavlov’s use of the empirical evidence was foundational to the study’s success.

Experimental Psychology Milestones:

1890: William James publishes “The Principles of Psychology”, a foundational text in the field of psychology.

1896: Lightner Witmer opens the first psychological clinic at the University of Pennsylvania, marking the beginning of clinical psychology.

1913: John B. Watson publishes “Psychology as the Behaviorist Views It”, marking the beginning of Behaviorism.

1920: Hermann Rorschach introduces the Rorschach inkblot test.

1938: B.F. Skinner introduces the concept of operant conditioning .

1967: Ulric Neisser publishes “Cognitive Psychology” , marking the beginning of the cognitive revolution.

1980: The third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III) is published, introducing a new classification system for mental disorders.

The Scientific Process

• Observe an interesting phenomenon
• Formulate testable hypothesis
• Select methodology and design study
• Submit research proposal to IRB
• Collect and analyzed data; write paper
• Submit paper for critical reviews

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• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Defense Mechanisms Examples
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• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 18 Adaptive Behavior Examples

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 23 Achieved Status Examples
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• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 15 Theory of Planned Behavior Examples

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6.1 Experiment Basics

Learning objectives.

• Explain what an experiment is and recognize examples of studies that are experiments and studies that are not experiments.
• Explain what internal validity is and why experiments are considered to be high in internal validity.
• Explain what external validity is and evaluate studies in terms of their external validity.
• Distinguish between the manipulation of the independent variable and control of extraneous variables and explain the importance of each.
• Recognize examples of confounding variables and explain how they affect the internal validity of a study.

What Is an Experiment?

As we saw earlier in the book, an experiment is a type of study designed specifically to answer the question of whether there is a causal relationship between two variables. Do changes in an independent variable cause changes in a dependent variable? Experiments have two fundamental features. The first is that the researchers manipulate, or systematically vary, the level of the independent variable. The different levels of the independent variable are called conditions. For example, in Darley and Latané’s experiment, the independent variable was the number of witnesses that participants believed to be present. The researchers manipulated this independent variable by telling participants that there were either one, two, or five other students involved in the discussion, thereby creating three conditions. The second fundamental feature of an experiment is that the researcher controls, or minimizes the variability in, variables other than the independent and dependent variable. These other variables are called extraneous variables. Darley and Latané tested all their participants in the same room, exposed them to the same emergency situation, and so on. They also randomly assigned their participants to conditions so that the three groups would be similar to each other to begin with. Notice that although the words manipulation and control have similar meanings in everyday language, researchers make a clear distinction between them. They manipulate the independent variable by systematically changing its levels and control other variables by holding them constant.

Internal and External Validity

Internal validity.

Recall that the fact that two variables are statistically related does not necessarily mean that one causes the other. “Correlation does not imply causation.” For example, if it were the case that people who exercise regularly are happier than people who do not exercise regularly, this would not necessarily mean that exercising increases people’s happiness. It could mean instead that greater happiness causes people to exercise (the directionality problem) or that something like better physical health causes people to exercise and be happier (the third-variable problem).

The purpose of an experiment, however, is to show that two variables are statistically related and to do so in a way that supports the conclusion that the independent variable caused any observed differences in the dependent variable. The basic logic is this: If the researcher creates two or more highly similar conditions and then manipulates the independent variable to produce just one difference between them, then any later difference between the conditions must have been caused by the independent variable. For example, because the only difference between Darley and Latané’s conditions was the number of students that participants believed to be involved in the discussion, this must have been responsible for differences in helping between the conditions.

An empirical study is said to be high in internal validity if the way it was conducted supports the conclusion that the independent variable caused any observed differences in the dependent variable. Thus experiments are high in internal validity because the way they are conducted—with the manipulation of the independent variable and the control of extraneous variables—provides strong support for causal conclusions.

External Validity

At the same time, the way that experiments are conducted sometimes leads to a different kind of criticism. Specifically, the need to manipulate the independent variable and control extraneous variables means that experiments are often conducted under conditions that seem artificial or unlike “real life” (Stanovich, 2010). In many psychology experiments, the participants are all college undergraduates and come to a classroom or laboratory to fill out a series of paper-and-pencil questionnaires or to perform a carefully designed computerized task. Consider, for example, an experiment in which researcher Barbara Fredrickson and her colleagues had college students come to a laboratory on campus and complete a math test while wearing a swimsuit (Fredrickson, Roberts, Noll, Quinn, & Twenge, 1998). At first, this might seem silly. When will college students ever have to complete math tests in their swimsuits outside of this experiment?

The issue we are confronting is that of external validity. An empirical study is high in external validity if the way it was conducted supports generalizing the results to people and situations beyond those actually studied. As a general rule, studies are higher in external validity when the participants and the situation studied are similar to those that the researchers want to generalize to. Imagine, for example, that a group of researchers is interested in how shoppers in large grocery stores are affected by whether breakfast cereal is packaged in yellow or purple boxes. Their study would be high in external validity if they studied the decisions of ordinary people doing their weekly shopping in a real grocery store. If the shoppers bought much more cereal in purple boxes, the researchers would be fairly confident that this would be true for other shoppers in other stores. Their study would be relatively low in external validity, however, if they studied a sample of college students in a laboratory at a selective college who merely judged the appeal of various colors presented on a computer screen. If the students judged purple to be more appealing than yellow, the researchers would not be very confident that this is relevant to grocery shoppers’ cereal-buying decisions.

We should be careful, however, not to draw the blanket conclusion that experiments are low in external validity. One reason is that experiments need not seem artificial. Consider that Darley and Latané’s experiment provided a reasonably good simulation of a real emergency situation. Or consider field experiments that are conducted entirely outside the laboratory. In one such experiment, Robert Cialdini and his colleagues studied whether hotel guests choose to reuse their towels for a second day as opposed to having them washed as a way of conserving water and energy (Cialdini, 2005). These researchers manipulated the message on a card left in a large sample of hotel rooms. One version of the message emphasized showing respect for the environment, another emphasized that the hotel would donate a portion of their savings to an environmental cause, and a third emphasized that most hotel guests choose to reuse their towels. The result was that guests who received the message that most hotel guests choose to reuse their towels reused their own towels substantially more often than guests receiving either of the other two messages. Given the way they conducted their study, it seems very likely that their result would hold true for other guests in other hotels.

A second reason not to draw the blanket conclusion that experiments are low in external validity is that they are often conducted to learn about psychological processes that are likely to operate in a variety of people and situations. Let us return to the experiment by Fredrickson and colleagues. They found that the women in their study, but not the men, performed worse on the math test when they were wearing swimsuits. They argued that this was due to women’s greater tendency to objectify themselves—to think about themselves from the perspective of an outside observer—which diverts their attention away from other tasks. They argued, furthermore, that this process of self-objectification and its effect on attention is likely to operate in a variety of women and situations—even if none of them ever finds herself taking a math test in her swimsuit.

Manipulation of the Independent Variable

Again, to manipulate an independent variable means to change its level systematically so that different groups of participants are exposed to different levels of that variable, or the same group of participants is exposed to different levels at different times. For example, to see whether expressive writing affects people’s health, a researcher might instruct some participants to write about traumatic experiences and others to write about neutral experiences. The different levels of the independent variable are referred to as conditions , and researchers often give the conditions short descriptive names to make it easy to talk and write about them. In this case, the conditions might be called the “traumatic condition” and the “neutral condition.”

Notice that the manipulation of an independent variable must involve the active intervention of the researcher. Comparing groups of people who differ on the independent variable before the study begins is not the same as manipulating that variable. For example, a researcher who compares the health of people who already keep a journal with the health of people who do not keep a journal has not manipulated this variable and therefore not conducted an experiment. This is important because groups that already differ in one way at the beginning of a study are likely to differ in other ways too. For example, people who choose to keep journals might also be more conscientious, more introverted, or less stressed than people who do not. Therefore, any observed difference between the two groups in terms of their health might have been caused by whether or not they keep a journal, or it might have been caused by any of the other differences between people who do and do not keep journals. Thus the active manipulation of the independent variable is crucial for eliminating the third-variable problem.

Of course, there are many situations in which the independent variable cannot be manipulated for practical or ethical reasons and therefore an experiment is not possible. For example, whether or not people have a significant early illness experience cannot be manipulated, making it impossible to do an experiment on the effect of early illness experiences on the development of hypochondriasis. This does not mean it is impossible to study the relationship between early illness experiences and hypochondriasis—only that it must be done using nonexperimental approaches. We will discuss this in detail later in the book.

In many experiments, the independent variable is a construct that can only be manipulated indirectly. For example, a researcher might try to manipulate participants’ stress levels indirectly by telling some of them that they have five minutes to prepare a short speech that they will then have to give to an audience of other participants. In such situations, researchers often include a manipulation check in their procedure. A manipulation check is a separate measure of the construct the researcher is trying to manipulate. For example, researchers trying to manipulate participants’ stress levels might give them a paper-and-pencil stress questionnaire or take their blood pressure—perhaps right after the manipulation or at the end of the procedure—to verify that they successfully manipulated this variable.

Control of Extraneous Variables

An extraneous variable is anything that varies in the context of a study other than the independent and dependent variables. In an experiment on the effect of expressive writing on health, for example, extraneous variables would include participant variables (individual differences) such as their writing ability, their diet, and their shoe size. They would also include situation or task variables such as the time of day when participants write, whether they write by hand or on a computer, and the weather. Extraneous variables pose a problem because many of them are likely to have some effect on the dependent variable. For example, participants’ health will be affected by many things other than whether or not they engage in expressive writing. This can make it difficult to separate the effect of the independent variable from the effects of the extraneous variables, which is why it is important to control extraneous variables by holding them constant.

Extraneous Variables as “Noise”

Extraneous variables make it difficult to detect the effect of the independent variable in two ways. One is by adding variability or “noise” to the data. Imagine a simple experiment on the effect of mood (happy vs. sad) on the number of happy childhood events people are able to recall. Participants are put into a negative or positive mood (by showing them a happy or sad video clip) and then asked to recall as many happy childhood events as they can. The two leftmost columns of Table 6.1 “Hypothetical Noiseless Data and Realistic Noisy Data” show what the data might look like if there were no extraneous variables and the number of happy childhood events participants recalled was affected only by their moods. Every participant in the happy mood condition recalled exactly four happy childhood events, and every participant in the sad mood condition recalled exactly three. The effect of mood here is quite obvious. In reality, however, the data would probably look more like those in the two rightmost columns of Table 6.1 “Hypothetical Noiseless Data and Realistic Noisy Data” . Even in the happy mood condition, some participants would recall fewer happy memories because they have fewer to draw on, use less effective strategies, or are less motivated. And even in the sad mood condition, some participants would recall more happy childhood memories because they have more happy memories to draw on, they use more effective recall strategies, or they are more motivated. Although the mean difference between the two groups is the same as in the idealized data, this difference is much less obvious in the context of the greater variability in the data. Thus one reason researchers try to control extraneous variables is so their data look more like the idealized data in Table 6.1 “Hypothetical Noiseless Data and Realistic Noisy Data” , which makes the effect of the independent variable is easier to detect (although real data never look quite that good).

Table 6.1 Hypothetical Noiseless Data and Realistic Noisy Data

One way to control extraneous variables is to hold them constant. This can mean holding situation or task variables constant by testing all participants in the same location, giving them identical instructions, treating them in the same way, and so on. It can also mean holding participant variables constant. For example, many studies of language limit participants to right-handed people, who generally have their language areas isolated in their left cerebral hemispheres. Left-handed people are more likely to have their language areas isolated in their right cerebral hemispheres or distributed across both hemispheres, which can change the way they process language and thereby add noise to the data.

In principle, researchers can control extraneous variables by limiting participants to one very specific category of person, such as 20-year-old, straight, female, right-handed, sophomore psychology majors. The obvious downside to this approach is that it would lower the external validity of the study—in particular, the extent to which the results can be generalized beyond the people actually studied. For example, it might be unclear whether results obtained with a sample of younger straight women would apply to older gay men. In many situations, the advantages of a diverse sample outweigh the reduction in noise achieved by a homogeneous one.

Extraneous Variables as Confounding Variables

The second way that extraneous variables can make it difficult to detect the effect of the independent variable is by becoming confounding variables. A confounding variable is an extraneous variable that differs on average across levels of the independent variable. For example, in almost all experiments, participants’ intelligence quotients (IQs) will be an extraneous variable. But as long as there are participants with lower and higher IQs at each level of the independent variable so that the average IQ is roughly equal, then this variation is probably acceptable (and may even be desirable). What would be bad, however, would be for participants at one level of the independent variable to have substantially lower IQs on average and participants at another level to have substantially higher IQs on average. In this case, IQ would be a confounding variable.

To confound means to confuse, and this is exactly what confounding variables do. Because they differ across conditions—just like the independent variable—they provide an alternative explanation for any observed difference in the dependent variable. Figure 6.1 “Hypothetical Results From a Study on the Effect of Mood on Memory” shows the results of a hypothetical study, in which participants in a positive mood condition scored higher on a memory task than participants in a negative mood condition. But if IQ is a confounding variable—with participants in the positive mood condition having higher IQs on average than participants in the negative mood condition—then it is unclear whether it was the positive moods or the higher IQs that caused participants in the first condition to score higher. One way to avoid confounding variables is by holding extraneous variables constant. For example, one could prevent IQ from becoming a confounding variable by limiting participants only to those with IQs of exactly 100. But this approach is not always desirable for reasons we have already discussed. A second and much more general approach—random assignment to conditions—will be discussed in detail shortly.

Figure 6.1 Hypothetical Results From a Study on the Effect of Mood on Memory

Because IQ also differs across conditions, it is a confounding variable.

Key Takeaways

• An experiment is a type of empirical study that features the manipulation of an independent variable, the measurement of a dependent variable, and control of extraneous variables.
• Studies are high in internal validity to the extent that the way they are conducted supports the conclusion that the independent variable caused any observed differences in the dependent variable. Experiments are generally high in internal validity because of the manipulation of the independent variable and control of extraneous variables.
• Studies are high in external validity to the extent that the result can be generalized to people and situations beyond those actually studied. Although experiments can seem “artificial”—and low in external validity—it is important to consider whether the psychological processes under study are likely to operate in other people and situations.
• Practice: List five variables that can be manipulated by the researcher in an experiment. List five variables that cannot be manipulated by the researcher in an experiment.

Practice: For each of the following topics, decide whether that topic could be studied using an experimental research design and explain why or why not.

• Effect of parietal lobe damage on people’s ability to do basic arithmetic.
• Effect of being clinically depressed on the number of close friendships people have.
• Effect of group training on the social skills of teenagers with Asperger’s syndrome.
• Effect of paying people to take an IQ test on their performance on that test.

Cialdini, R. (2005, April). Don’t throw in the towel: Use social influence research. APS Observer . Retrieved from http://www.psychologicalscience.org/observer/getArticle.cfm?id=1762 .

Fredrickson, B. L., Roberts, T.-A., Noll, S. M., Quinn, D. M., & Twenge, J. M. (1998). The swimsuit becomes you: Sex differences in self-objectification, restrained eating, and math performance. Journal of Personality and Social Psychology, 75 , 269–284.

Stanovich, K. E. (2010). How to think straight about psychology (9th ed.). Boston, MA: Allyn & Bacon.

Research Methods in Psychology Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Experimental Psychology

Definition:

Experimental psychology is a subfield of psychology that focuses on scientific investigation and research methods to study human behavior and mental processes. It involves conducting controlled experiments to examine hypotheses and gather empirical data.

Subfields of Experimental Psychology:

Sensory processes:.

Sensory processes in experimental psychology involve understanding how humans perceive and process information through their senses, such as vision, hearing, taste, smell, and touch.

Learning and Memory:

This subfield explores how individuals acquire and retain knowledge and skills, including the study of different types of memory, learning strategies, and factors that influence memory processes.

Cognitive Psychology:

Cognitive psychology examines mental processes, including attention, perception, problem-solving, decision-making, language, and thinking. It investigates how individuals process information, solve problems, and make decisions.

Developmental Psychology:

Developmental psychology focuses on the study of human development across the lifespan, from infancy to old age. It investigates how individuals change physically, cognitively, and emotionally as they grow and mature.

Social Psychology:

Social psychology studies how individuals’ thoughts, feelings, and behaviors are influenced by social interactions and social environments. It examines topics such as conformity, persuasion, group dynamics, and intergroup relations.

Personality Psychology:

Personality psychology aims to understand individual differences in behavior, thoughts, and emotions. It investigates various personality traits, their development, and how they influence behavior and well-being.

Psychopathology:

This subfield focuses on the study of mental disorders, their causes, symptoms, and treatments. Psychopathology research is often conducted using experimental methods to examine the effectiveness of therapeutic interventions.

Psychopharmacology:

Psychopharmacology involves studying the effects of drugs on behavior, cognition, and emotions. It examines how different medications impact mental processes and aims to develop effective pharmacological treatments for psychological disorders.

Neuropsychology:

Neuropsychology investigates the relationship between brain function and behavior. It examines how brain damage, genetics, and neurological disorders affect cognitive abilities, emotions, and behavior.

5.1 Experiment Basics

Learning objectives.

• Explain what an experiment is and recognize examples of studies that are experiments and studies that are not experiments.
• Distinguish between the manipulation of the independent variable and control of extraneous variables and explain the importance of each.
• Recognize examples of confounding variables and explain how they affect the internal validity of a study.

What Is an Experiment?

As we saw earlier in the book, an  experiment  is a type of study designed specifically to answer the question of whether there is a causal relationship between two variables. In other words, whether changes in an independent variable  cause  a change in a dependent variable. Experiments have two fundamental features. The first is that the researchers manipulate, or systematically vary, the level of the independent variable. The different levels of the independent variable are called conditions . For example, in Darley and Latané’s experiment, the independent variable was the number of witnesses that participants believed to be present. The researchers manipulated this independent variable by telling participants that there were either one, two, or five other students involved in the discussion, thereby creating three conditions. For a new researcher, it is easy to confuse  these terms by believing there are three independent variables in this situation: one, two, or five students involved in the discussion, but there is actually only one independent variable (number of witnesses) with three different levels or conditions (one, two or five students). The second fundamental feature of an experiment is that the researcher controls, or minimizes the variability in, variables other than the independent and dependent variable. These other variables are called extraneous variables . Darley and Latané tested all their participants in the same room, exposed them to the same emergency situation, and so on. They also randomly assigned their participants to conditions so that the three groups would be similar to each other to begin with. Notice that although the words  manipulation  and  control  have similar meanings in everyday language, researchers make a clear distinction between them. They manipulate  the independent variable by systematically changing its levels and control  other variables by holding them constant.

Manipulation of the Independent Variable

Again, to  manipulate  an independent variable means to change its level systematically so that different groups of participants are exposed to different levels of that variable, or the same group of participants is exposed to different levels at different times. For example, to see whether expressive writing affects people’s health, a researcher might instruct some participants to write about traumatic experiences and others to write about neutral experiences. As discussed earlier in this chapter, the different levels of the independent variable are referred to as  conditions , and researchers often give the conditions short descriptive names to make it easy to talk and write about them. In this case, the conditions might be called the “traumatic condition” and the “neutral condition.”

Notice that the manipulation of an independent variable must involve the active intervention of the researcher. Comparing groups of people who differ on the independent variable before the study begins is not the same as manipulating that variable. For example, a researcher who compares the health of people who already keep a journal with the health of people who do not keep a journal has not manipulated this variable and therefore has not conducted an experiment. This distinction  is important because groups that already differ in one way at the beginning of a study are likely to differ in other ways too. For example, people who choose to keep journals might also be more conscientious, more introverted, or less stressed than people who do not. Therefore, any observed difference between the two groups in terms of their health might have been caused by whether or not they keep a journal, or it might have been caused by any of the other differences between people who do and do not keep journals. Thus the active manipulation of the independent variable is crucial for eliminating potential alternative explanations for the results.

Of course, there are many situations in which the independent variable cannot be manipulated for practical or ethical reasons and therefore an experiment is not possible. For example, whether or not people have a significant early illness experience cannot be manipulated, making it impossible to conduct an experiment on the effect of early illness experiences on the development of hypochondriasis. This caveat does not mean it is impossible to study the relationship between early illness experiences and hypochondriasis—only that it must be done using nonexperimental approaches. We will discuss this type of methodology in detail later in the book.

Independent variables can be manipulated to create two conditions and experiments involving a single independent variable with two conditions is often referred to as a  single factor two-level design.  However, sometimes greater insights can be gained by adding more conditions to an experiment. When an experiment has one independent variable that is manipulated to produce more than two conditions it is referred to as a single factor multi level design.  So rather than comparing a condition in which there was one witness to a condition in which there were five witnesses (which would represent a single-factor two-level design), Darley and Latané’s used a single factor multi-level design, by manipulating the independent variable to produce three conditions (a one witness, a two witnesses, and a five witnesses condition).

Control of Extraneous Variables

As we have seen previously in the chapter, an  extraneous variable  is anything that varies in the context of a study other than the independent and dependent variables. In an experiment on the effect of expressive writing on health, for example, extraneous variables would include participant variables (individual differences) such as their writing ability, their diet, and their gender. They would also include situational or task variables such as the time of day when participants write, whether they write by hand or on a computer, and the weather. Extraneous variables pose a problem because many of them are likely to have some effect on the dependent variable. For example, participants’ health will be affected by many things other than whether or not they engage in expressive writing. This influencing factor can make it difficult to separate the effect of the independent variable from the effects of the extraneous variables, which is why it is important to  control  extraneous variables by holding them constant.

Extraneous Variables as “Noise”

Extraneous variables make it difficult to detect the effect of the independent variable in two ways. One is by adding variability or “noise” to the data. Imagine a simple experiment on the effect of mood (happy vs. sad) on the number of happy childhood events people are able to recall. Participants are put into a negative or positive mood (by showing them a happy or sad video clip) and then asked to recall as many happy childhood events as they can. The two leftmost columns of  Table 5.1 show what the data might look like if there were no extraneous variables and the number of happy childhood events participants recalled was affected only by their moods. Every participant in the happy mood condition recalled exactly four happy childhood events, and every participant in the sad mood condition recalled exactly three. The effect of mood here is quite obvious. In reality, however, the data would probably look more like those in the two rightmost columns of  Table 5.1 . Even in the happy mood condition, some participants would recall fewer happy memories because they have fewer to draw on, use less effective recall strategies, or are less motivated. And even in the sad mood condition, some participants would recall more happy childhood memories because they have more happy memories to draw on, they use more effective recall strategies, or they are more motivated. Although the mean difference between the two groups is the same as in the idealized data, this difference is much less obvious in the context of the greater variability in the data. Thus one reason researchers try to control extraneous variables is so their data look more like the idealized data in  Table 5.1 , which makes the effect of the independent variable easier to detect (although real data never look quite  that  good).

One way to control extraneous variables is to hold them constant. This technique can mean holding situation or task variables constant by testing all participants in the same location, giving them identical instructions, treating them in the same way, and so on. It can also mean holding participant variables constant. For example, many studies of language limit participants to right-handed people, who generally have their language areas isolated in their left cerebral hemispheres. Left-handed people are more likely to have their language areas isolated in their right cerebral hemispheres or distributed across both hemispheres, which can change the way they process language and thereby add noise to the data.

In principle, researchers can control extraneous variables by limiting participants to one very specific category of person, such as 20-year-old, heterosexual, female, right-handed psychology majors. The obvious downside to this approach is that it would lower the external validity of the study—in particular, the extent to which the results can be generalized beyond the people actually studied. For example, it might be unclear whether results obtained with a sample of younger heterosexual women would apply to older homosexual men. In many situations, the advantages of a diverse sample (increased external validity) outweigh the reduction in noise achieved by a homogeneous one.

Extraneous Variables as Confounding Variables

The second way that extraneous variables can make it difficult to detect the effect of the independent variable is by becoming confounding variables. A confounding variable  is an extraneous variable that differs on average across  levels of the independent variable (i.e., it is an extraneous variable that varies systematically with the independent variable). For example, in almost all experiments, participants’ intelligence quotients (IQs) will be an extraneous variable. But as long as there are participants with lower and higher IQs in each condition so that the average IQ is roughly equal across the conditions, then this variation is probably acceptable (and may even be desirable). What would be bad, however, would be for participants in one condition to have substantially lower IQs on average and participants in another condition to have substantially higher IQs on average. In this case, IQ would be a confounding variable.

To confound means to confuse , and this effect is exactly why confounding variables are undesirable. Because they differ systematically across conditions—just like the independent variable—they provide an alternative explanation for any observed difference in the dependent variable.  Figure 5.1  shows the results of a hypothetical study, in which participants in a positive mood condition scored higher on a memory task than participants in a negative mood condition. But if IQ is a confounding variable—with participants in the positive mood condition having higher IQs on average than participants in the negative mood condition—then it is unclear whether it was the positive moods or the higher IQs that caused participants in the first condition to score higher. One way to avoid confounding variables is by holding extraneous variables constant. For example, one could prevent IQ from becoming a confounding variable by limiting participants only to those with IQs of exactly 100. But this approach is not always desirable for reasons we have already discussed. A second and much more general approach—random assignment to conditions—will be discussed in detail shortly.

Figure 5.1 Hypothetical Results From a Study on the Effect of Mood on Memory. Because IQ also differs across conditions, it is a confounding variable.

Key Takeaways

• An experiment is a type of empirical study that features the manipulation of an independent variable, the measurement of a dependent variable, and control of extraneous variables.
• An extraneous variable is any variable other than the independent and dependent variables. A confound is an extraneous variable that varies systematically with the independent variable.
• Practice: List five variables that can be manipulated by the researcher in an experiment. List five variables that cannot be manipulated by the researcher in an experiment.
• Effect of parietal lobe damage on people’s ability to do basic arithmetic.
• Effect of being clinically depressed on the number of close friendships people have.
• Effect of group training on the social skills of teenagers with Asperger’s syndrome.
• Effect of paying people to take an IQ test on their performance on that test.

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Experimental Research

23 Experiment Basics

Learning objectives.

• Explain what an experiment is and recognize examples of studies that are experiments and studies that are not experiments.
• Distinguish between the manipulation of the independent variable and control of extraneous variables and explain the importance of each.
• Recognize examples of confounding variables and explain how they affect the internal validity of a study.
• Define what a control condition is, explain its purpose in research on treatment effectiveness, and describe some alternative types of control conditions.

What Is an Experiment?

As we saw earlier in the book, an  experiment is a type of study designed specifically to answer the question of whether there is a causal relationship between two variables. In other words, whether changes in one variable (referred to as an independent variable ) cause a change in another variable (referred to as a dependent variable ). Experiments have two fundamental features. The first is that the researchers manipulate, or systematically vary, the level of the independent variable. The different levels of the independent variable are called conditions . For example, in Darley and Latané’s experiment, the independent variable was the number of witnesses that participants believed to be present. The researchers manipulated this independent variable by telling participants that there were either one, two, or five other students involved in the discussion, thereby creating three conditions. For a new researcher, it is easy to confuse these terms by believing there are three independent variables in this situation: one, two, or five students involved in the discussion, but there is actually only one independent variable (number of witnesses) with three different levels or conditions (one, two or five students). The second fundamental feature of an experiment is that the researcher exerts control over, or minimizes the variability in, variables other than the independent and dependent variable. These other variables are called extraneous variables . Darley and Latané tested all their participants in the same room, exposed them to the same emergency situation, and so on. They also randomly assigned their participants to conditions so that the three groups would be similar to each other to begin with. Notice that although the words  manipulation  and  control  have similar meanings in everyday language, researchers make a clear distinction between them. They manipulate  the independent variable by systematically changing its levels and control  other variables by holding them constant.

Manipulation of the Independent Variable

Again, to  manipulate an independent variable means to change its level systematically so that different groups of participants are exposed to different levels of that variable, or the same group of participants is exposed to different levels at different times. For example, to see whether expressive writing affects people’s health, a researcher might instruct some participants to write about traumatic experiences and others to write about neutral experiences. The different levels of the independent variable are referred to as conditions , and researchers often give the conditions short descriptive names to make it easy to talk and write about them. In this case, the conditions might be called the “traumatic condition” and the “neutral condition.”

Notice that the manipulation of an independent variable must involve the active intervention of the researcher. Comparing groups of people who differ on the independent variable before the study begins is not the same as manipulating that variable. For example, a researcher who compares the health of people who already keep a journal with the health of people who do not keep a journal has not manipulated this variable and therefore has not conducted an experiment. This distinction  is important because groups that already differ in one way at the beginning of a study are likely to differ in other ways too. For example, people who choose to keep journals might also be more conscientious, more introverted, or less stressed than people who do not. Therefore, any observed difference between the two groups in terms of their health might have been caused by whether or not they keep a journal, or it might have been caused by any of the other differences between people who do and do not keep journals. Thus the active manipulation of the independent variable is crucial for eliminating potential alternative explanations for the results.

Of course, there are many situations in which the independent variable cannot be manipulated for practical or ethical reasons and therefore an experiment is not possible. For example, whether or not people have a significant early illness experience cannot be manipulated, making it impossible to conduct an experiment on the effect of early illness experiences on the development of hypochondriasis. This caveat does not mean it is impossible to study the relationship between early illness experiences and hypochondriasis—only that it must be done using nonexperimental approaches. We will discuss this type of methodology in detail later in the book.

Independent variables can be manipulated to create two conditions and experiments involving a single independent variable with two conditions are often referred to as a single factor two-level design .  However, sometimes greater insights can be gained by adding more conditions to an experiment. When an experiment has one independent variable that is manipulated to produce more than two conditions it is referred to as a single factor multi level design .  So rather than comparing a condition in which there was one witness to a condition in which there were five witnesses (which would represent a single-factor two-level design), Darley and Latané’s experiment used a single factor multi-level design, by manipulating the independent variable to produce three conditions (a one witness, a two witnesses, and a five witnesses condition).

Control of Extraneous Variables

As we have seen previously in the chapter, an  extraneous variable  is anything that varies in the context of a study other than the independent and dependent variables. In an experiment on the effect of expressive writing on health, for example, extraneous variables would include participant variables (individual differences) such as their writing ability, their diet, and their gender. They would also include situational or task variables such as the time of day when participants write, whether they write by hand or on a computer, and the weather. Extraneous variables pose a problem because many of them are likely to have some effect on the dependent variable. For example, participants’ health will be affected by many things other than whether or not they engage in expressive writing. This influencing factor can make it difficult to separate the effect of the independent variable from the effects of the extraneous variables, which is why it is important to control extraneous variables by holding them constant.

Extraneous Variables as “Noise”

Extraneous variables make it difficult to detect the effect of the independent variable in two ways. One is by adding variability or “noise” to the data. Imagine a simple experiment on the effect of mood (happy vs. sad) on the number of happy childhood events people are able to recall. Participants are put into a negative or positive mood (by showing them a happy or sad video clip) and then asked to recall as many happy childhood events as they can. The two leftmost columns of  Table 5.1 show what the data might look like if there were no extraneous variables and the number of happy childhood events participants recalled was affected only by their moods. Every participant in the happy mood condition recalled exactly four happy childhood events, and every participant in the sad mood condition recalled exactly three. The effect of mood here is quite obvious. In reality, however, the data would probably look more like those in the two rightmost columns of  Table 5.1 . Even in the happy mood condition, some participants would recall fewer happy memories because they have fewer to draw on, use less effective recall strategies, or are less motivated. And even in the sad mood condition, some participants would recall more happy childhood memories because they have more happy memories to draw on, they use more effective recall strategies, or they are more motivated. Although the mean difference between the two groups is the same as in the idealized data, this difference is much less obvious in the context of the greater variability in the data. Thus one reason researchers try to control extraneous variables is so their data look more like the idealized data in  Table 5.1 , which makes the effect of the independent variable easier to detect (although real data never look quite  that  good).

One way to control extraneous variables is to hold them constant. This technique can mean holding situation or task variables constant by testing all participants in the same location, giving them identical instructions, treating them in the same way, and so on. It can also mean holding participant variables constant. For example, many studies of language limit participants to right-handed people, who generally have their language areas isolated in their left cerebral hemispheres [1] . Left-handed people are more likely to have their language areas isolated in their right cerebral hemispheres or distributed across both hemispheres, which can change the way they process language and thereby add noise to the data.

In principle, researchers can control extraneous variables by limiting participants to one very specific category of person, such as 20-year-old, heterosexual, female, right-handed psychology majors. The obvious downside to this approach is that it would lower the external validity of the study—in particular, the extent to which the results can be generalized beyond the people actually studied. For example, it might be unclear whether results obtained with a sample of younger lesbian women would apply to older gay men. In many situations, the advantages of a diverse sample (increased external validity) outweigh the reduction in noise achieved by a homogeneous one.

Extraneous Variables as Confounding Variables

The second way that extraneous variables can make it difficult to detect the effect of the independent variable is by becoming confounding variables. A confounding variable  is an extraneous variable that differs on average across  levels of the independent variable (i.e., it is an extraneous variable that varies systematically with the independent variable). For example, in almost all experiments, participants’ intelligence quotients (IQs) will be an extraneous variable. But as long as there are participants with lower and higher IQs in each condition so that the average IQ is roughly equal across the conditions, then this variation is probably acceptable (and may even be desirable). What would be bad, however, would be for participants in one condition to have substantially lower IQs on average and participants in another condition to have substantially higher IQs on average. In this case, IQ would be a confounding variable.

To confound means to confuse , and this effect is exactly why confounding variables are undesirable. Because they differ systematically across conditions—just like the independent variable—they provide an alternative explanation for any observed difference in the dependent variable.  Figure 5.1  shows the results of a hypothetical study, in which participants in a positive mood condition scored higher on a memory task than participants in a negative mood condition. But if IQ is a confounding variable—with participants in the positive mood condition having higher IQs on average than participants in the negative mood condition—then it is unclear whether it was the positive moods or the higher IQs that caused participants in the first condition to score higher. One way to avoid confounding variables is by holding extraneous variables constant. For example, one could prevent IQ from becoming a confounding variable by limiting participants only to those with IQs of exactly 100. But this approach is not always desirable for reasons we have already discussed. A second and much more general approach—random assignment to conditions—will be discussed in detail shortly.

Treatment and Control Conditions

In psychological research, a treatment is any intervention meant to change people’s behavior for the better. This intervention includes psychotherapies and medical treatments for psychological disorders but also interventions designed to improve learning, promote conservation, reduce prejudice, and so on. To determine whether a treatment works, participants are randomly assigned to either a treatment condition , in which they receive the treatment, or a control condition , in which they do not receive the treatment. If participants in the treatment condition end up better off than participants in the control condition—for example, they are less depressed, learn faster, conserve more, express less prejudice—then the researcher can conclude that the treatment works. In research on the effectiveness of psychotherapies and medical treatments, this type of experiment is often called a randomized clinical trial .

There are different types of control conditions. In a no-treatment control condition , participants receive no treatment whatsoever. One problem with this approach, however, is the existence of placebo effects. A placebo is a simulated treatment that lacks any active ingredient or element that should make it effective, and a placebo effect is a positive effect of such a treatment. Many folk remedies that seem to work—such as eating chicken soup for a cold or placing soap under the bed sheets to stop nighttime leg cramps—are probably nothing more than placebos. Although placebo effects are not well understood, they are probably driven primarily by people’s expectations that they will improve. Having the expectation to improve can result in reduced stress, anxiety, and depression, which can alter perceptions and even improve immune system functioning (Price, Finniss, & Benedetti, 2008) [2] .

Placebo effects are interesting in their own right (see Note “The Powerful Placebo” ), but they also pose a serious problem for researchers who want to determine whether a treatment works. Figure 5.2 shows some hypothetical results in which participants in a treatment condition improved more on average than participants in a no-treatment control condition. If these conditions (the two leftmost bars in Figure 5.2 ) were the only conditions in this experiment, however, one could not conclude that the treatment worked. It could be instead that participants in the treatment group improved more because they expected to improve, while those in the no-treatment control condition did not.

Fortunately, there are several solutions to this problem. One is to include a placebo control condition , in which participants receive a placebo that looks much like the treatment but lacks the active ingredient or element thought to be responsible for the treatment’s effectiveness. When participants in a treatment condition take a pill, for example, then those in a placebo control condition would take an identical-looking pill that lacks the active ingredient in the treatment (a “sugar pill”). In research on psychotherapy effectiveness, the placebo might involve going to a psychotherapist and talking in an unstructured way about one’s problems. The idea is that if participants in both the treatment and the placebo control groups expect to improve, then any improvement in the treatment group over and above that in the placebo control group must have been caused by the treatment and not by participants’ expectations. This difference is what is shown by a comparison of the two outer bars in Figure 5.4 .

Of course, the principle of informed consent requires that participants be told that they will be assigned to either a treatment or a placebo control condition—even though they cannot be told which until the experiment ends. In many cases the participants who had been in the control condition are then offered an opportunity to have the real treatment. An alternative approach is to use a wait-list control condition , in which participants are told that they will receive the treatment but must wait until the participants in the treatment condition have already received it. This disclosure allows researchers to compare participants who have received the treatment with participants who are not currently receiving it but who still expect to improve (eventually). A final solution to the problem of placebo effects is to leave out the control condition completely and compare any new treatment with the best available alternative treatment. For example, a new treatment for simple phobia could be compared with standard exposure therapy. Because participants in both conditions receive a treatment, their expectations about improvement should be similar. This approach also makes sense because once there is an effective treatment, the interesting question about a new treatment is not simply “Does it work?” but “Does it work better than what is already available?

The Powerful Placebo

Many people are not surprised that placebos can have a positive effect on disorders that seem fundamentally psychological, including depression, anxiety, and insomnia. However, placebos can also have a positive effect on disorders that most people think of as fundamentally physiological. These include asthma, ulcers, and warts (Shapiro & Shapiro, 1999) [3] . There is even evidence that placebo surgery—also called “sham surgery”—can be as effective as actual surgery.

Medical researcher J. Bruce Moseley and his colleagues conducted a study on the effectiveness of two arthroscopic surgery procedures for osteoarthritis of the knee (Moseley et al., 2002) [4] . The control participants in this study were prepped for surgery, received a tranquilizer, and even received three small incisions in their knees. But they did not receive the actual arthroscopic surgical procedure. Note that the IRB would have carefully considered the use of deception in this case and judged that the benefits of using it outweighed the risks and that there was no other way to answer the research question (about the effectiveness of a placebo procedure) without it. The surprising result was that all participants improved in terms of both knee pain and function, and the sham surgery group improved just as much as the treatment groups. According to the researchers, “This study provides strong evidence that arthroscopic lavage with or without débridement [the surgical procedures used] is not better than and appears to be equivalent to a placebo procedure in improving knee pain and self-reported function” (p. 85).

• Knecht, S., Dräger, B., Deppe, M., Bobe, L., Lohmann, H., Flöel, A., . . . Henningsen, H. (2000). Handedness and hemispheric language dominance in healthy humans. Brain: A Journal of Neurology, 123 (12), 2512-2518. http://dx.doi.org/10.1093/brain/123.12.2512 ↵
• Price, D. D., Finniss, D. G., & Benedetti, F. (2008). A comprehensive review of the placebo effect: Recent advances and current thought. Annual Review of Psychology, 59 , 565–590. ↵
• Shapiro, A. K., & Shapiro, E. (1999). The powerful placebo: From ancient priest to modern physician . Baltimore, MD: Johns Hopkins University Press. ↵
• Moseley, J. B., O’Malley, K., Petersen, N. J., Menke, T. J., Brody, B. A., Kuykendall, D. H., … Wray, N. P. (2002). A controlled trial of arthroscopic surgery for osteoarthritis of the knee. The New England Journal of Medicine, 347 , 81–88. ↵

A type of study designed specifically to answer the question of whether there is a causal relationship between two variables.

The variable the experimenter manipulates.

The variable the experimenter measures (it is the presumed effect).

The different levels of the independent variable to which participants are assigned.

Holding extraneous variables constant in order to separate the effect of the independent variable from the effect of the extraneous variables.

Any variable other than the dependent and independent variable.

Changing the level, or condition, of the independent variable systematically so that different groups of participants are exposed to different levels of that variable, or the same group of participants is exposed to different levels at different times.

An experiment design involving a single independent variable with two conditions.

When an experiment has one independent variable that is manipulated to produce more than two conditions.

An extraneous variable that varies systematically with the independent variable, and thus confuses the effect of the independent variable with the effect of the extraneous one.

Any intervention meant to change people’s behavior for the better.

The condition in which participants receive the treatment.

The condition in which participants do not receive the treatment.

An experiment that researches the effectiveness of psychotherapies and medical treatments.

The condition in which participants receive no treatment whatsoever.

A simulated treatment that lacks any active ingredient or element that is hypothesized to make the treatment effective, but is otherwise identical to the treatment.

An effect that is due to the placebo rather than the treatment.

Condition in which the participants receive a placebo rather than the treatment.

Condition in which participants are told that they will receive the treatment but must wait until the participants in the treatment condition have already received it.

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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experimental psychology

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• American Psychological Association - Understanding Experimental Psychology

experimental psychology , a method of studying psychological phenomena and processes. The experimental method in psychology attempts to account for the activities of animals (including humans) and the functional organization of mental processes by manipulating variables that may give rise to behaviour; it is primarily concerned with discovering laws that describe manipulable relationships. The term generally connotes all areas of psychology that use the experimental method.

These areas include the study of sensation and perception , learning and memory , motivation , and biological psychology . There are experimental branches in many other areas, however, including child psychology , clinical psychology , educational psychology , and social psychology . Usually the experimental psychologist deals with normal, intact organisms; in biological psychology, however, studies are often conducted with organisms modified by surgery, radiation, drug treatment, or long-standing deprivations of various kinds or with organisms that naturally present organic abnormalities or emotional disorders. See also psychophysics .

• Abnormal Psychology
• Assessment (IB)
• Biological Psychology
• Cognitive Psychology
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What is an “experiment?”

Travis Dixon October 7, 2017 Research Methodology

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If you’re reading this it’s probably because your teacher has assigned this as homework because you’ve called a study an “experiment” when it wasn’t an experiment at all. So this post is to help you know exactly when to use the term “experiment”, and when it’s safe just to say “study.”

But before we get to that, let’s first clarify why this is important knowledge. I think there are two reasons:

• If you use the term experiment incorrectly in an exam it will suggest to the examiner that you have limited knowledge – this will affect your marks.
• Research methods (and especially experiments) are the backbone of psychological research and so they’re a pretty important concept to understand.

Definition of experiment:

An experiment in psychology is when there is a study conducted that investigates the direct effect of an independent variable on a dependent variable. 

Tip:  If you’re not sure if it’s an experiment, you’re always safe to call it a “study.”

Before you can call a study an experiment, you have to identify the independent variable. Ask yourself:

• “Are there different groups in the study that the researchers are comparing?”

For example, in this study about serotonin’s effects on the brain we can see that there are two groups: drinking the placebo or the drink that reduces serotonin. So the IV is serotonin levels.

Experiments test  causal  relationships. 

If there are different groups and there is clearly an IV, you then need to ask yourself, “are the researchers studying the  effects  on a DV?”  In other words, is there a  causal  relationship between the IV and DV being examined?

If you look at the examples in the studies in this post , you’ll see that all of these studies are clearly investigating the effects of an IV on a DV:

• Serotonin study: the effects of serotonin levels (IV) on prefrontal cortex activity (DV)
• Rat experiment: the effects of testosterone (IV) on aggression (DV)
• Watching TV (Bandura): the effects of observing violence (IV) on aggression (DV).

So if the study is testing a causal relationship between an IV and a DV, you my friend, have got yourself an experiment 🙂

Laboratories are good places to conduct experiments because the conditions can be controlled so the IV can be isolated – this is essential when testing causal relationships.

So when is a study  not  an experiment?

A simple test would be to ask yourself:

• Did the researchers create the groups/conditions?

If they did, then you’ve got an experiment.

• Serotonin study: the researchers chose who drank which drink and when.
• Rat study: the researchers chose which rats to castrate and which ones not to.
• TV study: they told which kids to watch TV and which ones not to.

If the researchers didn’t create the groups you might be better to call it a “study” to be on the safe side.

In a true experiment it is the researchers who manipulate the independent variable (i.e. they create the groups/conditions in the experiment).

For example, in studies that compare cultures the researchers cannot create the groups because people are born into their existing cultures. These types of studies are most commonly correlational studies.

Another example is research on communication in relationships: the researchers compare the differences between couples with positive communication with those who have negative communication, but they didn’t create these groups – they occurred naturally. These are also correlational studies.

To conclude: if the researchers create the groups for comparison it’s an experiment. If not, you’re safer to call it a “study.”

Qualitative studies are  never  experiments, so be extra-careful when using this word in Paper 3.

But just to get tricky, there are some experiments where the independent variable is naturally occurring. These are called natural experiments (or quasi-experiments). So if you have a study with a naturally occurring variable, before you can call it an experiment you have to ask yourself:

• Are they testing a causal relationship between the IV and the DV?

But the problem is in order to answer this question you need to know quite a bit about the methodology. This is because you have to know if they’ve controlled for confounding variables in either their design or their statistical analyses. If they’ve tried to control confounding variables and isolate the IV as the only variable affecting the DV, you can call it an experiment.

But here we’re getting pretty complicated, which is why it might better to err on the side of caution with naturally occurring IVs and call them studies if you’re not sure if they’re experimental or not (another way to check is to ask your teacher).

What makes an experiment “quasi?” (Read More)

I hope this post helps. If you need anything clarified or you have questions about a specific study, please feel free to post it in the comments.

Travis Dixon is an IB Psychology teacher, author, workshop leader, examiner and IA moderator.

One type of research method in which the investigator manipulates one or more independent variables (IV) to determine the effect(s) on some behavior (the dependent variable) while controlling other relevant factors. There are two types of experiments, the true experiment and the quasi experiment. A true experiment occurs when the investigator does two things: 1) randomly assigns participants to groups (e.g., experimental and control); and 2) manipulates at least one IV. A quasi experiment is almost the same, except now there is no random assignment of participants to groups; only manipulation of the IV. In order to reach "cause and effect" conclusions about the effect of the IV on the DV, you must use a true experiment.

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Psychology Experiment: Psychology Definition, History & Examples

Psychology experiments are foundational to the empirical study of human behavior and mental processes. Rooted in rigorous scientific methodology, these experiments aim to test hypotheses and expand our understanding of psychological phenomena.

The history of psychological experimentation dates back to the late 19th century, with the establishment of the first psychological laboratory by Wilhelm Wundt in 1879, marking the formal genesis of psychology as a distinct scientific field. Over the years, seminal experiments such as the Pavlov’s conditioning , Milgram’s obedience study, and the Stanford Prison Experiment have significantly influenced the discipline .

This overview will elucidate the definition of psychology experiments, trace their historical development, and present examples that highlight their role in advancing psychological research, while also delineating key terms and referencing pivotal academic contributions.

Table of Contents

A psychology experiment is a research method where researchers manipulate variables to see how they affect people’s behavior or thoughts.

It helps scientists understand cause and effect relationships and uses statistical analysis to determine the significance of findings.

Psychology as a scientific discipline has its roots in the late 19th century when it emerged as a distinct field of study. The term ‘psychology’ originated from the Greek words ‘psyche’ meaning ‘soul’ or ‘mind’ and ‘logos’ meaning ‘study’ or ‘knowledge.’ It can be traced back to ancient civilizations such as ancient Egypt, Greece, China, and India, where philosophers and scholars contemplated the nature of the mind and human behavior.

However, the development of psychology as an empirical science began in the late 19th century. One of the key figures associated with its establishment was Wilhelm Wundt, a German psychologist who is often referred to as the ‘father of experimental psychology.’ In 1879, Wundt founded the first psychology laboratory at the University of Leipzig in Germany. This marked a significant turning point in the field, as it shifted from philosophical speculation to experimental inquiry.

Wundt’s laboratory focused on studying consciousness and the structure of the mind. He developed methodologies such as introspection, where participants were asked to reflect on their own conscious experiences and describe their thoughts and sensations. Wundt also conducted reaction time experiments to understand the time it takes for individuals to respond to certain stimuli. These experimental protocols laid the foundation for future psychological research and shaped the direction of the field.

The early 20th century witnessed the diversification of psychology into different schools of thought, each with its own set of theories and methodologies. One notable school was behaviorism , led by figures such as John B. Watson and B.F. Skinner. Behaviorists believed that behavior could be understood and predicted by studying observable stimuli and responses. They conducted experiments using animals and humans to examine the effects of rewards and punishments on behavior.

Another influential school was cognitivism, which gained prominence in the mid-20th century. Key figures in this movement included Ulric Neisser and Jean Piaget. Cognitivists focused on studying mental processes such as perception , memory , and problem-solving. They used experimental methods to investigate how individuals acquire, process, and store information.

Psychoanalysis, developed by Sigmund Freud, also made significant contributions to the field of psychology. Freud’s theories focused on the unconscious mind and the influence of early childhood experiences on behavior. Although psychoanalysis relied less on traditional experimental methods, it emphasized the importance of clinical observation and case studies.

Throughout its history, psychology has been shaped by significant events and studies that have contributed to its evolution. For example, the Stanford Prison Experiment conducted by Philip Zimbardo in 1971 shed light on the powerful influence of situational factors on human behavior. This study demonstrated the potential for individuals to adopt abusive roles and highlighted ethical concerns in psychological research.

Practical Examples of Psychology Terms in Real-Life Contexts:

• Confirmation Bias: Imagine you have a friend who strongly believes in conspiracy theories. Whenever they come across new information, they tend to selectively focus on evidence that supports their preexisting beliefs, while dismissing anything that contradicts them. This is an example of confirmation bias, where our tendency to seek out information that confirms our existing beliefs can influence our decision-making and perception of reality.
• Cognitive Dissonance: Picture a person who is trying to quit smoking. They know that smoking is harmful to their health , but they still find it difficult to give up the habit. This creates a state of cognitive dissonance, where there is a conflict between their knowledge of the negative effects of smoking and their desire to continue the behavior. They may try to resolve this dissonance by rationalizing their smoking or finding reasons to justify their actions.
• Halo Effect: Consider a job interview scenario. The interviewer meets a candidate who is well-dressed, confident, and articulate. Based on these initial positive impressions, the interviewer may unconsciously assume that the candidate possesses other desirable qualities, such as intelligence or competence. This is an example of the halo effect, where our overall positive impression of someone influences our perception of their specific traits or abilities.
• Learned Helplessness: Imagine a student who consistently receives negative feedback and criticism from their teacher, regardless of their effort or performance . Over time, the student may start to believe that their efforts are futile and that they have no control over their academic success. This learned helplessness can lead to a decrease in motivation and a belief that they are incapable of improving, even when opportunities for success arise.
• Self-fulfilling Prophecy: Think of a situation where a person believes they are bad at public speaking. Due to this belief, they may feel anxious and lack confidence when presenting in front of others. As a result, their performance may suffer, confirming their initial belief that they are indeed bad at public speaking. This is an example of a self-fulfilling prophecy, where our beliefs about ourselves or others can influence our behavior in a way that aligns with those beliefs, ultimately shaping the outcome.

Related Terms

Psychology’s rich lexicon includes terms that illuminate various aspects of human behavior and mental processes, each interwoven with the field’s history and practice. To fully grasp psychological experimentation, one must understand related terminology.

For example, in addition to the concept of a ‘variable’ denoting anything that can vary and potentially impact experimental outcomes, there are other closely linked terms such as ‘independent variable’ and ‘dependent variable .’

The independent variable is the factor that the researcher manipulates or controls in an experiment to observe its effect on the dependent variable. In contrast, the dependent variable is the outcome or behavior that is measured and is expected to change as a result of the manipulation of the independent variable. These two terms work together to establish cause-and-effect relationships in experimental research.

Furthermore, the ‘control group’ is another related term that complements the concept of a variable. While a variable can be any factor that can vary, a control group refers to participants who are not exposed to the experimental treatment. By comparing the outcomes of the control group to those of the experimental group, researchers can determine the effectiveness or impact of the independent variable.

Another important term closely associated with variables and control groups is ‘random assignment.’ This term refers to the process of randomly assigning participants to different experimental conditions. Random assignment ensures that each subject has an equal chance of being placed in any group, thus mitigating selection biases. It helps create groups that are comparable and reduces the likelihood that any pre-existing differences among participants will confound the results.

Lastly, ‘double-blind’ procedures are crucial in preserving the integrity of results by preventing expectancy effects. In a double-blind study, neither the participants nor the experimenters know who is receiving a particular treatment. This helps eliminate biases and unconscious influences that could affect the results. By keeping both parties unaware, the researchers can obtain more objective and reliable data.

Mastery of these terms, including variables, independent and dependent variables, control groups, random assignment, and double-blind procedures, is essential for methodical analysis within psychological research. Understanding their relationships and how they differ or complement each other is crucial for designing and interpreting experiments accurately.

Building upon the foundational terms outlined above, this section will provide a selection of key references that have contributed to the understanding and methodology of psychological experimentation. Notably, B.F. Skinner’s work on operant conditioning revolutionized behavioral psychology through empirical research, as documented in his seminal book, ‘The Behavior of Organisms’ (Skinner, 1938). Skinner’s research demonstrated the principles of reinforcement and punishment, which have had a profound impact on the field of psychology.

Another influential study in the field of psychology is the ‘Stanford prison experiment’ conducted by Zimbardo (1971). This study explored the effects of perceived power and social roles on behavior within a simulated prison environment . The ethical considerations raised by this experiment have since helped shape the guidelines for conducting psychological research involving human participants.

In the realm of cognitive psychology, Miller’s publication ‘The Magical Number Seven, Plus or Minus Two’ (Miller, 1956) provided valuable insights into the limitations of human memory. The study demonstrated that the average person’s short-term memory has a limited capacity, with an optimal range of around seven items. This research has influenced subsequent studies on memory and cognition .

These references, along with many others, have played significant roles in advancing the field of psychology. They are academically credible sources that provide a foundation for further reading and understanding of the term being discussed.

References:

Skinner, B. F. (1938). The Behavior of Organisms. Appleton-Century-Crofts.

Zimbardo, P. G. (1971). The Stanford prison experiment. Stanford University.

Miller, G. A. (1956). The Magical Number Seven, Plus or Minus Two. Psychological Review, 63(2), 81-97.

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Experimental Psychology Studies Humans and Animals

Understanding Experimental Psychology

Our personalities, and to some degree our life experiences, are defined by the way we behave. But what influences the way we behave in the first place? How does our behavior shape our experiences throughout our lives? 

Experimental psychologists are interested in exploring theoretical questions, often by creating a hypothesis and then setting out to prove or disprove it through experimentation. They study a wide range of behavioral topics among humans and animals, including sensation, perception, attention, memory, cognition and emotion.

Experimental Psychology Applied

Experimental psychologists use scientific methods to collect data and perform research. Often, their work builds, one study at a time, to a larger finding or conclusion. Some researchers have devoted their entire career to answering one complex research question. 

These psychologists work in a variety of settings, including universities, research centers, government agencies and private businesses. The focus of their research is as varied as the settings in which they work. Often, personal interest and educational background will influence the research questions they choose to explore. 

In a sense, all psychologists can be considered experimental psychologists since research is the foundation of the discipline, and many psychologists split their professional focus among research, patient care, teaching or program administration. Experimental psychologists, however, often devote their full attention to research — its design, execution, analysis and dissemination. 

Those focusing their careers specifically on experimental psychology contribute work across subfields . For example, they use scientific research to provide insights that improve teaching and learning, create safer workplaces and transportation systems, improve substance abuse treatment programs and promote healthy child development.

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Types of Variables in Psychology Research

Examples of Independent and Dependent Variables

Dependent and Independent Variables

• Intervening Variables
• Extraneous Variables
• Controlled Variables
• Confounding Variables
• Operationalizing Variables

Frequently Asked Questions

Variables in psychology are things that can be changed or altered, such as a characteristic or value. Variables are generally used in psychology experiments to determine if changes to one thing result in changes to another.

Variables in psychology play a critical role in the research process. By systematically changing some variables in an experiment and measuring what happens as a result, researchers are able to learn more about cause-and-effect relationships.

The two main types of variables in psychology are the independent variable and the dependent variable. Both variables are important in the process of collecting data about psychological phenomena.

This article discusses different types of variables that are used in psychology research. It also covers how to operationalize these variables when conducting experiments.

Students often report problems with identifying the independent and dependent variables in an experiment. While this task can become more difficult as the complexity of an experiment increases, in a psychology experiment:

• The independent variable is the variable that is manipulated by the experimenter. An example of an independent variable in psychology: In an experiment on the impact of sleep deprivation on test performance, sleep deprivation would be the independent variable. The experimenters would have some of the study participants be sleep-deprived while others would be fully rested.
• The dependent variable is the variable that is measured by the experimenter. In the previous example, the scores on the test performance measure would be the dependent variable.

So how do you differentiate between the independent and dependent variables? Start by asking yourself what the experimenter is manipulating. The things that change, either naturally or through direct manipulation from the experimenter, are generally the independent variables. What is being measured? The dependent variable is the one that the experimenter is measuring.

Intervening Variables in Psychology

Intervening variables, also sometimes called intermediate or mediator variables, are factors that play a role in the relationship between two other variables. In the previous example, sleep problems in university students are often influenced by factors such as stress. As a result, stress might be an intervening variable that plays a role in how much sleep people get, which may then influence how well they perform on exams.

Extraneous Variables in Psychology

Independent and dependent variables are not the only variables present in many experiments. In some cases, extraneous variables may also play a role. This type of variable is one that may have an impact on the relationship between the independent and dependent variables.

For example, in our previous example of an experiment on the effects of sleep deprivation on test performance, other factors such as age, gender, and academic background may have an impact on the results. In such cases, the experimenter will note the values of these extraneous variables so any impact can be controlled for.

There are two basic types of extraneous variables:

• Participant variables : These extraneous variables are related to the individual characteristics of each study participant that may impact how they respond. These factors can include background differences, mood, anxiety, intelligence, awareness, and other characteristics that are unique to each person.
• Situational variables : These extraneous variables are related to things in the environment that may impact how each participant responds. For example, if a participant is taking a test in a chilly room, the temperature would be considered an extraneous variable. Some participants may not be affected by the cold, but others might be distracted or annoyed by the temperature of the room.

Other extraneous variables include the following:

• Demand characteristics : Clues in the environment that suggest how a participant should behave
• Experimenter effects : When a researcher unintentionally suggests clues for how a participant should behave

Controlled Variables in Psychology

In many cases, extraneous variables are controlled for by the experimenter. A controlled variable is one that is held constant throughout an experiment.

In the case of participant variables, the experiment might select participants that are the same in background and temperament to ensure that these factors don't interfere with the results. Holding these variables constant is important for an experiment because it allows researchers to be sure that all other variables remain the same across all conditions.  

Using controlled variables means that when changes occur, the researchers can be sure that these changes are due to the manipulation of the independent variable and not caused by changes in other variables.

It is important to also note that a controlled variable is not the same thing as a control group . The control group in a study is the group of participants who do not receive the treatment or change in the independent variable.

All other variables between the control group and experimental group are held constant (i.e., they are controlled). The dependent variable being measured is then compared between the control group and experimental group to see what changes occurred because of the treatment.

Confounding Variables in Psychology

If a variable cannot be controlled for, it becomes what is known as a confounding variabl e. This type of variable can have an impact on the dependent variable, which can make it difficult to determine if the results are due to the influence of the independent variable, the confounding variable, or an interaction of the two.

Operationalizing Variables in Psychology

An operational definition describes how the variables are measured and defined in the study. Before conducting a psychology experiment , it is essential to create firm operational definitions for both the independent variable and dependent variables.

For example, in our imaginary experiment on the effects of sleep deprivation on test performance, we would need to create very specific operational definitions for our two variables. If our hypothesis is "Students who are sleep deprived will score significantly lower on a test," then we would have a few different concepts to define:

• Students : First, what do we mean by "students?" In our example, let’s define students as participants enrolled in an introductory university-level psychology course.
• Sleep deprivation : Next, we need to operationally define the "sleep deprivation" variable. In our example, let’s say that sleep deprivation refers to those participants who have had less than five hours of sleep the night before the test.
• Test variable : Finally, we need to create an operational definition for the test variable. For this example, the test variable will be defined as a student’s score on a chapter exam in the introductory psychology course.

Once all the variables are operationalized, we're ready to conduct the experiment.

Variables play an important part in psychology research. Manipulating an independent variable and measuring the dependent variable allows researchers to determine if there is a cause-and-effect relationship between them.

A Word From Verywell

Understanding the different types of variables used in psychology research is important if you want to conduct your own psychology experiments. It is also helpful for people who want to better understand what the results of psychology research really mean and become more informed consumers of psychology information .

Independent and dependent variables are used in experimental research. Unlike some other types of research (such as correlational studies ), experiments allow researchers to evaluate cause-and-effect relationships between two variables.

Researchers can use statistical analyses to determine the strength of a relationship between two variables in an experiment. Two of the most common ways to do this are to calculate a p-value or a correlation. The p-value indicates if the results are statistically significant while the correlation can indicate the strength of the relationship.

In an experiment on how sugar affects short-term memory, sugar intake would be the independent variable and scores on a short-term memory task would be the independent variable.

In an experiment looking at how caffeine intake affects test anxiety, the amount of caffeine consumed before a test would be the independent variable and scores on a test anxiety assessment would be the dependent variable.

Just as with other types of research, the independent variable in a cognitive psychology study would be the variable that the researchers manipulate. The specific independent variable would vary depending on the specific study, but it might be focused on some aspect of thinking, memory, attention, language, or decision-making.

American Psychological Association. Operational definition . APA Dictionary of Psychology.

American Psychological Association. Mediator . APA Dictionary of Psychology.

Altun I, Cınar N, Dede C. The contributing factors to poor sleep experiences in according to the university students: A cross-sectional study .  J Res Med Sci . 2012;17(6):557-561. PMID:23626634

Skelly AC, Dettori JR, Brodt ED. Assessing bias: The importance of considering confounding .  Evid Based Spine Care J . 2012;3(1):9-12. doi:10.1055/s-0031-1298595

• Evans, AN & Rooney, BJ. Methods in Psychological Research. Thousand Oaks, CA: SAGE Publications; 2014.
• Kantowitz, BH, Roediger, HL, & Elmes, DG. Experimental Psychology. Stamfort, CT: Cengage Learning; 2015.

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