Name: experimental and control groups
Uploaded: 2020-02-12T11:07:39.000Z
Duration: 2 min 1 s
Channel: JoVE

K12 Standards

Virginia  Standards of Learning

HIgh School

Biology

BIO.1

BIO.1.b

Group Design

When deciding how to structure a study that involves groups of people, researchers typically choose between two experimental designs: between-groups and repeated-measures or within-subjects.

Perhaps a researcher wants to compare how much readers empathize with the protagonist in a story&mdash;the dependent variable&mdash;when they read text that contains more emotional language versus more descriptive wording&mdash;the two levels of the independent variable.

She may decide to use a between-groups design&mdash;randomly assigning different individuals to each condition: the emotional language and descriptive language groups. As a result, each participant will only take part in one condition.

With random assignment, any potential confounds, such as how much people normally empathize with characters while reading, should be more equally distributed across both groups.

Alternatively, the researcher may decide to carry out the same study using a repeated-measures design&mdash;assigning the same participants to every level of the experimental conditions. Here, after taking part in one condition, each participant will also complete the second condition.

In this repeated-measures, or within-subjects design, potential co

group design

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference&mdash; experimental manipulation. The experimental group gets the experimental manipulation&mdash;that is, the treatment or variable being tested&mdash;and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

In an&nbsp;example of how violent television programming might affect violent behavior in children, we have the experimental group view violent television programming for a specified time and then measure their violent behavior. We measure the violent behavior in our control group after they watch nonviolent television programming for the same amount of time. It is important for the control group to be treated similarly to the experimental group, with the exception that the control group does not receive the experimental manipulation. Therefore, we have the control group watch non-violent television programming for the same amount of time as the experimental group.

We also need to precisely define, or operationalize, what is considered violent and nonviolent. An operational definition is a description of how we will measure our variables, and it is important in allowing others understand exactly how and what a researcher measures in a particular experiment. In operationalizing violent behavior, we might choose to count only physical acts like kicking or punching as instances of this behavior, or we also may choose to include angry verbal exchanges. Whatever we determine, it is important that we operationalize violent behavior in such a way that anyone who hears about our study for the first time knows exactly what we mean by violence. This aids peoples&rsquo; ability to interpret our data as well as their capacity to repeat our experiment should they choose to do so.

Once we have operationalized what is considered violent television programming and what is considered violent behavior from our experiment participants, we need to establish how we will run our experiment. In this case, we might have participants watch a 30-minute television program (either violent or nonviolent, depending on their group membership) before sending them out to a playground for an hour where their behavior is observed and the number and type of violent acts is recorded.

Independent and Dependent Variables 

In a research experiment, we strive to study whether changes in one thing cause changes in another. To achieve this, we must pay attention to two important variables, or things that can be changed, in any experimental study: the independent variable and the dependent variable. An independent variable is manipulated or controlled by the experimenter. In a well-designed experimental study, the independent variable is the only important difference between the experimental and control groups. In the example of how violent television programs affect children&rsquo;s display of violent behavior, the independent variable is the type of program&mdash;violent or nonviolent&mdash;viewed by participants in the study.

A dependent variable is what the researcher measures to see how much effect the independent variable had. In our example, the dependent variable is the number of violent acts displayed by the experimental participants.

We expect that the dependent variable will change as a function of the independent variable. In other words, the dependent variable depends on the independent variable. A good way to think about the relationship between the independent and dependent variables is with this question: What effect does the independent variable have on the dependent variable? Returning to our example, what effect does watching a half hour of violent television programming or nonviolent television programming have on the number of incidents of physical aggression displayed on the playground?

Selecting and Assigning Experimental Participants 

Once the study is designed, we need to obtain a sample of individuals to include in our experiment. Our study involves human participants so we need to determine who to include. Participants are the subjects of psychological research, and as the name implies, individuals who are involved in psychological research actively participate in the process. Often, psychological research projects rely on college students to serve as participants. In fact, the vast majority of research in psychology subfields has historically involved students as research participants (Sears, 1986; Arnett, 2008). But are college students truly representative of the general population? College students tend to be younger, more educated, more liberal, and less diverse than the general population. Although using students as test subjects is an accepted practice, relying on such a limited pool of research participants can be problematic because it is difficult to generalize findings to the larger population.

The hypothetical experiment involves children, and we must first generate a sample of child participants. Samples are used because populations are usually too large to reasonably involve every member in our particular experiment. If possible, we should use a random sample. A random sample is a subset of a larger population in which every member of the population has an equal chance of being selected. Random samples are preferred because if the sample is large enough we can be reasonably sure that the participating individuals are representative of the larger population. This means that the percentages of characteristics in the sample&mdash;sex, ethnicity, socioeconomic level, and any other characteristics that might affect the results&mdash;are close to those percentages in the larger population.

In the example given, let&rsquo;s say we decide our population of interest is fourth graders. But all fourth graders is a very large population, so we need to be more specific; instead we might say our population of interest is all fourth graders in a particular city. We should include students from various income brackets, family situations, races, ethnicities, religions, and geographic areas of town. With this more manageable population, we can work with the local schools in selecting a random sample of around 200 fourth graders who we want to participate in our experiment.

In summary, because we cannot test all of the fourth graders in a city, we want to find a group of about 200 that reflects the composition of that city. With a representative group, we can generalize our findings to the larger population without fear of our sample being biased in some way.

The next step of the experimental process is to split the participants into experimental and control groups through random assignment. With random assignment, all participants have an equal chance of being assigned to either group. There is statistical software that will randomly assign each of the fourth graders in the sample to either the experimental or the control group.

Random assignment is critical for sound experimental design. With sufficiently large samples, random assignment makes it unlikely that there are systematic differences between the groups. So, for instance, it would be very unlikely that we would get one group composed entirely of males, a given ethnic identity, or a given religious ideology. This is important because if the groups were systematically different before the experiment began, we would not know the origin of any differences we find between the groups: Were the differences preexisting, or were they caused by manipulation of the independent variable? Random assignment allows us to assume that any differences observed between experimental and control groups result from the manipulation of the independent variable.

Confounding Variables

Random assignment is also critical to equally distribute potential confounds&mdash;unknown factors that could contribute to the observed results. Researchers don&#39;t know everything, so there&#39;s always a possbility that additional and unanticpated variables are responsible for an&nbsp;outcome. With proper research design, researchers can at least control for confounds and avoid making incorrect conclusions.&nbsp;&nbsp;&nbsp;&nbsp;

&nbsp;

This text is adapted from <a href="https://cnx.org/contents/Sr8Ev5Og@10.24:mfArybye@16/2-3-Analyzing-Findings" target="_blank">OpenStax, Psychology. OpenStax CNX.</a>

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except ...

Education

JoVE Core

Social Psychology

Foundations of Social Psychology

Research Methods

KEY TERMS AND CONCEPTS

experimental and control groups

Experimental and control groups are the two parts of a basic experiment. The groups should be the same except for one difference: the experimental manipulation. The experimental group gets the treatment or variable being tested, and the control group does not. Because that is the only planned difference, researchers can link any change between the groups to the manipulation rather than to chance.

A clear example is a study on violent television and children’s behavior. In that setup, the experimental group watches violent television for a set time, and the control group watches nonviolent television for the same amount of time. Both groups should be treated the same way except for the program they view. That control helps make the comparison fair.

Researchers also need operational definitions. An operational definition explains exactly how a variable will be measured. For violent behavior, a study might count only physical acts like kicking or punching, or it might also include angry verbal exchanges. Defining violent and nonviolent behavior this way helps other people understand the study and repeat it if needed.

The experiment also needs a clear procedure. In this example, participants might watch a 30-minute program and then go to a playground for an hour while their behavior is observed. The number and type of violent acts would be recorded. This gives the researcher a direct way to compare the two groups.

Experiments also use independent and dependent variables. The independent variable is the factor the experimenter changes or controls. In the television example, it is the type of program, violent or nonviolent. The dependent variable is what the researcher measures, such as the number of violent acts shown by the children. Researchers ask what effect the independent variable has on the dependent variable.

To run the study, researchers first need participants. Participants are the human subjects who take part in psychological research. Studies often use college students, but that group may not represent the general population well because it tends to be younger, more educated, more liberal, and less diverse. That can make it harder to generalize the findings.

If the experiment is about children, the researcher needs a sample of child participants. A sample is used because the full population is usually too large to test. A random sample gives every member of the population an equal chance of being chosen. In the example, the population might be all fourth graders in one city, and the sample might include about 200 students from different income levels, family situations, races, ethnicities, religions, and parts of town.

After selecting the sample, researchers use random assignment. This means every participant has an equal chance of ending up in either the experimental group or the control group. With a large enough sample, random assignment helps prevent major preexisting differences between the groups. That way, if the groups differ after the experiment, the change is more likely to come from the independent variable.

Random assignment also helps spread out confounding variables. Confounds are unknown factors that could affect the results. Researchers cannot know every possible influence, so good design helps control for them and reduces the risk of drawing the wrong conclusion.

Experimental and Control Groups

the scientific method

Research Questions and Falsifiable Hypotheses

Research questions and falsifiable hypotheses help scientists separate facts from opinions. Facts are observable realities. Opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In science, facts are established with evidence from empirical research, which means research based on observation and experience. Scientific knowledge grows through the scientific method, a process that connects ideas with real-world evidence. Researchers test theories and...

case studies

Studying Rare Cases in Psychology

Case studies help psychologists study rare people or rare situations in detail. This research method is used in observational research when scientists focus on one person or just a few individuals. Because the group is so small, researchers can collect very rich information and gain a deep understanding of the case. A well-known example is the New York Times story about Krista and Tatiana Hogan, Canadian twin girls who are conjoined at the head. Scientists have evidence that the twins may be...

naturalistic observations

Watching Behavior in Real Settings

Naturalistic observation is a research method for watching behavior in its real setting. Researchers try to record what people or animals do without changing the situation. The goal is to see behavior as naturally as possible. People often act differently when they know they are being watched. That is why observers must be inconspicuous, or hard to notice. In a classroom hand-washing example, a student observer might stand at a sink and pretend to put in contact lenses while secretly recording...

surveys

Survey Data in Psychology

Survey data in psychology comes from sets of questions answered by research participants. Surveys can be given on paper, online, or by speaking with people directly. They are usually quick to complete, which makes them useful when researchers want information from many people. A survey helps researchers study a sample, which is a smaller group chosen from a population, the larger group they want to understand. Because surveys can reach larger and more diverse samples, the results may reflect...

archival research

Using Records to Study Behavior

Archival research uses existing records and data sets to study behavior and answer research questions. Researchers do not collect new data from participants in this method. Instead, they look back at records that already exist to find patterns and relationships. A researcher might, for example, examine the academic records of students who enrolled in college over the past ten years. Those records could show how long students took to finish their degrees, along with course loads, grades, and...

longitudinal research

Tracking the Same People Over Time

Longitudinal research tracks the same group of people over time. Researchers use this design when they want to study change in human development or across the lifespan. Data are collected from the same participants repeatedly over an extended period. A simple example is a survey on dietary habits. The same people might answer at age 20, again at age 30, and again at age 40. This repeated testing helps researchers see how responses change over the years. Longitudinal research can also help...

cross-sectional research

Studying Age Groups at One Point in Time

Cross-sectional research compares different groups of people at the same time. Researchers use it when they want to study how a trait or behavior varies across age groups or other segments of the population. For example, a researcher interested in dietary habits could compare 20-year-old, 30-year-old, and 40-year-old individuals in one study. This approach does not require waiting 20 years to track how one group changes from decade to decade. It is a shorter-term way to collect data. <br...

Experimental and control groups are the two parts of a basic experiment. The groups should be the same except for one difference: the experimental manipulation. The experimental group gets the treatment or variable being tested, and the control group does not. Because that is the only planned difference, researchers can link any change between the groups to the manipulation rather than to chance. A clear example is a study on violent television and children’s behavior. In that setup, the...

factorial design

Factorial Analysis in ANOVA

Factorial analysis is a research design that uses ANOVA, or analysis of variance, to test how more than one independent variable affects a dependent variable. The independent variables are also called factors. A worker productivity study can show how salary and skill level may each influence the result. In this example, salary can be grouped into three levels: low, moderate, and high. Skill level can be grouped into two levels: entry level and experienced. The study would be called a two-way...

the placebo effect

How Expectations Shape Placebo Results

The placebo effect shows how expectations and beliefs can shape what people experience. In some situations, simply expecting something to happen can make it feel real. This effect is often discussed when scientists test a new medicine. A common example is a study on depression treatment. A pharmaceutical company may compare two groups. The experimental group receives the medication, and the control group does not. To keep participants from knowing which treatment they got, researchers may give...

blind procedures

Single-Blind and Double-Blind Studies

Single-blind and double-blind studies help researchers reduce bias in an experiment. Bias can happen when expectations affect how a study is carried out or how results are read. In this kind of research, blinding keeps those expectations from shaping the outcome. In a single-blind study, the participants do not know whether they are in the experimental group or the control group. The researcher who designed the study still knows who is in each group. This setup helps limit the effect of...

ethics in research

Research Oversight for Human and Animal Studies

Research oversight protects human dignity and safety in modern science. Good research must be ethical, and researchers must show that their studies meet that standard. This idea is especially important when studies involve people or animals. Studies with human participants follow strict rules to prevent harm. Research institutions that receive federal support for human studies must have access to an institutional review board, or IRB. An IRB is a committee made up of administrators,...

correlations

Reading Correlation Coefficients

Correlation describes a relationship between two or more variables. It does not automatically mean that one variable causes the other. When variables are correlated, one changes as the other changes, and that relationship can be measured with a correlation coefficient. A correlation coefficient is a number from -1 to +1. It is usually written as r. The number shows the strength of the relationship. Values closer to 1, whether positive or negative, show a stronger relationship and make changes...

cause and effect

Why Correlation Can Mislead

Correlation can be misleading when two variables move together for a different reason. A confounding variable, or hidden factor, may be causing the pattern instead of one variable directly affecting the other. The ice cream and crime example shows this clearly. When temperatures rise, more people go outside, buy ice cream, and may also have more chances for conflict. A correlation does not prove causation. Even when a relationship looks strong, we should not assume that one variable causes the...

reliability and validity

Testing Measurement Quality in Research

Reliable and valid measurements are essential in data collection and research. Reliability means a tool or test gives the same result in a consistent way. In psychology, that means the instruments used to collect data should produce reproducible results. Consistency alone is not enough. A kitchen scale can show the same reading every time, but it can still be wrong if it is not calibrated correctly. In that case, the scale is reliable because it is consistent, but it does not measure the...

regression toward the mean

Regression Toward the Mean in Data

Regression toward the mean is a statistical pattern in which very high or very low values move closer to the average when they are measured again. A blood pressure reading taken at one moment is one example. The change is usually caused by random error and chance, not by a real underlying shift. This idea matters because it can affect many kinds of research. If scientists do not account for regression toward the mean, they may think a treatment worked when the difference was really just a...

measures of central tendency

Mean, Median, and Mode in Data

Mean, median, and mode are the main ways to describe the center of a data set. The center is also a way to describe location. The mean and the median are the two most widely used measures of center. The mean is the arithmetic mean, which most people call the average. In everyday use, average and mean are often used to mean the same thing. The mode is another measure of center. It is the value that appears most often in a data set. If two values occur the same number of times, the data set is...

variation: normal distribution, range, and standard deviation

variation-normal-distribution-range-and-standard-deviation

Measuring Data Spread with Range and Variance

Variation describes how far scores are from each other in a data set. In psychology, researchers organize measurements of traits, features, or characteristics, called variables, in different ways. Qualitative data, such as ethnicity, can be counted to show the proportion and variety of groups in a sample or population. Quantitative data allow for more calculations, including measures of central tendency and variability. The mean, mode, and median are central tendency measures. They identify a...

statistical significance

Testing Whether Group Differences Matter

Statistical analysis helps determine whether differences between an experimental group and a control group are meaningful. After data are collected, researchers check whether the results are likely to be real or just due to chance. If a difference is caused by chance, it is not considered meaningful. In psychology, a group difference is usually called significant when the chance of it happening by accident is 5 percent or less. Another way to say this is that if the experiment were repeated...

key terms and concepts

Learn how experimental and control groups, operational definitions, variables, random sampling, and random assignment work in a basic experiment.

Experimental and Control Groups | JoVE K12

JoVE Core Social Psychology offers a comprehensive learning experience on the principles of social behavior through concise, animated video lessons. The series explores key topics such as self-concept, social cognition, group dynamics, stereotypes, and relationships. It provides a structured foundation for understanding human behavior in social situations. Students gain insights into how individuals think, feel, and behave in social contexts while examining the psychological processes that influence interactions and judgments. By integrating theory with real-world applications, these lessons offer a clear and engaging approach to mastering essential concepts in social psychology.

social psychology

Chemistry

CH.1

CH.1.b

Texas Essential Knowledge and Skills

High School

CHEM.4

CHEM.4.B

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• ask questions that arise from careful observation of phenomena and/or
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BIO.1.c

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BIO.1.f

Experimental and Control Groups

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