Control Group vs. Experimental Group
What's the difference.
Control group and experimental group are two essential components of a scientific experiment. The control group serves as a baseline for comparison, as it does not receive any treatment or intervention. It helps researchers determine the natural or expected outcome of the experiment. On the other hand, the experimental group is exposed to the independent variable or the treatment being tested. By comparing the results of the control group with the experimental group, researchers can assess the effectiveness or impact of the treatment. The control group provides a reference point, while the experimental group allows for the evaluation of the specific variable being studied.
Further Detail
Introduction.
In scientific research, control groups and experimental groups play crucial roles in understanding the effects of variables and determining causality. These groups are essential in conducting experiments and studies to gather reliable data and draw meaningful conclusions. While both groups serve distinct purposes, they possess different attributes that set them apart. In this article, we will explore and compare the attributes of control groups and experimental groups, shedding light on their significance in research.
Control Group
A control group is a group of individuals or subjects in an experiment that does not receive the experimental treatment or intervention. It serves as a baseline against which the experimental group is compared. The primary purpose of a control group is to provide a reference point to measure the effects of the independent variable in the experimental group. By keeping all other variables constant, except for the one being tested, researchers can determine whether the observed changes are due to the intervention or other factors.
One attribute of a control group is that it is randomly selected or assigned. Randomization helps ensure that the control group represents the larger population accurately, reducing the potential for bias. Additionally, the control group should be similar to the experimental group in terms of relevant characteristics such as age, gender, and health status. This similarity allows for a more accurate comparison between the two groups.
Another attribute of a control group is that it receives a placebo or a standard treatment. Placebos are inert substances or procedures that mimic the experimental treatment but have no therapeutic effect. By providing a placebo to the control group, researchers can account for the placebo effect, where individuals may experience improvements simply due to their belief in receiving treatment. Alternatively, the control group may receive a standard treatment that is already established as effective, allowing researchers to compare the experimental treatment against an existing standard.
Control groups are also characterized by their size. The larger the control group, the more reliable the results are likely to be. A larger sample size helps reduce the impact of individual variations and increases the statistical power of the study. It allows for more accurate generalizations and strengthens the validity of the findings.
Lastly, control groups are typically subjected to the same conditions as the experimental group, except for the intervention being tested. This ensures that any observed differences between the two groups can be attributed to the independent variable and not external factors. By controlling the environment and other variables, researchers can isolate the effects of the intervention and draw more accurate conclusions.
Experimental Group
The experimental group, also known as the treatment group, is the group of individuals or subjects in an experiment that receives the experimental treatment or intervention being tested. Unlike the control group, the experimental group is exposed to the independent variable, allowing researchers to assess the effects of the intervention.
One attribute of the experimental group is that it is carefully selected or assigned. Researchers must ensure that the individuals in the experimental group meet specific criteria and are representative of the population being studied. This selection process helps increase the internal validity of the study and enhances the generalizability of the findings.
Another attribute of the experimental group is that it undergoes the experimental treatment or intervention. This treatment can be a new drug, therapy, educational program, or any other intervention being tested. By administering the intervention to the experimental group, researchers can observe and measure its effects, comparing them to the control group's outcomes.
The size of the experimental group is also an important attribute. Similar to the control group, a larger sample size in the experimental group increases the reliability and statistical power of the study. It allows for more accurate assessments of the intervention's effectiveness and helps identify any potential side effects or adverse reactions.
Experimental groups are often subjected to pre and post-tests to measure the changes resulting from the intervention. These tests can include surveys, physical examinations, cognitive assessments, or any other relevant measurements. By comparing the pre and post-intervention results, researchers can determine the impact of the intervention on the dependent variable.
Lastly, experimental groups may be divided into subgroups to explore different variables or conditions. This approach allows researchers to assess the effects of the intervention across various demographics, such as age groups or different levels of severity. By analyzing subgroups within the experimental group, researchers can gain a deeper understanding of how the intervention affects different populations.
Control groups and experimental groups are fundamental components of scientific research. While control groups provide a reference point and help establish causality, experimental groups allow researchers to assess the effects of interventions. Both groups possess distinct attributes that contribute to the validity and reliability of the study. By understanding and comparing the attributes of control groups and experimental groups, researchers can conduct rigorous experiments and generate meaningful insights that advance scientific knowledge.
Comparisons may contain inaccurate information about people, places, or facts. Please report any issues.
Controlled Experiment
Saul McLeod, PhD
Editor-in-Chief for Simply Psychology
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
Learn about our Editorial Process
Olivia Guy-Evans, MSc
Associate Editor for Simply Psychology
BSc (Hons) Psychology, MSc Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
This is when a hypothesis is scientifically tested.
In a controlled experiment, an independent variable (the cause) is systematically manipulated, and the dependent variable (the effect) is measured; any extraneous variables are controlled.
The researcher can operationalize (i.e., define) the studied variables so they can be objectively measured. The quantitative data can be analyzed to see if there is a difference between the experimental and control groups.
What is the control group?
In experiments scientists compare a control group and an experimental group that are identical in all respects, except for one difference – experimental manipulation.
Unlike the experimental group, the control group is not exposed to the independent variable under investigation and so provides a baseline against which any changes in the experimental group can be compared.
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.
Randomly allocating participants to independent variable groups means that all participants should have an equal chance of participating in each condition.
The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.
What are extraneous variables?
The researcher wants to ensure that the manipulation of the independent variable has changed the changes in the dependent variable.
Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.
Extraneous variables should be controlled were possible, as they might be important enough to provide alternative explanations for the effects.
In practice, it would be difficult to control all the variables in a child’s educational achievement. For example, it would be difficult to control variables that have happened in the past.
A researcher can only control the current environment of participants, such as time of day and noise levels.
Why conduct controlled experiments?
Scientists use controlled experiments because they allow for precise control of extraneous and independent variables. This allows a cause-and-effect relationship to be established.
Controlled experiments also follow a standardized step-by-step procedure. This makes it easy for another researcher to replicate the study.
Key Terminology
Experimental group.
The group being treated or otherwise manipulated for the sake of the experiment.
Control Group
They receive no treatment and are used as a comparison group.
Ecological validity
The degree to which an investigation represents real-life experiences.
Experimenter effects
These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.
Demand characteristics
The clues in an experiment lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).
Independent variable (IV)
The variable the experimenter manipulates (i.e., changes) – is assumed to have a direct effect on the dependent variable.
Dependent variable (DV)
Variable the experimenter measures. This is the outcome (i.e., the result) of a study.
Extraneous variables (EV)
All variables that are not independent variables but could affect the results (DV) of the experiment. Extraneous variables should be controlled where possible.
Confounding variables
Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.
Random Allocation
Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of participating in each condition.
Order effects
Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:
(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;
(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.
What is the control in an experiment?
In an experiment , the control is a standard or baseline group not exposed to the experimental treatment or manipulation. It serves as a comparison group to the experimental group, which does receive the treatment or manipulation.
The control group helps to account for other variables that might influence the outcome, allowing researchers to attribute differences in results more confidently to the experimental treatment.
Establishing a cause-and-effect relationship between the manipulated variable (independent variable) and the outcome (dependent variable) is critical in establishing a cause-and-effect relationship between the manipulated variable.
What is the purpose of controlling the environment when testing a hypothesis?
Controlling the environment when testing a hypothesis aims to eliminate or minimize the influence of extraneous variables. These variables other than the independent variable might affect the dependent variable, potentially confounding the results.
By controlling the environment, researchers can ensure that any observed changes in the dependent variable are likely due to the manipulation of the independent variable, not other factors.
This enhances the experiment’s validity, allowing for more accurate conclusions about cause-and-effect relationships.
It also improves the experiment’s replicability, meaning other researchers can repeat the experiment under the same conditions to verify the results.
Why are hypotheses important to controlled experiments?
Hypotheses are crucial to controlled experiments because they provide a clear focus and direction for the research. A hypothesis is a testable prediction about the relationship between variables.
It guides the design of the experiment, including what variables to manipulate (independent variables) and what outcomes to measure (dependent variables).
The experiment is then conducted to test the validity of the hypothesis. If the results align with the hypothesis, they provide evidence supporting it.
The hypothesis may be revised or rejected if the results do not align. Thus, hypotheses are central to the scientific method, driving the iterative inquiry, experimentation, and knowledge advancement process.
What is the experimental method?
The experimental method is a systematic approach in scientific research where an independent variable is manipulated to observe its effect on a dependent variable, under controlled conditions.
IMAGES
VIDEO