difference in control group and experimental group

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The Difference Between Control Group and Experimental Group

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In an experiment , data from an experimental group is compared with data from a control group. These two groups should be identical in every respect except one: the difference between a control group and an experimental group is that the independent variable is changed for the experimental group, but is held constant in the control group.

Key Takeaways: Control vs. Experimental Group

• The control group and experimental group are compared against each other in an experiment. The only difference between the two groups is that the independent variable is changed in the experimental group. The independent variable is "controlled", or held constant, in the control group.
• A single experiment may include multiple experimental groups, which may all be compared against the control group.
• The purpose of having a control is to rule out other factors which may influence the results of an experiment. Not all experiments include a control group, but those that do are called "controlled experiments."
• A placebo may also be used in an experiment. A placebo isn't a substitute for a control group because subjects exposed to a placebo may experience effects from the belief they are being tested; this itself is known as the placebo effect.

What Are Is an Experimental Group in Experiment Design?

An experimental group is a test sample or the group that receives an experimental procedure. This group is exposed to changes in the independent variable being tested. The values of the independent variable and the impact on the dependent variable are recorded. An experiment may include multiple experimental groups at one time.

A control group is a group separated from the rest of the experiment such that the independent variable being tested cannot influence the results. This isolates the independent variable's effects on the experiment and can help rule out alternative explanations of the experimental results.

While all experiments have an experimental group, not all experiments require a control group. Controls are extremely useful where the experimental conditions are complex and difficult to isolate. Experiments that use control groups are called controlled experiments .

A Simple Example of a Controlled Experiment

A simple example of a controlled experiment may be used to determine whether or not plants need to be watered to live. The control group would be plants that are not watered. The experimental group would consist of plants that receive water. A clever scientist would wonder whether too much watering might kill the plants and would set up several experimental groups, each receiving a different amount of water.

Sometimes setting up a controlled experiment can be confusing. For example, a scientist may wonder whether or not a species of bacteria needs oxygen in order to live. To test this, cultures of bacteria may be left in the air, while other cultures are placed in a sealed container of nitrogen (the most common component of air) or deoxygenated air (which likely contained extra carbon dioxide). Which container is the control? Which is the experimental group?

Control Groups and Placebos

The most common type of control group is one held at ordinary conditions so it doesn't experience a changing variable. For example, If you want to explore the effect of salt on plant growth, the control group would be a set of plants not exposed to salt, while the experimental group would receive the salt treatment. If you want to test whether the duration of light exposure affects fish reproduction, the control group would be exposed to a "normal" number of hours of light, while the duration would change for the experimental group.

Experiments involving human subjects can be much more complex. If you're testing whether a drug is effective or not, for example, members of a control group may expect they will not be unaffected. To prevent skewing the results, a placebo may be used. A placebo is a substance that doesn't contain an active therapeutic agent. If a control group takes a placebo, participants don't know whether they are being treated or not, so they have the same expectations as members of the experimental group.

However, there is also the placebo effect to consider. Here, the recipient of the placebo experiences an effect or improvement because she believes there should be an effect. Another concern with a placebo is that it's not always easy to formulate one that truly free of active ingredients. For example, if a sugar pill is given as a placebo, there's a chance the sugar will affect the outcome of the experiment.

Positive and Negative Controls

Positive and negative controls are two other types of control groups:

• Positive control groups are control groups in which the conditions guarantee a positive result. Positive control groups are effective to show the experiment is functioning as planned.
• Negative control groups are control groups in which conditions produce a negative outcome. Negative control groups help identify outside influences which may be present that were not unaccounted for, such as contaminants.
• Bailey, R. A. (2008). Design of Comparative Experiments . Cambridge University Press. ISBN 978-0-521-68357-9.
• Chaplin, S. (2006). "The placebo response: an important part of treatment". Prescriber : 16–22. doi: 10.1002/psb.344
• Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
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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.

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Control Group vs. Experimental Group: Everything You Need To Know About The Difference Between Control Group And Experimental Group

As someone who is deeply interested in the field of research, you may have heard the terms control group and experimental group thrown around a lot. If you’re not very familiar with these terms, it can be daunting to determine the role they play in research and why they are so important. In layman’s terms, a control group is a group that does not receive any experimental treatment and is used as a benchmark for the group that does receive the treatment. Meanwhile, the experimental group is a group that receives the treatment and is compared to the control group that does not receive the treatment. To put it simply, the main difference between a control group and an experimental group is whether or not they receive the experimental treatment.

Why is it important to understand the difference between these two groups? Well, when conducting research, it is essential to ensure that the results are reliable, unbiased and accurate. The use of a control group in an experiment can help researchers determine the effectiveness of the experiment by acting as a comparison.

Table of Contents

What Is Control Group?

A control group is a group in an experiment that does not receive the experimental treatment and is used as a comparison for the group that does receive the treatment. It is a critical aspect of experimental research to determine whether the treatment caused the outcome rather than another factor. The control group ensures that any observed effects can be attributed to the treatment and not a result of other variables. The quality of the control group can affect the validity of the experiment. Therefore, researchers must carefully design and select participants for the control group to ensure that it accurately represents the population and provides meaningful results. Overall, control groups are essential to gain accurate and reliable results in experimental research.

What Is Experimental Group?

An experimental group is a term used in experimental studies to refer to a group of participants who are exposed to a specific experimental treatment or intervention. This treatment is a variable that the researchers manipulate to measure the impact of the treatment on the dependent variable being studied. The experimental group is then compared against a control group, which is not exposed to the experimental treatment. The purpose of the control group is to provide a baseline for measuring the effects of the independent variable, thus ensuring that any observed changes in the dependent variable can be attributed to the experimental treatment. By using an experimental group, researchers can determine if the treatment has any significant effects, and if so, they can evaluate the efficacy of the treatment.

Key Differences Between Control Group And Experimental Group

Control group and experimental group are two important terms in conducting experiments. The control group refers to a group of subjects that do not receive the experimental treatment and is used as a comparison for the group that receives the treatment. In contrast, the experimental group is the group that receives the experimental treatment and is compared to a control group that does not receive the treatment. The key differences between control group and experimental group are that the control group serves as a baseline, while the experimental group allows researchers to evaluate the effects of an experimental intervention. Additionally, experimental results are more reliable and valid when compared to the control group, demonstrating the importance of incorporating both groups in experimental research.

• The control group serves as a baseline, while the experimental group allows researchers to evaluate the effects of an experimental intervention.
• The control group receives no treatment, while the experimental group receives treatment.
• The control group is exposed to the same conditions that the experimental group receives, while the experimental group is exposed to different conditions that the control group does not receive.

Control Group vs. Experimental Group Similarities

The control group and experimental group are two essential components of any research study. The main similarity between these groups is that they are both used to assess the effects of a treatment or intervention. The control group is intended to provide a baseline measurement of the outcomes that are expected in the absence of the intervention. In contrast, the experimental group is exposed to the intervention or treatment and is observed for any changes or improvements in outcomes. In summary, both groups serve as comparisons for one another, and their use increases the credibility and validity of research findings.

Control Group vs. Experimental Group Pros and Cons

Control group pros & cons.

Control Group Pros

A control group is an important element of scientific research that serves as a benchmark group for comparison with the experimental group. The primary advantage of a control group is that it aids in determining the cause and effect relationship between the independent variable and the dependent variable. It enables the researcher to isolate and measure the effect of the experimental treatment by holding all other variables constant. By having a control group, researchers can rule out the possibility of confounding variables that could influence the results of the study. Additionally, a control group provides a basis for making valid conclusions and assertions about the effect of the experimental treatment. This approach enhances scientific rigor and reliability, resulting in more accurate and trustworthy findings.

• The control group helps determine the causal relationship between the independent variable and the dependent variable. 
• The control group allows the researcher to isolate and measure the effect of the experimental treatment while all other variables are unchanged. 
• The control group provides a basis for valid inferences and claims about the effects of the experimental treatment.
• The control group allows for more accurate and reliable study results.

Control Group Cons

The use of a control group in experiments remains a standard practice in scientific research. However, despite its advantages, there are some disadvantages and cons of using a control group. First, the control group may present ethical concerns as it inherently denies some participants the opportunity to receive the experimental treatment. Second, the control group may not accurately represent the larger population being studied, leading to biased results. Third, the control group may experience changes due to factors other than the experimental treatment, leading to invalid results. Lastly, the use of a control group may increase the cost, time, and resources needed to conduct the experiment. Taking these disadvantages into consideration, researchers must carefully evaluate the use of a control group in their experimental design.

• The use of a control group may increase the cost, time, and resources needed to conduct the experiment.
• The control group may experience changes due to factors other than the experimental treatment, leading to invalid results.
• The control group may not accurately represent the larger population being studied, leading to biased results.
• The control group may present ethical concerns as it inherently denies some participants the opportunity to receive the experimental treatment.

Experimental Group Pros & Cons

Experimental Group Pros

The Experimental Group, in scientific studies and experimentation, is a group that receives the experimental treatment and is compared to a control group that does not receive the treatment. There are several advantages or pros of this group. First, the experimental group allows researchers to determine the effectiveness of a new treatment or procedure. Second, it helps in identifying side effects of the treatment on the subjects. Third, it provides clear evidence regarding the cause and effect relationships between variables. Additionally, the experimental group enables researchers to validate their findings and test the hypothesis. These benefits make the Experimental Group essential in accurately assessing the effectiveness of new treatments or procedures.

• The experimental group allows researchers to determine the effectiveness of a new treatment or procedure.
• The experimental group helps in identifying side effects of the treatment on the subjects.
• The experimental group provides clear evidence regarding the cause and effect relationships between variables.
• The experimental group enables researchers to validate their findings and test the hypothesis. 

Experimental Group Cons

Experimental groups are a critical component of scientific research as they allow researchers to test the efficacy of different treatments or interventions. However, along with their advantages, experimental groups also present some disadvantages and cons. Firstly, ethical considerations may arise as some experimental treatments may cause harm or discomfort to participants. It is also possible that the treatment may not have a significant effect, which would mean that resources and time are wasted. Finally, experimental groups can be affected by confounding variables, which may render results unreliable or inaccurate. Therefore, it is important to carefully consider the potential disadvantages and limitations when designing and conducting an experiment that involves an experimental group.

• The experimental groups can be affected by confounding variables, which may render results unreliable or inaccurate. 
• It is also possible that the treatment may not have a significant effect, which would mean that resources and time are wasted.
• Ethical considerations may arise as some experimental treatments may cause harm or discomfort to participants.

Comparison Table: 5 Key Differences Between Control Group And Experimental Group

Comparison chart.

Comparison Video

Conclusion: what is the difference between control group and experimental group.

In conclusion, understanding the difference between a control group and an experimental group is crucial in designing and conducting reliable experiments. The control group serves as a baseline, allowing researchers to compare the effects of the experimental treatment. Without a control group, it is difficult to determine whether any observed effects are due to the treatment or to other factors. By contrast, the experimental group receives the treatment and is used to evaluate the effects of the intervention. By carefully controlling for different factors, scientists can use these groups to test hypotheses and draw meaningful conclusions about the impact of different treatments on the outcomes of interest.

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Control Group vs. Experimental Group — What's the Difference?

Difference Between Control Group and Experimental Group

Table of contents, key differences, comparison chart, outcome measurement, significance, example use, outcome analysis, compare with definitions, control group, experimental group, common curiosities, why is a control group necessary, can an experiment have multiple experimental groups, how do researchers ensure the groups are comparable, what is an experimental group, what is a placebo, how is the effectiveness of the treatment measured, what is a double-blind study, why is randomization important in assigning groups, what is a control group, how are participants assigned to each group, what happens if there's no difference between the control and experimental groups, how do researchers deal with variables other than the treatment, can the control group receive a standard treatment instead of a placebo, what is the significance of the placebo effect, what ethical considerations are involved in using control groups, share your discovery.

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Difference Between Control And Experimental Group

Almost all experimental studies are designed to include a control group and one or more experimental groups, each serving a different purpose. In most cases, participants are randomly assigned to either a control or experimental group.

Experimental groups are usually manipulated to try and change the out come of the experiment. Control groups are usually kept as natural or unchanged to provide a normal outcome for comparison in the experiment. Read the article to learn more about the two.

Experimental Group

The experimental group, is the group of subjects or participants that receives the experimental treatment, intervention or condition being studied. In other words, it is a group of items, animals or people being tested, which have one variable or condition changed from the other groups in the experiment. The variable is usually stated in the hypothesis and is the main focus of the experiment.

Experimental group is exposed to changes in the independent variable being tested. The values of the independent variable and the impact on the dependent variable are recorded. An experiment may include multiple experimental groups at one time.

Researchers will compare the responses of the experimental group to those of a control group to see if the independent variable impacted the participants.

An experiment must have at least one control group and one experimental group; however, a single experiment can include multiple experimental groups, which are all compared against the control group.

Having multiple experimental groups enables researchers to vary different levels of an experimental variable and compare the effects of these changes to the control group and among each other.

An example of an experimental group would be if someone wanted to see if music helps people sleep longer. The experimental population could be divided into two groups. One group would track the length of time they sleep each night without music playing. The other group would track the length of time they sleep each night when listening to music. This group would be your experimental group because something has been changed in this group. Listening to music while they sleep. This group is being “experimented” on.

What you need to know about Control Group

• Members of the experimental group are exposed to the experimental treatment, which is the variable or condition that the study aims to test. This treatment could be a drug, therapy, educational program, or any other factor under investigation.
• To ensure fairness and minimize bias, subjects are often randomly assigned to either the experimental group or the control group. Randomization helps create comparable groups, ensuring that the results are not skewed by pre-existing differences between the participants.
• Experimental groups can also be single-blind or double-blind. In single-blind studies, participants do not know whether they are in the experimental or control group. In double-blind studies, both participants and researchers are unaware of group assignments to reduce bias.
• While the experimental group is exposed to the treatment, efforts are made to control or account for confounding variables—factors other than the treatment that could influence the results.
• In clinical trials, the experimental group receives the investigational drug or treatment, while the control group may receive a placebo or the current standard of care.

Control Group

A control group is a fundamental component of experimental research design, and its primary purpose is to serve as a baseline or reference group against which the experimental group is compared. In other words, it is is a collection of factors that remain constant throughout an experiment. 

The control group allows researchers to assess the natural course or behavior of the subjects in the absence of the experimental intervention. This baseline comparison helps determine whether any observed changes in the experimental group can be attributed to the treatment or are simply a result of the normal variation or other factors.

While all experiments have an experimental group, not all experiments require a control group. Controls are extremely useful where the experimental conditions are complex and difficult to isolate. Experiments that use control groups are called controlled experiments.

Unlike the experimental group, the control group is not exposed to the independent variable under investigation. So, it provides a baseline against which any changes in the experimental group can be compared.

In comparative experiments, members of a control group receive a standard treatment, a placebo, or no treatment at all. There may be more than one treatment group, more than one control group, or both.

A simple example of a controlled experiment may be used to determine whether or not plants need to be watered to live. The control group would be plants that are not watered. The experimental group would consist of plants that receive water. A clever scientist would wonder whether too much watering might kill the plants and would set up several experimental groups, each receiving a different amount of water.

Types of control groups

Positive and negative controls are two other types of control groups:

• Positive control groups  are control groups in which the conditions guarantee a positive result. Positive control groups are effective to show the experiment is functioning as planned.
• Negative control groups  are control groups in which conditions produce a negative outcome. Negative control groups help identify outside influences which may be present that were not unaccounted for, such as contaminants.
• Members of the control group do not receive the experimental treatment, intervention, or condition. Instead, they may receive a placebo (inactive treatment) or no treatment at all, depending on the study design.
• In many experiments, subjects are randomly assigned to either the control group or the experimental group. Randomization helps ensure that the groups are comparable and that any differences between them are not due to pre-existing biases.
• Control groups can be single-blind or double-blind. In a single-blind design, the subjects do not know whether they are in the control or experimental group. In a double-blind design, both the subjects and the researchers are unaware of group assignments, reducing the potential for bias.
• Control groups are important in controlling or minimizing the influence of confounding variables—factors other than the treatment that could affect the study’s outcome.
• In some cases, control groups may receive a placebo or no treatment, which is ethically acceptable when there is no known effective treatment or when withholding treatment does not harm the subjects.
• In psychology studies, the experimental group might be exposed to a specific psychological intervention, such as cognitive-behavioral therapy, while the control group receives no treatment or an alternative treatment.
• In psychology experiments, control groups might be exposed to a neutral condition or a placebo, while the experimental group is exposed to the variable being studied.

Control vs Experimental Group: Key Differences

Control vs experimental group: key takeaways.

• Control Group : It serves as a baseline or reference group against which the experimental group is compared. It does not receive the experimental treatment or intervention.
• Experimental Group : It is the group that receives the experimental treatment, intervention, or condition being studied.
• Control Group : Receives no treatment or a placebo (inactive treatment) to ensure that any observed effects in the experimental group are due to the experimental treatment and not other factors.
• Experimental Group : Receives the treatment or intervention being studied.
• Control Group : Helps identify the natural course or behavior of the subjects without the experimental intervention.
• Experimental Group : Allows researchers to assess the effects of the experimental treatment or condition on the subjects.
• Control Group : Used for comparison to determine whether the experimental treatment has an effect.
• Experimental Group : Used to measure the impact of the experimental treatment.

Randomization

• Control Group : Subjects in the control group may be randomly assigned, but they do not receive the experimental treatment.
• Experimental Group : Subjects are randomly assigned to ensure that the groups are comparable, with one group receiving the experimental treatment.

Outcome Measurement

• Control Group : Provides a basis for assessing the baseline or natural outcome in the absence of the experimental treatment.
• Experimental Group : Allows researchers to measure the treatment’s effects on the subjects.
• Control Group : Can be single-blind or double-blind, where the subjects or researchers may not know who is in the control group.
• Experimental Group : Can also be single-blind or double-blind, depending on the study design.

Hypothesis Testing

• Control Group : Used to test whether the experimental group’s results significantly differ from the control group, supporting or refuting the research hypothesis.
• Experimental Group : The focus of hypothesis testing to determine if the treatment has a statistically significant effect.

Statistical Analysis

• Control Group : Data from the control group are used as a reference point in statistical comparisons.
• Experimental Group : Data from the experimental group are analyzed to evaluate the treatment’s effectiveness.
• Control Group : Ensures the internal validity of the experiment by controlling for confounding variables.
• Experimental Group : The group of interest for studying the research question and establishing causal relationships.

Major Differences

5 differences between control group and experimental group with example.

• Difference between Alternative hypothesis and Null hypothesis
• Difference between dependent and independent variable

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Experimental Design: Types, Examples & Methods

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.

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Experimental design refers to how participants are allocated to different groups in an experiment. Types of design include repeated measures, independent groups, and matched pairs designs.

Probably the most common way to design an experiment in psychology is to divide the participants into two groups, the experimental group and the control group, and then introduce a change to the experimental group, not the control group.

The researcher must decide how he/she will allocate their sample to the different experimental groups.  For example, if there are 10 participants, will all 10 participants participate in both groups (e.g., repeated measures), or will the participants be split in half and take part in only one group each?

Three types of experimental designs are commonly used:

1. Independent Measures

Independent measures design, also known as between-groups , is an experimental design where different participants are used in each condition of the independent variable.  This means that each condition of the experiment includes a different group of participants.

This should be done by random allocation, ensuring that each participant has an equal chance of being assigned to one group.

Independent measures involve using two separate groups of participants, one in each condition. For example:

• Con : More people are needed than with the repeated measures design (i.e., more time-consuming).
• Pro : Avoids order effects (such as practice or fatigue) as people participate in one condition only.  If a person is involved in several conditions, they may become bored, tired, and fed up by the time they come to the second condition or become wise to the requirements of the experiment!
• Con : Differences between participants in the groups may affect results, for example, variations in age, gender, or social background.  These differences are known as participant variables (i.e., a type of extraneous variable ).
• Control : After the participants have been recruited, they should be randomly assigned to their groups. This should ensure the groups are similar, on average (reducing participant variables).

2. Repeated Measures Design

Repeated Measures design is an experimental design where the same participants participate in each independent variable condition.  This means that each experiment condition includes the same group of participants.

Repeated Measures design is also known as within-groups or within-subjects design .

• Pro : As the same participants are used in each condition, participant variables (i.e., individual differences) are reduced.
• Con : There may be order effects. Order effects refer to the order of the conditions affecting the participants’ behavior.  Performance in the second condition may be better because the participants know what to do (i.e., practice effect).  Or their performance might be worse in the second condition because they are tired (i.e., fatigue effect). This limitation can be controlled using counterbalancing.
• Pro : Fewer people are needed as they participate in all conditions (i.e., saves time).
• Control : To combat order effects, the researcher counter-balances the order of the conditions for the participants.  Alternating the order in which participants perform in different conditions of an experiment.

Counterbalancing

Suppose we used a repeated measures design in which all of the participants first learned words in “loud noise” and then learned them in “no noise.”

We expect the participants to learn better in “no noise” because of order effects, such as practice. However, a researcher can control for order effects using counterbalancing.

The sample would be split into two groups: experimental (A) and control (B).  For example, group 1 does ‘A’ then ‘B,’ and group 2 does ‘B’ then ‘A.’ This is to eliminate order effects.

Although order effects occur for each participant, they balance each other out in the results because they occur equally in both groups.

3. Matched Pairs Design

A matched pairs design is an experimental design where pairs of participants are matched in terms of key variables, such as age or socioeconomic status. One member of each pair is then placed into the experimental group and the other member into the control group .

One member of each matched pair must be randomly assigned to the experimental group and the other to the control group.

• Con : If one participant drops out, you lose 2 PPs’ data.
• Pro : Reduces participant variables because the researcher has tried to pair up the participants so that each condition has people with similar abilities and characteristics.
• Con : Very time-consuming trying to find closely matched pairs.
• Pro : It avoids order effects, so counterbalancing is not necessary.
• Con : Impossible to match people exactly unless they are identical twins!
• Control : Members of each pair should be randomly assigned to conditions. However, this does not solve all these problems.

Experimental design refers to how participants are allocated to an experiment’s different conditions (or IV levels). There are three types:

1. Independent measures / between-groups : Different participants are used in each condition of the independent variable.

2. Repeated measures /within groups : The same participants take part in each condition of the independent variable.

3. Matched pairs : Each condition uses different participants, but they are matched in terms of important characteristics, e.g., gender, age, intelligence, etc.

Learning Check

Read about each of the experiments below. For each experiment, identify (1) which experimental design was used; and (2) why the researcher might have used that design.

1 . To compare the effectiveness of two different types of therapy for depression, depressed patients were assigned to receive either cognitive therapy or behavior therapy for a 12-week period.

The researchers attempted to ensure that the patients in the two groups had similar severity of depressed symptoms by administering a standardized test of depression to each participant, then pairing them according to the severity of their symptoms.

2 . To assess the difference in reading comprehension between 7 and 9-year-olds, a researcher recruited each group from a local primary school. They were given the same passage of text to read and then asked a series of questions to assess their understanding.

3 . To assess the effectiveness of two different ways of teaching reading, a group of 5-year-olds was recruited from a primary school. Their level of reading ability was assessed, and then they were taught using scheme one for 20 weeks.

At the end of this period, their reading was reassessed, and a reading improvement score was calculated. They were then taught using scheme two for a further 20 weeks, and another reading improvement score for this period was calculated. The reading improvement scores for each child were then compared.

4 . To assess the effect of the organization on recall, a researcher randomly assigned student volunteers to two conditions.

Condition one attempted to recall a list of words that were organized into meaningful categories; condition two attempted to recall the same words, randomly grouped on the page.

Experiment Terminology

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 which 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 taking part 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.

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.