This is when ahypothesisis 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. Thequantitative datacan be analyzed to see if there is a difference between the experimental and control groups.
What is the control group?
In experiments scientists compare acontrol group and an experimental groupthat 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 ofrandom allocationis 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 variablesshould 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.
Key Terminology
Experimental GroupThe group being treated or otherwise manipulated for the sake of the experiment.
Experimental Group
The group being treated or otherwise manipulated for the sake of the experiment.
Control GroupThey receive no treatment and are used as a comparison group.
Control Group
They receive no treatment and are used as a comparison group.
Ecological validityThe degree to which an investigation represents real-life experiences.
Ecological validity
The degree to which an investigation represents real-life experiences.
Experimenter effectsThese are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.
Experimenter effects
These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.
Demand characteristicsThe clues in an experiment lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).
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.
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.
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 variablesshould be controlled where possible.
Extraneous variables (EV)
All variables that are not independent variables but could affect the results (DV) of the experiment.Extraneous variablesshould be controlled where possible.
Confounding variablesVariable(s) that have affected the results (DV), apart from the IV. Aconfounding variablecould be an extraneous variable that has not been controlled.
Confounding variables
Variable(s) that have affected the results (DV), apart from the IV. Aconfounding variablecould be an extraneous variable that has not been controlled.
Random AllocationRandomly allocating participants to independent variable conditions 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.
Random Allocation
Randomly allocating participants to independent variable conditions 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.
Randomly allocating participants to independent variable conditions 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.
Order effectsChanges 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.FAQs
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.FAQs
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.
FAQs
What is the control in an experiment?In anexperiment, 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?Theexperimental methodis a systematic approach in scientific research where an independent variable is manipulated to observe its effect on a dependent variable, under controlled conditions.
What is the control in an experiment?In anexperiment, 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 control in an experiment?
In anexperiment, 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.
In anexperiment, 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.
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.
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.
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.
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?Theexperimental methodis a systematic approach in scientific research where an independent variable is manipulated to observe its effect on a dependent variable, under controlled conditions.
What is the experimental method?
Theexperimental methodis a systematic approach in scientific research where an independent variable is manipulated to observe its effect on a dependent variable, under controlled conditions.
Olivia Guy-Evans, MSc
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.
Saul McLeod, PhD
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.
