Anything that is considered to be constant or limited in an experiment or research study is termed Control Variable. The variable contributes nothing to the study’s outcome; however, it must be controlled so as not to have any influence on the results.

Variables can be controlled if they are held constant throughout the study. One example of this is controlling the room temperature during the experiment. Variables can also be controlled indirectly with the use of several methods like statistical control or randomisation.

What is the importance of control variables?

Control variables help limit the influence of external or confounding variables, which helps to enhance the study’s internal validity. In addition, such variables help to establish the relationship between your variables of interest.

The variables that can impact the results should be controlled apart from the independent and dependent variables. If relevant variables are left unchecked, you might not prove their influence on the results. Uncontrolled variables leave room for alternate explanations to your findings.

• Control variables in experiments: When conducting research, the research is more likely to be interested in the effects the independent variable has on the dependent one. By controlling the other variables, they can ascertain that their experimental manipulation solely causes the results.
• Control variables in non-experimental research: In non-experimental research, researchers are not able to manipulate independent variables. In such a case, control variables play a vital role which helps to infer the relation between the main variables of interest.

How do you control a variable?

Several methods help to control extraneous variables during experiments. Some of them can also be employed during observational or quasi-experimental designs.

• Random assessment: When conducting experiments involving several subjects, participants should be randomly chosen and assigned to different conditions. Random assessment helps to ensure that there are no systematic differences by balancing the characteristics of the groups.
• The assignment method helps to control subject variables, which might otherwise vary among groups causing the results to skew.
• Standardised procedures: Researchers must apply the same rules of control across all groups when conducting a study. In ideal cases, the groups should only differ in manipulating the independent variable, which will help researchers isolate its effects on the dependent variable.
• A good way of controlling variables is by holding them constant to a certain level using the experiment’s design protocol and using the same for all participant sessions. For example, the time spent. The instructions should be the same for all the participants in a laboratory setting for conducting experimental tasks.
• Statistical controls: Extraneous variables can be measured and controlled statistically to negate their effects on other variables.
• Modelling control variable data by considering the independent and dependent variable in ANCOVAs and regression analysis is known as “Controlling for a variable”. This is because it helps to isolate the effects of the control variable from the relation between the independent and dependent variables that we are interested in.

Control variable vs control group

A control variable is quite different from a control group. Control variables are the extraneous variables that are held constant or measured during an experiment for both experimental and control groups, with an independent variable varying between control and experimental groups.

On the other hand, a control group does not go through experiments as they are used as the benchmark to compare results with the experimental group. A control group undergoes no treatment or sometimes is placed under a placebo.

Everything else apart from the experimental treatment should be the same between the control and experimental group during the procedure.

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