What Are Control Variables?
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A control variable is not the aim of the study, though it exists and should be controlled because it can influence the outcomes. Control variables should be constant and restricted in their potential.
You can control variables by keeping them in the same form or state throughout the entire research process. Or you can control such variables via randomization or statistical impact.
- The research question is ‘Does the amount of water influence the growth of succulents?’ Possible control variables are air temperature, types of plant pots, and the amount of light.
- The research question is ‘Do people with agoraphobia always avoid crowds?’ Possible control variables are the number of people acceptable to feel comfortable, the size of the room or other space, and the levels of noise.
- The research question is ‘Can chocolate reduce stress?’ Possible control variables can involve the age of participants, their levels of chocolate consumption, other diet components, and their levels of stress.
Why Are Control Variables Important?
Control variables can reduce the influence of other types of variables, such as confounding and extraneous ones. Therefore, they boost the internal validity of the research results. You can also set a more accurate correlation or causal relationship between independent and dependent variables within the research.
Unrelated to independent and dependent variables and their interaction, all other variables that can impact the results should be properly controlled. If you do not do that, you will not be able to prove that these variables did not influence the results of your study. They can always provide alternative explanations and outcomes.
Experiments and Control Variables
When you conduct an experiment, you want to understand the influence of an independent on a dependent variable. When you use control variables, you can be sure that no other factors, apart from your manipulations, have influenced the dependent variables.
Your study’s purpose is to research the impact of aspirin on improving the heart’s health. The control group receives a placebo pill, while the experimental group receives aspirin. The independent variable is aspirin consumption. The dependent variable is heart activity. To be sure that taking aspirin changes heart performance and that these changes are not caused by other factors, you should control the following variables:
- ✔️ taking other medicines;
- ✔️ the age of participants;
- ✔️ the presence of other acute or chronicle disorders;
- ✔️ the effect of any external situations and environments.
Non-Experimental Research and Control Variables
Non-experimental research involves observations and other types of study. You cannot manipulate the independent variable here. There are practical or ethical limitations to this. So, you need control variables to understand the relationships between independent and dependent variables.
You are planning to research relationships between the variables of receiving good academic education and happiness. Your hypothesis is that a well-educated person does not always feel as happy as those who have not received enough education. You cannot manipulate the variable of education because it is already a constant factor. Instead, you can use a survey for collecting data about the connections between levels of education and people’s happiness.
There are some other factors that can influence the results, so you need to control them. They may include participants’ age, working experiences, hobbies, favorite occupations, and levels of income.
How Can You Control a Variable?
You can apply different techniques for controlling extraneous variables in experimental, quasi-experimental, and observational designs.
Assigning Tasks Randomly
You can assign different conditions or tasks to multiple groups randomly in your experimental studies. In this way, you can balance the specific group characteristics and eliminate differences between them. This technique can prevent skewing the final results.
You are conducting an experiment and need to recruit participants for it. You use social media, spreading flyers, and word of mouth. You have found 35% of participants via Facebook and Instagram, while 45% have read about your experiments in the flyers. Those who found your ad via the Internet are likely to spend more time on social media, so they appear to be more responsive. If your experiment is connected with using the Web, it makes sense to divide the participants into experimental and control groups randomly to avoid biased influences.
Using Standardized Procedures
You should apply the same procedures to all groups within your experiment. Only an independent variable and manipulations with it can differ. In this way, you can distinguish between different influences on dependent variables and their results.
Keep the external variables constant during the entire procedure to control them. You can use a specifically created protocol for this. You should also care about the same settings and environment during the experiment for all the groups.
Define the exact time for doing the task for all the groups and provide them with the same instructions. The instructions for all the participants should be the following:
- To control the amount of time spent on the Internet by all the participants, they are asked to fix the time they spend on work and relaxation there.
- To control the effectiveness of Internet use, all the participants are instructed to use the Internet only during the daytime.
- To control their emotions after using social media, all the participants are asked to report their feelings and well-being at a certain time at the end of the day.
The experimental group can also be provided with some additional instructions (for example, never use the Internet between 12:00 and 3:00 p.m. every day. This additional instruction should not be available to the control group.
Controlling Variables Statistically
You can control extraneous variables statistically in non-experimental and quasi-experimental designs. That will reduce their influence on the variables of your interest.
You can control variables in this way by modeling the control variable data with the help of regression analysis or ANCOVAs. You can distinguish between the control variable’s effects and the true correlations between independent and dependent variables.
For example, you can collect separately the data for your main variables, such as the time spent on the Internet, the amount of time spent at the computer, and the people’s emotions afterward. The data related to control variables of age, occupation, and emotional reactions should be gathered, too, but with the help of a different task.
When you do a multiple linear regression analysis, the focus is on the correlation between the independent and dependent variables, plus the addition of all control variables to make more accurate predictions. The combined results will tell you how people who use social media for a long time during the day will feel depending on their age, gender, occupation, and emotional reactions.
What Is the Difference Between a Control Variable and a Control Group?
These two terms should not be confused. Control variables are external variables that need to remain constant throughout the entire research, either for experimental or control groups. However, you can vary an independent variable between these two groups. A control group is a group that does not need to be exposed to experimental treatment. The outcomes of such an approach are compared and analyzed at the end of the research.
A control group usually does not have any treatment or has a placebo treatment (or something similar to that if it is not related to medicine) or undergoes the standard treatment that everybody knows a lot about. All other factors, apart from the experimental treatment, should be the same between these two groups.
Final Thoughts
As you see, control variables play an important role in enhancing the internal and external validity of your research results. You should derive the control variables from all the external ones that can influence the results of your study and keep them constant throughout the entire experiment or observation. If you manage to do that, the results of your study will be trustworthy and viable. They can become an excellent basis for further research in this field and the next step to your academic success.