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Control Variable in Charter School Study

What is the importance of control variable? How does the control variable differ from independent and dependent variables?
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In the charter school study example, the independent variable is charter education-related inputs, while the dependent variable is students’ performance. Do you recall that you should not conclude the causality simply because you have the independent and dependent variables? What we can say is there is a relationship between the independent and dependent variables. However, Here, the experimenter wanted to make sure that charter schooling had caused the performance change. But how can we do that? How can we make sure that charter schooling caused performance improvement? The method that the experimenter had selected was the control variable.

The article introduces the control variable. The control variable, as its name tells, is the variable that remains the same throughout the whole experiment. It is the choice that the experimenter wants to make it constant so that it does not disturb the results of the experiment. In this example, the experimenter wants to know if the students’ performance increased or not due to charter schooling. Then, the experimenter had controlled all other factors that could affect students’ performance except for the existence of charter schooling.

If the students come from a particular local area, this might affect the result. In other words, students’ performance might not be solely from the charter school, but the other reason. For example, most of the students come from a very affluent area, and the parents might spend a lot more time and money to help their kids to improve the academic performance outside of schooling. In this case, the areas students come from should become the control variable. We should have students from various regions. Because of that, our conclusion of the relationship between charter schooling and performance should not be affected.

Then how do you decide upon which variable is the control variable? It is why you have to understand the problem you like to solve very well before you do any data analysis. You will do reasoning based on your knowledge of the subject.

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