Confounding Variable vs Response Variable
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Confounding variable
Collecting data and study design
A confounding variable is one whose effect on the response is tangled with the explanatory variable's, so you cannot separate their two influences.
A confounding variable changes along with the explanatory variable, so its effect and the explanatory variable's effect on the response cannot be told apart. This is why an observed association does not by itself prove causation. For example, if students who attend tutoring also study more, and tutored students score higher, study time confounds the effect of tutoring. Random assignment defends against confounding by spreading such variables evenly across the treatment groups on average.
Response variable
Variables and data types
A response variable is the outcome you measure to see how it changes with the explanatory variable; it goes on the y-axis of a scatterplot.
The response variable, also called the dependent variable, is the outcome you expect to depend on the explanatory variable. It sits on the vertical axis and supplies the values in a regression, so the fitted line predicts it. For example, when studying how study time affects test scores, the test score is the response variable. A regression line estimates the mean response for each value of the explanatory variable.