In statistics and research, understanding the relationship between variables is crucial. An explanatory variable, often referred to as an independent variable, is the one that is manipulated or varied to observe its effect on another variable. The response variable, on the other hand, is the one that is measured to see how it is affected by changes in the explanatory variable.
For instance, if we are studying the effect of study hours on exam scores, the number of study hours would be the explanatory variable because it is what we’re controlling or varying. The exam scores would be the response variable as we are measuring how they change as a result of different study hours. Making this distinction is important for properly setting up experiments and interpreting results.