Answer:
The correct answer is D. A confounding variable.
A confounding variable is a variable that is related to both the independent variable and the dependent variable, which can distort the relationship between the two variables. This means that it is a non-manipulatable variable that can affect the outcome or results of an experiment or study. Examples of confounding variables include a person's sex, age, socioeconomic status, or geographic location. The purpose of a statistical analysis is to identify and control for confounding variables so that the effect of the independent variable on the dependent variable can be correctly determined.