Which of the following best describes a confounding variable in the context of probability and statistics?

• A. A variable that is intentionally manipulated by the researcher to observe its effect on the response variable.
• B. A variable that is always independent of both the explanatory and response variables.
• C. A variable that is not measured in a study but influences both the explanatory and response variables, potentially leading to a false association between them.
• D. A variable that is only related to the response variable and not to the explanatory variable.

Answer: (C)

Verified step by step guidance

1. Understand that a confounding variable is a third variable in a study that can affect both the explanatory (independent) variable and the response (dependent) variable.
2. Recognize that this variable is not controlled or measured in the study, which means its influence can create a misleading association between the explanatory and response variables.
3. Recall that a confounding variable can make it appear as though there is a direct relationship between the explanatory and response variables when, in fact, the relationship is influenced or caused by this hidden variable.
4. Note that a confounding variable is different from a variable that is intentionally manipulated (which is the explanatory variable) or one that is independent of both variables.
5. Therefore, the best description of a confounding variable is: a variable that is not measured in a study but influences both the explanatory and response variables, potentially leading to a false association between them.