Which best describes the relationship between correlation and causation?

Question

Responses

A positive correlation between two variables always implies that a change in one variable causes a change in the other variable.
A positive correlation between two variables always implies that a change in one variable causes a change in the other variable.

A negative correlation between two variables always implies that a change in one variable does not cause a change in the other variable.
A negative correlation between two variables always implies that a change in one variable does not cause a change in the other variable.

A correlation between two variables does not always imply that a change in one variable causes a change in the other variable.
A correlation between two variables does not always imply that a change in one variable causes a change in the other variable.

There is no relationship between correlation and causation.
There is no relationship between correlation and causation.

Answer 1

The statement that best describes the relationship between correlation and causation is:

A correlation between two variables does not always imply that a change in one variable causes a change in the other variable.

This statement captures the essential understanding that correlation does not equate to causation, meaning that just because two variables are correlated (positively or negatively) does not mean that one variable directly causes changes in the other. Other factors, including external variables or confounding factors, may influence the observed correlation.