Which statement about correlation and causation is true? Correlation always implies causation. Causation always implies correlation. Correlation does not necessarily imply causation. Causation and correlation are synonymous terms.

The correct statement about correlation and causation is: "Correlation does not necessarily imply causation."

Here's why:

1. Correlation is a statistical measure that describes the degree to which two variables move in relation to each other. If two variables are correlated, it means that as one changes, there's a predictable change in the other. However, this doesn't mean that one variable is causing the other to change.

2. Causation, on the other hand, is a cause-and-effect relationship. If A causes B, then a change in A will always result in a change in B.

3. The statement "Correlation always implies causation" is incorrect because, as explained above, just because two variables are correlated doesn't mean one is causing the other to change. There could be other factors at play, or it could be a coincidence.

4. The statement "Causation always implies correlation" is also incorrect. While it's true that if A causes B, then A and B are likely to be correlated, it's not always the case. There could be other factors influencing B that disrupt the correlation.

5. The statement "Causation and correlation are synonymous terms" is incorrect. As explained above, correlation and causation have different meanings in statistics.

6. Therefore, the statement "Correlation does not necessarily imply causation" is the correct one. It's possible for two variables to be correlated without there being a cause-and-effect relationship between them.