Suppose that there were a strong correlation between the variables d and f. Which of these is a true statement?
A. f must cause d.
B. d may cause f.
C. d must cause f.
D. d must not cause f.
The correct answer and explanation is :
The correct answer is:
B. d may cause f.
Explanation:
Correlation between two variables, such as d and f, means that they tend to vary together in a predictable way. However, correlation alone does not establish a cause-and-effect relationship.
Understanding Correlation vs. Causation
- Correlation means that when one variable changes, the other variable also tends to change in a consistent pattern. However, this does not mean that one variable directly causes the other.
- Causation means that changes in one variable directly result in changes in the other. Causal relationships require further investigation through controlled experiments or additional statistical methods.
Evaluating the Answer Choices:
- Option A (f must cause d): Incorrect. A strong correlation does not imply that f necessarily causes d. The relationship could be the other way around, or due to another factor.
- Option B (d may cause f): Correct. The word “may” allows for the possibility that d causes f, but does not assume it as a certainty. While correlation does not prove causation, it suggests that further investigation is needed.
- Option C (d must cause f): Incorrect. Just because d and f are correlated, it does not mean d must be the cause of f. Other factors may be at play.
- Option D (d must not cause f): Incorrect. This statement is too strong because d could still be a cause of f—it is just not guaranteed.
Additional Possibilities:
- Reverse causation: f might actually cause d instead of the other way around.
- Third variable problem: A separate variable, g, might be influencing both d and f, causing the observed correlation.
Thus, the best answer is B. d may cause f, since correlation suggests a possible causal link but does not confirm it.