Which statement best describes correlation without implying causation?

• A. A reported association proves the causal link.
• B. An observed correlation does not prove causation.
• C. There is no relationship between the variables.
• D. The relationship is always due to a third factor.

Answer: (B)

At its heart, this question is about distinguishing association from causation. A correlation simply means two things tend to move together in some pattern, but it doesn’t tell you which one causes the other, or if a second factor is driving both. To move from correlation to causation, you need evidence that rules out other explanations, shows the direction of influence, and demonstrates that changing one variable leads to a change in the other.

For example, ice cream sales and drowning incidents rise together in summer. The correlation exists, but the hotter weather drives both, not that ice cream causes drownings. This kind of pattern shows why correlation alone isn’t proof of causation.

The only statement that matches this nuance is that an observed correlation does not prove causation. The other options push too far—either claiming a proven causal link, denying any relationship, or insisting the effect is always due to a third factor—none of which accurately reflect why correlation isn’t enough to establish cause.