Which statement best describes the relationship between correlation and causation?

• A. Correlation proves causation
• B. Correlation implies one variable causes the other
• C. Correlation indicates association but does not prove causation
• D. Correlation is unrelated to causation

Answer: (C)

Understanding how correlation and causation relate helps you distinguish when two things just move together from when one actually causes the other. When two variables are correlated, it means they have a relationship or association—when one changes, the other tends to change in a predictable way. But that association alone doesn’t prove that one variable makes the other change.

There are many reasons two things can move together without one causing the other. They might both be influenced by a third factor, they could be connected through a chain of events, or the signal could be coincidental. To claim causation, you need stronger evidence: demonstrating a temporal order (the cause happens before the effect), ruling out confounding factors, and ideally showing the effect persists under controlled conditions, such as in a well-designed experiment.

So the best description is that correlation indicates an association but does not prove causation. An example is ice cream sales and sunburn; they rise together in hot weather, but one does not cause the other—the heat drives both. If you see a correlation, you should consider other explanations and seek experiments or additional data to establish causality rather than assuming one variable causes the other.