True or false: When correlation coefficients reach the 'strong' or 'very strong' ranges, you have discovered statistical evidence that one attribute causes the other to change.

• A. True
• B. False
• C. Causation not implied
• D. Not enough data

Answer: (B)

The key idea here is that correlation measures association, not causation. A strong or very strong correlation means the two attributes move together in a predictable way, but it does not prove that one causes the other to change. There could be a third variable driving both, the relationship could be reversed, or the association might arise by coincidence in the data sample. To claim causation you need additional evidence beyond correlation—such as temporal order showing that the change in one variable precedes the change in the other, careful control of confounding factors, or experimental or quasi-experimental designs that isolate the effect.

So, even with a high correlation, you haven’t necessarily found evidence that one attribute causes the other.