Which statement best describes the difference between correlation and causation?

• A. Correlation implies causation.
• B. A relationship between two variables is called correlation; causation means one variable directly causes the change in another.
• C. Causation means two variables move together.
• D. They are the same.

Answer: (B)

The important distinction is between correlation and causation. Correlation is when two variables show a pattern of association—they tend to move together in some way, but one does not necessarily cause the other. Causation means one variable directly brings about a change in the other, a cause-and-effect link.

The statement that a relationship between two variables is called correlation, while causation means one variable directly causes the change in another, is the best description because it separates simply noticing a pattern from proving a cause-and-effect relationship. You can observe a correlation without assuming a direct cause; there could be a third factor or coincidence at play.

For example, ice cream sales and sunglasses bought might rise together in sunny weather. That’s a correlation, not causation—the hot weather drives both, but buying ice cream doesn’t cause more sunglasses to be sold, and vice versa. To claim causation, you’d need evidence that changing one variable directly changes the other, ideally with a clear mechanism and proper controls or experiments.