Correlation Does Not Imply Causation

Correlation vs. causation

A correlation means two variables move together in some way. Causation means one variable actually produces a change in the other. These are not the same thing, so a strong pattern in data does not by itself prove one thing causes the other.

How to approach each exercise

1. Identify the relationship shown. Decide whether the data only shows an association, a trend, or a possible cause-and-effect statement.
2. Ask what is actually supported. If the information only comes from observed data, the safest conclusion is usually that the variables are correlated.
3. Look for alternative explanations. A third variable, coincidence, or reverse direction may explain the pattern.
4. Choose the simplest correct conclusion. If the exercise asks for a simplified final answer, state only what the data supports and avoid adding unsupported causation.

Good check

Before finishing, ask: “Does this evidence prove that one variable directly changes the other?” If not, your answer should say the relationship is correlation, not causation.

Common wording

Phrases like “is associated with,” “is related to,” or “moves with” usually describe correlation. Phrases like “causes” or “leads to” require much stronger evidence than a pattern alone.