Which statement best distinguishes correlation from causation?

• A. Correlation indicates a relationship; causation proves one variable causes the other; example: smoking and lung cancer; causation established by trials
• B. Correlation implies immediate treatment
• C. Causation is weaker than correlation
• D. Correlation requires a randomized trial

Answer: (B)

The key idea is that correlation is simply an association between two variables, while causation means one variable actually causes the other to change. Seeing two things rise and fall together doesn’t prove one causes the other; there could be a third factor at play or the relationship could be coincidental. Proving causation usually means showing that changing the first variable leads to a change in the second, and this evidence typically comes from well-designed studies or trials that control for confounding factors and establish temporality (the cause comes before the effect). That’s why correlation by itself does not justify treatment decisions—treatment relies on evidence that one thing truly causes another, often supported by randomized trials or other rigorous evidence. In short, correlation signals a relationship; causation demonstrates a true cause-and-effect connection.