In the context of scatterplots and correlation, which statement best describes how correlation and causation differ?

• A. Correlation can only be negative, while causation can be positive or negative.
• B. Correlation describes an association between two variables, while causation means changes in one variable directly produce changes in the other.
• C. Correlation proves a cause-and-effect relationship, while causation only suggests a possible relationship.
• D. Correlation means one variable causes the other, while causation only means the variables are related.

Answer: (B)

Verified step by step guidance

1. Step 1: Understand the concept of correlation. Correlation measures the strength and direction of a linear relationship between two variables. It is a statistical association but does not imply that one variable causes the other to change.
2. Step 2: Understand the concept of causation. Causation means that changes in one variable directly cause changes in another variable, indicating a cause-and-effect relationship.
3. Step 3: Recognize that correlation can be positive (both variables increase together) or negative (one variable increases while the other decreases), but it only indicates association, not causality.
4. Step 4: Note that causation requires more rigorous evidence, such as controlled experiments or longitudinal studies, to establish that one variable produces changes in another.
5. Step 5: Conclude that the best description is: correlation describes an association between two variables, while causation means changes in one variable directly produce changes in the other.