Introduction: Why Regression and Correlation Matter
Regression and correlation are two of the most tested concepts on the AP Statistics exam. From scatterplots to slope interpretation, these skills show up in multiple-choice, FRQs, and calculator work.
Mastering these topics can give you a huge edge on exam day because:
- They appear across multiple units.
- They connect probability, data analysis, and inference.
- They require both interpretation and calculation.
This guide covers the key regression and correlation tips for AP Stats with RevisionDojo’s strategies, practice, and formula support.
Understanding Correlation
Correlation (r) measures the strength and direction of a linear relationship between two quantitative variables.
- Range: -1 ≤ r ≤ 1
- r > 0: Positive association (as x increases, y increases).
- r < 0: Negative association (as x increases, y decreases).
- |r| close to 1: Strong relationship.
- |r| close to 0: Weak/no linear relationship.
Important: Correlation does not imply causation.
Interpreting Correlation on the AP Exam
When asked to describe correlation:
- Mention direction (positive/negative).
- Mention strength (weak, moderate, strong).
- Mention form (linear/nonlinear).
r = -0.82 → “There is a strong negative linear relationship between hours of TV watched per day and GPA.”
