Statistics (STAT 101) Linear Regression Practice Problems: Correlation, Residuals, and R-Squared
University of Minnesota
Statistics (STAT 101) | Practice Problems

Overview
A STAT 101 regression review for interpreting scatterplots, correlation, least-squares lines, residuals, R-squared, and prediction limits.

Key topics
•direction, form, strength, and outliers in scatterplots
•correlation sign and magnitude
•least-squares regression line interpretation
•residual plots and model fit
•R-squared as explained variation

Suggested study tasks
•interpret 10 scatterplot descriptions
•calculate and explain 8 residuals
•answer 12 slope/intercept interpretation prompts
•classify 6 residual plots
•write a do-not-extrapolate checklist

Common pitfalls
•calling correlation causation
•using regression outside the data range
•misreading R-squared as percent correct
•ignoring curved residual patterns
•forgetting units for slope and intercept