8 min read
This study guide covers residuals and residual plots for evaluating linear regression models. It explains how to calculate residuals (observed - predicted), interpret positive and negative residuals, and create residual plots. The guide emphasizes identifying patterns in residual plots to assess model fit, distinguishing between random scatter (good fit) and non-random patterns (bad fit). Finally, it provides practice questions and tips for the AP Statistics exam.
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Question 1 of 11
What does a residual represent in the context of a linear regression model? 🤔
The predicted value minus the observed value
The difference between the actual and predicted values
The sum of all observed values
The slope of the regression line