This is post #3 on the subject of linear regression, using R for computational demonstrations and examples. We cover here residuals (or prediction errors) and the RMSE of the prediction line. The first post in the series is LR01: Correlation. Acknowledgments: organization is extracted from: Freedman, Pisani, Purves, Statistics, 4th ed., probably the best book on statistical thinking...