Simple Linear Regression. Multiple Regression. Drawing Conclusions. Weighted Least Squares, Testing for Lack of Fit, General F-tests, and Confidence Ellipsoids. Diagnostics I: Residuals and Influence. Diagnostics II: Symptoms and Remedies. Model Building I: Defining New Predictors. Model Building II: Collinearity and Variable Selection. Prediction. Incomplete Data. Non-least Squares Estimation. Generalizations of Linear Regression. Appendixes. Tables. References. Symbol Index. Index.

About the Author

Sanford Weisberg is associate professor and director of the Statistical Center at the University of Minnesota. The coauthor of Residuals and Influence in Regression (1982) and an associate editor of Journal of the American Statistical Association, Dr. Weisberg received his PhD in statistics from Harvard University.

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About the Author