Least Squares for Response Surface Work

This chapter contains sections titled: The Method of Least Squares Linear Models Matrix Formulas for Least Squares Geometry of Least Squares Analysis of Variance for One Regressor Least Squares for Two Regressors Geometry of the Analysis of Variance for Two Regressors Orthogonalizing the Second Regressor, Extra Sum of Squares Principle Generalization to p Regressors Bias in Least-Squares Estimators Arising from an Inadequate Model Pure Error and Lack of Fit Confidence Intervals and Confidence Regions Robust Estimation, Maximum Likelihood, and Least Squares Appendix 3A. Iteratively Reweighted Least Squares Appendix 3B. Justification of Least Squares by the Gauss–Markov Theorem; Robustness Appendix 3C. Matrix Theory Appendix 3D. Nonlinear Estimation Appendix 3E. Results Involving V(ŷ) Exercises