Includes bibliographical references (pages 531-548) and index.
Front Matter -- Vectors of Random Variables -- Multivariate Normal Distribution -- Linear Regression: Estimation and Distribution Theory -- Hypothesis Testing -- Confidence Intervals and Regions -- Straight-Line Regression -- Polynomial Regression -- Analysis of Variance -- Departures from Underlying Assumptions -- Departures from Assumptions: Diagnosis and Remedies -- Computational Algorithms for Fitting a Regression -- Prediction and Model Selection -- Appendix A: Some Matrix Algebra -- Appendix B: Orthogonal Projections -- Appendix C: Tables -- Outline Solutions to Selected Exercises -- References -- Index -- Wiley Series in Probability and Statistics.
'Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested'--Provided by publisher.