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This new edition, now with a co-author, offers a complete and up-to-date examination of the field. The authors have streamlined previously tedious topics, such as multivariate regression and MANOVA techniques, to add newer, more timely content. Each chapter contains exercises, providing readers with the opportunity to test and extend their understanding. The new edition also presents several expanded topics in Kronecker product; prediction errors; maximum likelihood estimation; and selective key, but accessible proofs. This resource meets the needs of both statistics majors and those of students and professionals in other fields.
Preface xvii
Acknowledgments xxi
1 Introduction 1
2 Matrix Algebra 7
3 Characterizing and Displaying Multivariate Data 47
4 The Multivariate Normal Distribution 91
5 Tests on One or Two Mean Vectors 125
6 Multivariate Analysis of Variance 169
7 Tests on Covariance Matrices 259
8 Discriminant Analysis: Description of Group Separation 281
9 Classification Analysis: Allocation of Observations to Groups309
10 Multivariate Regression 339
11 Canonical Correlation 385
12 Principal Component Analysis 405
13 Exploratory Factor Analysis 435
14 Confirmatory Factor Analysis 479
15 Cluster Analysis 501
16 Graphical Procedures 555
Appendix A: Tables 597
Appendix B: Answers and Hints to Problems 637
Appendix C: Data Sets and SAS Files 727
References 729
Index 747
Alvin C. Rencher is Professor Emeritus in the Department of Statistics at Brigham Young University. A Fellow of the American Statistical Association, he is the author of Linear Models in Statistics, Second Edition and Multivariate Statistical Inference and Applications, both published by Wiley. William F. Christensen is Professor in the Department of Statistics at Brigham Young University. He has been published extensively in his areas of research interest, which include multivariate analysis, resampling methods, and spatial and environmental statistics.
