SHAYLE R. SEARLE, PhD, is Professor Emeritus of Biometry at Cornell University. He is the author of Linear Models, Linear Models for Unbalanced Data, and Generalized, Linear, and Mixed Models (with Charles E. McCulloch), all from Wiley.

1. Introduction.
2. Basic Operations.
3. Special Matrices.
4. Determinants.
5. Inverse Matrices.
6. Rank.
7. Canonical Forms.
8. Generalized Inverses.
9. Solving Linear Equations.
10. Partitioned Matrices.
11. Eigenvalues and Eigenvectors.
11A. Appendix to Chapter 11.
12. Miscellanea.
13. Applications in Statistics.
14. The Matrix Algebra of Regression Analysis.
15. An Introduction to Linear Statistical Models.
References.
Index.

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"This book is intended to teach useful matrix algebra to 'students, teachers, consultants, researchers, and practitioners' in 'statistics and other quantitative methods'.The author concentrates on practical matters, and writes in a friendly and informal style . . . this is a useful and enjoyable book to have at hand."
-Biometrics
This book is an easy-to-understand guide to matrix algebra and its uses in statistical analysis. The material is presented in an explanatory style rather than the formal theorem-proof format. This self-contained text includes numerous applied illustrations, numerical examples, and exercises.