Matrix Algebra Useful for Statistics
WILEY-INTERSCIENCE PAPERBACK SERIES

The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists.

"This book is intended to teach useful matrix algebra to 'students,teachers, consultants, researchers, and practitioners' in'statistics and other quantitative methods'.The author concentrateson 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 itsuses in statistical analysis. The material is presented in anexplanatory style rather than the formal theorem-proof format. Thisself-contained text includes numerous applied illustrations,numerical examples, and exercises.
1101193094
Matrix Algebra Useful for Statistics
WILEY-INTERSCIENCE PAPERBACK SERIES

The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists.

"This book is intended to teach useful matrix algebra to 'students,teachers, consultants, researchers, and practitioners' in'statistics and other quantitative methods'.The author concentrateson 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 itsuses in statistical analysis. The material is presented in anexplanatory style rather than the formal theorem-proof format. Thisself-contained text includes numerous applied illustrations,numerical examples, and exercises.
175.75 In Stock
Matrix Algebra Useful for Statistics

Matrix Algebra Useful for Statistics

by Shayle R. Searle
Matrix Algebra Useful for Statistics

Matrix Algebra Useful for Statistics

by Shayle R. Searle

Paperback(Older Edition)

$175.75 
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Overview

WILEY-INTERSCIENCE PAPERBACK SERIES

The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists.

"This book is intended to teach useful matrix algebra to 'students,teachers, consultants, researchers, and practitioners' in'statistics and other quantitative methods'.The author concentrateson 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 itsuses in statistical analysis. The material is presented in anexplanatory style rather than the formal theorem-proof format. Thisself-contained text includes numerous applied illustrations,numerical examples, and exercises.

Product Details

ISBN-13: 9780470009611
Publisher: Wiley
Publication date: 03/20/2006
Series: Wiley Series in Probability and Statistics , #633
Edition description: Older Edition
Pages: 480
Product dimensions: 6.20(w) x 9.20(h) x 1.01(d)

About the Author

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.

Table of Contents

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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