Description 
xx, 721 pages : illustrations ; 24 cm 
Series 
Wiley series in probability and statistics 

Wiley series in probability and statistics.

Contents 
1. Introduction  2. The Multivariate Normal Distribution  3. Estimation of the Mean Vector and the Covariance Matrix  4. The Distributions and Uses of Sample Correlation Coefficients  5. The Generalized T[superscript 2]Statistic  6. Classification of Observations  7. The Distribution of the Sample Covariance Matrix and the Sample Generalized Variance  8. Testing the General Linear Hypothesis; Multivariate Analysis of Variance  9. Testing Independence of Sets of Variates  10. Testing Hypotheses of Equality of Covariance Matrices and Equality of Mean Vectors and Covariance Matrices  11. Principal Components  12. Canonical Correlations and Canonical Variables  13. The Distributions of Characteristic Roots and Vectors  14. Factor Analysis  15. Patterns of Dependence; Graphical Models  App. A. Matrix Theory 
Summary 
"For more than four decades An Introduction to Multivariate Statistical Analysis has been an invaluable text for students and a resource for professionals wishing to acquire a basic knowledge of multivariate statistical analysis. Since the previous edition, the field has grown significantly. This updated and improved Third Edition familiarizes readers with these new advances, elucidating several aspects that are particularly relevant to methodology and comprehension."BOOK JACKET 
Notes 
Previous ed.: 1984 
Bibliography 
Includes bibliographical references (pages 687711) and index 
Subject 
Multivariate analysis.

LC no. 
2002034317 
ISBN 
0471360910 hardback alkaline paper 
