"This textbook presents a classical approach to some techniques of multivariate analysis in a simple and transparent manner. It offers clear and concise development of the concepts; interpretation of the output of the analysis; and criteria for selection of the methods, taking into account the strengths and weaknesses of each. With its roots in matrix algebra, for which a separate chapter has been added as an appendix, the book includes both data-oriented techniques and a reasonable coverage of classical methods supplemented by comments about robustness and general practical applicability. It also illustrates the methods of numerical calculations at various stages."--Publisher's website.

Includes bibliographical references (p. 525-534) and indexes.

Preliminaries -- Organization of multivariate data -- Multivariate normal distributions and related distributions -- Distributions arising out of the multivariate normal distribution -- Testing of hypotheses -- Multivariate regression analysis -- Multivariate analysis of variance and covariance -- Principal component analysis -- Factor analysis -- Canonical correlation -- Classification and discrimination.