Review by Choice Review
This book (the first of two in a comprehensive survey of the subject) concentrates on what can be called basic methods of multivariate analysis. After a brief introduction, chapters discuss the fundamental distribution theory (required for understanding the remainder of the book), initial data analysis, projections and linear transformations, and distance methods and ordination, all presenting a survey of various descriptive techniques used in multivariate analysis. The final three chapters on inference, multivariate linear models, and nonlinear models discuss those inferential techniques that generalize familiar univariate methods to the multivariate case. This work is much more than just a revision of Maurice G. Kendall's Multivariate Analysis (1st ed., 1975; 2nd ed., CH, Mar'81); authors have adhered to Kendall's original aim of providing a comprehensive account of the subject as it now stands without a great overburden of technical mathematics. Rather than give extensive detailed proofs, the authors rely on references. A major, very welcome addition is a collection of exercises at the end of the chapters. Upper-division undergraduate through faculty. F. Giesbrecht; North Carolina State University
Copyright American Library Association, used with permission.
Review by Choice Review
