"The book's simplicity of approach and clear presentation make it a good choice for an undergraduate course or a self-study course in multivariate analysis."
- Journal of the American Statistical Association
"The original aims of the book are fulfilled remarkably well, thus providing a text which is to be welcomed into an area where there has been a recent dearth of introductory material."
Part One. Multivariate distributions. Preliminary data analysis. Part Two: Finding new underlying variables. Principal component analysis. Factor analysis. Part Three: Procedures based on the multivariate normal distribution. The multivariate normal distribution. Procedures based on normal distribution theory. The multivariate analysis of variance. The multivariate analysis of covariance and related topics. Part Four: Multi-dimensional scaling and cluster analysis. Multi-dimensional scaling. Cluster analysis.
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