This is a brand new edition of a classic work on multivariate data analysis. Most of the observable phenomena in the empirical sciences are of a multivariate nature.In financial studies, assets in stock markets are observed simultaneously and their joint development is analyzed to better understand general tendencies and to track indices. In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication. In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior. The underlying theoretical structure of these and many other quantitative studies of applied sciences is multivariate.A key advantage of the work is its accessibility. This is because, in its focus on applications, the book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data. In this second edition a wider scope of methods and applications of multivariate statistical analysis is introduced. All quantlets have been translated into the R and Matlab language and are made available online.
Review:
This textbook gives a broad and modern introduction to statistics for multivariate data. A bunch of interesting examples is used to illustrate the techniques. … All chapters are finished by memorable summaries subsuming the main results and a couple of exercises. The mathematical background and derivations are concise, while practical aspects like computation and visualization are stressed using detailed examples. … I consider the book to be an excellent starting point for everybody interested in learning about statistical methods for multivariable data sets." (R. Fried, Metrika, 2006)
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