From the reviews:
„The authors’ intention is to present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners who are confronted by statistical data analysis … . The book has a friendly yet rigorous style. All methods are demonstrated through numerous real examples. Mathematical results are clearly stated … . All chapters contain numerous theoretical and practical exercises. … it can be said that the authors have fully attained their goals.“ (Ricardo Maronna, Statistical Papers, Vol. 46 (1), 2005)
„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)
„The mathematics and statistical theory is at the graduate statistics level, and at that level, this book is superb. … Many of the applications … are packed with graphical presentations and are very informative and interesting to read. The exercises would be acceptable for classroom purposes. … it would serve well as a reference to a ‘mathematically mature’ person already familiar with multivariate methods. The e-book version makes the work particularly valuable as a reference.“ (Charles E. Heckler, Technometrics, Vol. 47 (4), 2005)
„The book contains a state of the art presentation of the tools and concepts of multivariate data analysis with a strong focus on applications. … It is an attractive blend of theory and practice with a wide range of examples and 228 exercises. All datasets used in the book can be downloaded and a downloadable online version offers interactive exercises and data analysis.“ (T. Postelnicu, Zentralblatt MATH, Vol. 1028, 2005)
„As the title of the book indicates this volume is particularly directed towards a readership that is interested in practical help when facing multivariate statistical problems. … Moreover, the many examples accompanying the presentation of the different methods cover various areas of empirical research. … It concludes with an appendix where we find all data sets used for the various real data examples. Each section provides a sample of exercises. … particular feature of this book is that it belongs to the Springer e-books series.“ (Stefan Sperlich, Statistical Software Newsletter, 2004)
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. Focussing on applications this book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who face statistical data analysis.
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.
