Exploratory Multivariate Analysis by Example Using R provides a very good overview of the application of three multivariate analysis techniques . There is a clear exposition of the use of [R] code throughout . this book does not express the mathematical concepts in matrix form. This is clearly advantageous for those who are considering the book from an applied perspective. This, I think, is refreshing and is done well. I therefore recommend the book to those who are interested in an introduction to these multivariate techniques. the book does provide a solid starting point for those who are just starting out. definitely a book to have in one's .

library. --Eric J. Beh, Journal of Applied Statistics, June 2012 Its strength is its detailed advice on interpretation, in the context of varied examples. It is written in a pleasant and engaging style . This text is a great source of worked examples and accompanying commentary. --John H. Maindonald, International Statistical Review (2011), 79 It is an excellent book which I would strongly recommend as a secondary text, supporting or accompanying the main text for any advanced undergraduate or graduate course in multivariate analysis. this is a compact book with a plethora of visualizations teaching all subtleties of major data exploratory methods.

It would supplement well any primary textbook in an advanced undergraduate or graduate course in multivariate analysis. --MAA Reviews, July 2011 . a truly excellent [chapter] on clustering . is an example of what upper-division undergraduate writing should aspire to. this enjoyable book and the FactoMineR package are highly recommended for an upper-division undergraduate or beginning graduate-level course in MVA. The acid test for such a work must be whether it is likely to spark an interest in students and prepare them adequately for more detailed, serious study of the subject and this book easily passes that test. --Journal of Statistical Software, April 2011, Vol. 40.