Introduction to Applied Multivariate Analysis with R

Brian Everitt is Professor Emeritus at King's College, London. He is the author of over 50 books on statistics. Torsten Hothorn is Professor of Biostatistics in the Faculty of Mathematics, Computer Science and Statistics at Ludwig-Maximilians-Universitat Munchen in Germany.

"This book covers basic to advanced approaches for the analysis of multivariate data in R. ... All chapters end with a summary and exercises, making this book an excellent addition to applied statistics courses. The approach, numerous examples and fragments of code make it accessible to undergraduate and postgraduate students alike, as well as researchers ... ." (Irina Ioana Mohorianu, zbMATH 1306.62010, 2015) "Each chapter introduces briefly the theory on well-known methods to analyze multivariate data and then focuses on the application of the multivariate techniques to example data with R. ... addressed to students in applied statistics courses or applied statisticians looking for a valuable educational textbook on multivariate analysis. ... an ideal textbook for students or persons, employed in the field of applied statistics, who wish to study the analysis of multivariate data and to apply multivariate techniques to real data." (Wiebke Werft, Biometrical Journal, Vol. 55 (6), 2013) "This practical book provides a well-organized summary of popular multivariate data analysis techniques with practical examples. As the book title indicates, all introduced techniques are accompanied by relevant and friendly R codes, and thus it can be used for excellent R programming reference for those who wish to use R for multivariate data analysis." (Technometrics, Vol. 54 (4), November, 2012)

• Multivariate data and multivariate analysis.- Looking at multivariate data: visualization.- Principal components analysis.- Multidimensional scaling.- Exploratory factor analysis.- Cluster analysis.- Confirmatory factor analysis and structural equation models.- The analysis of repeated measures data.-