An Introduction to Applied Multivariate Analysis with R (Use R!)

Brian Everitt, Torsten Hothorn

ISBN 10: 1441996494 / ISBN 13: 9781441996497

Editore: Springer 2011-05-03, 2011

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Codice articolo 6666-IUK-9781441996497

Dati bibliografici

Titolo: An Introduction to Applied Multivariate ...

Casa editrice: Springer 2011-05-03

Data di pubblicazione: 2011

Legatura: Paperback

Condizione: New

Descrizione articolo

Riassunto:

The majority of data sets collected by researchers in all disciplines are multivariate. This book comprehensively covers a variety of multivariate analysis techniques using R. It provides extensive examples of R code used to apply the multivariate techniques.

Recensione:

“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)