An Introduction to Applied Multivariate Analysis with R

by Brian S. Everitt

.

Genres: Mathematics

Paperback

First published January 1, 2011

Reviews

[Marius · Rating 4 out of 5]

This book is just like your genius but confusing statistics professor. The authors love fancy formulas but keep their focus on examples, unfortunately using fancy and barely replicable R coding, which is fun to look at but not too useful. They also do not use ggplot for their graphics and stay a bit too silent on how to practically conduct, interpret and report the instruments. It is still a decent book to work through the theoretical basics of multivariate statistics but can probably not replace watching countless YouTube tutorials and consulting step-by-step guides to actually carry out the analyses.

[Hannah · Rating 5 out of 5]

This is an excellent overview of multivariate techniques. Every topic is covered with appropriate depth. The chapter on visualizing multivariate data was particularly useful. The book is well written and very fun to read. They provide information about the math used for each approach and do an excellent job of explaining the math and the implications (e.g., whether/how scaling affects analyses). I particularly appreciated how carefully the chapters covered assumptions, caveats, and criticisms of techniques or analytic choice options and how they always directed interested readers to more detailed texts. The book doesn't cover MANOVA ("...we are not convinced that MANOVA is now of much more than historical interest...."!) or discriminant function analysis.

[Alireza Daneshvar · Rating 3 out of 5]

Multivariate techniques are well described in this book with R codes. It covers the main topics in multivariate analysis.

[Nancy · Rating 4 out of 5]

- Read Chapter 1-4, 8
- Skipped Chapter 6 Clustering
- Don't understand Chapter 5 and 7 on Factor Analysis

[Emil O. W. Kirkegaard · Rating 4 out of 5]

Decent but uses horrible plotting based on lattice or base. Authors should release a new version with ggplot2 versions.

[Bobu · Rating 4 out of 5]

Quick read. Good intro on Multivariate techniques. Covers only the basics. Focus on intuition and examples.