Exploratory Multivariate Analysis by Example Using R

by François Husson, Sébastien Lê, Jérôme Pagès

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) a

262 pages, Kindle Edition

Published April 25, 2017

Reviews

[Terran M · Rating 2 out of 5]

The explanations in this book are terse and somewhat opaque. It comes across like the authors are trying their best to explain things without rigorous mathematics, but are the kind of people who think internally in formal math and don't really know any other way to explain things, so their attempt falls short. It provides neither the math which would explain the concepts to those who are mathematically inclined nor the words which would explain it to those who are not. The book presents itself as if principal components analysis is a basic technique to be introduced in the first chapter, but if you don't already understand what PCA does, I think you are unlikely to learn it from this explanation, and it's a required building block for understanding the other material.

Surprisingly, the online videos by the same author are much better than the book! I would recommend those instead for learning about correspondence analysis. If you want a general explanation of techniques such as PCA, I recommend the Hastie and Tibshirani books instead (or first), which are better written. If you want a book on correspondence analysis, I preferred Greenacre.