ABSTRACT

Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used.

The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.

chapter 1|28 pages

The material of multivariate analysis

chapter 2|12 pages

Matrix algebra

chapter 3|12 pages

Displaying multivariate data

chapter 6|18 pages

Principal components analysis

chapter 7|18 pages

Factor analysis

chapter 8|24 pages

Discriminant function analysis

chapter 9|18 pages

Cluster analysis

chapter 10|22 pages

Canonical correlation analysis

chapter 11|16 pages

Multidimensional scaling

chapter 12|26 pages

Ordination

chapter 13|4 pages

Epilogue