Multivariate Analysis for the Behavioral Sciences, Second Edition

Praise for the first edition:

Clarity and conciseness have always been the hallmarks of Everitt’s writing. This book is no exception. Anyone looking for a clearly written text on the subject that is also practitioner oriented needs to look no further.
—Chuck Chakrapani, Journal of the Royal Statistical Society, Series A, 2012

… a clear, well-orchestrated guide to multivariate statistics for the post-graduate and professional behavioural scientist who possesses basic statistical knowledge. … Everitt successfully crafts a well-integrated introductory text that obviates potential difficulties by including real problems and their data sets. … the book’s applied orientation introduces the behavioural scientist to both the use and rudimentary understanding of multivariate techniques. … The book would also serve well as a training guide for the practitioner less experienced in multivariate techniques. …
—Psychometrika, June 2010

… The first two chapters give a magnificent introduction before approaching the modeling issues. Especially the second chapter, which shows how to look at data, is among the best I have ever seen in books on multivariate methods. … He also goes well beyond the typical graphs showing how to explore real insights of the data. … the book is extremely easy to browse and read. … Putting the R code in an appendix and on the website is an excellent choice. … the huge experience of the author … makes the presentation so clear and understandable. I’ll be happy to recommend this book to students and researchers.
—International Statistical Review, 2010

"Since there is always a shortage of multivariate statistical texts, it was uplifting to see a potential new text for the multivariate curriculum. As the authors state, this text goes far beyond the typical multivariate statistics text for psychologists or even statisticians. The text covers the spectrum of multivariate analysis (regressions, principal component analysis, exploratory/confirmatory factor analysis, structure equation modelling, clustering, correspondence analysis, multidimensional scaling, longitudinal data, and grouped multivariate data), as well as exploratory analysis with missing values and visualizations… The text provides a balance of history, theory, and interpretation of each method, while displaying most visualisations using R... I believe this edition of the text is a good start and future additions can make it an even greater text. For example, the online website provides a link to the GitHub Repository, which provides R syntax of the R visualisations and outputs for the examples provided in each chapter. Many students I teach find textbooks difficult if they do not show how to utilise the data and methods, but this text has done a great job at explaining the outputs and visualisations provided in each chapter... The text is great for providing a large breadth of knowledge of multivariate statistics for beginner or intermediate students with research questions involving advanced methods. Overall, I would recommend this book as a supplemental text for the classroom, or a handbook reference source for aspiring researchers with various backgrounds who are interested in learning about multivariate statistics and analysing them using R."
-Stephanie A. Besser, DePaul University, Chicago, Appeared in ISCB News, January 2020