Multivariate Data Analysis (7th Edition) 7th Edition

Multivariate data analysis is a central tool whenever several variables need to be considered at the same time. The present book explains a powerful and versatile way to analyse data tables, suitable also for researchers without formal training in statistics.The analysis of multivariate data requires the extension of standard univariate statistical models and methods but also introduces new problems. Initial attention is given to Data Mining techniques such as summarising and displaying high dimensional data and to ways of reducing multivariate problems to more manageable univariate ones. This is followed by routine generalisations of standard distributions and statistical tests before consideration of new strategies for constructing hypothesis tests. Finally, problems specific to multivariate data such as discrimination and classification (use in medical diagnosis problems for example) are studied. Most of these methods can be implemented in standard computer packages.This book shows that multivariate analysis are:- Design for capability (also known as capability-based design)- Inverse design, where any variable can be treated as an independent variable- Analysis of Alternatives (A0A), the selection of concepts to fulfill a customer need- Analysis of concepts with respect to changing scenarios- Identification of critical design drivers and correlations across hierarchical levels.Thank you to Joseph F. Hair, Ronald L. Tatham, Rolph E. Anderson, William Black for their excellent job..make my research so easy. Every Phd should have this book.

This is my all time favorite stats book. It's very easy to read and yet is authoritative and comprehensive. The book is designed to promote a real understanding of the topic. Each chapter includes: glossary and quick overview at the beginning of the chapter, to orient the reader to the chapter; description of the theory; an application; example of programming code; summary. The writing style is clear and easy to follow. I first read this book in graduate school. I still turn to it as a refresher. If I could own only one multivariate book, this would be it.

I purchased this book as a textbook for a course in statistics. I have to say that this is hands-down the best statistics book I've ever read and the only one out of the pile of books I've purchased that I'm keeping as a reference. There is so much focus on how to choose the correct methods based on the types of data that you're working with - it's refreshing to read a book that's less focused on the math and more focused on the real-world applications.

This book is great to understand multivariate analysis, yet it is an extremely tough book to get through. I personally am not that great at statistics, so this book was a challenge to read and understand. I would recommend the author spend a little more time explaining book examples more thoroughly and step by step, since many concepts and "shortcuts" are not explained. When I do the exercises, I often tell myself, "Where the heck is he getting that from?" I needed it for my class, so I was forced to read it, but I feel the delivery of the material could have been better.

Be aware that this book is not the exact copy of the North American edition of the book. However, if you are looking for just the chapters on CFA and SEM, they are exactly the same as far as I can tell (looking at them side-by-side). This book is missing the chapter on GLM from the NA edition.

Everyone knows this is an amazing book. I like it. The reason why I gave three stars is the fact that I got a paper book after paying over $200. First I thought the publisher sent me a wrong copy. After checking the description, I realize what I got is the right one. Man.... there is not even a single figure in color. Seriously, this book looks like an illegal copy. Since I bought this book as a textbook, I don't have a choice. But, not so sure if I will use this for my class.

I lost my previous copy and this is a replacement. This is absolutely my favorite reference source on multivariate analysis. It is comprehensive and includes appropriate code for new researchers. Provides thorough information for all the major multivariate techniques.

This book was referred to me while I was writing the data analysis chapter of my dissertation. What a good find. I thought I understood multivariate analysis but this gives you practical and clear appliacations that make sense. A must reference if your work goes beyond the simple t-test.