Multivariate Data Analysis (6th Edition)

Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today — e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations.

I use it as a reference- to refresh myself on a technique, or to consult when I run into a problem- this book has yet to let me down and has been able to answer any question or solve any problem that I've had.

You see this book cited in academic behavioral research, but the book does a great job of explaining things in a managerial way as well.

Other of these reviews have criticized it for going on too long on an example or a technique- for that I PRAISE this book- I WANT that extra information. I'm reminded of that quote from "Amadeus"- "Too many notes." I WANT as many notes as I can get- that's what makes it so much more helpful.

If you are looking for a great reference book for multivariate techniques, look no further.


Great book   June 28, 2001
Wayne Parker (Scottsdale, AZ United States)
43 out of 44 found this review helpful

This is the best applied book on multivariate analysis I know. It clearly explains how to do statistical analyses and how to interpret the output. Clear examples throughout. Syntax supplied for each type of multivariate analysis in both SPSS and SAS, with LISREL notation for CFA. In addition to specific techniques (factor analysis, multiple regression, multiple discriminant analysis, MANOVA, conjoint analysis, canonical correlation, cluster analysis, multidimensional scaling, structural equation modeling/CFA) excellent sections on structuring data, cleaning data, and handling missing data. While mathematical sophistication always helps in stat, this book doesn't require it. No knowledge of matrix algebra needed to understand this book. Few if any formulas. Emphasis is on logic rather than math.


Sure it's good, and a good price by the pund too!   October 26, 2005
Tom Anderson (Stamford, CT United States)
5 out of 5 found this review helpful

A pretty good overview and a lot of in-depth material on Multivariate data analysis. Not quite a bed time read though.

I recommend this book as part of your analytical library.

If you liked this book, another good book on multivariate data analysis you may want to check out as well is Sharma, S.; Applied Multivariate Techniques, New York: John Wiley & Sons, Inc., 1996.

If you want something easier to read/more practical, and you prefer SPSS over SAS you may want to check out either `Discovering Statistics using SPSS for Windows' by Andy Field, or probably even better/simpler `SPSS Survival Manual' by Pallant.

Tom Anderson
Anderson Analytics, LLC
(...)


Good for a second stats course & reference   August 3, 2005
swingreen (Brooksville, FL United States)
3 out of 3 found this review helpful

We used this book for our Stats 2 course in grad school, and although our professor was good enough to eclipse Hair, et al. (he had written his own Stats text), I am most pleased at how much mileage I have drawn from Hair, et al. in the years since I took the course. In my subsequent career, reviewers have often sent me back to Hair, et al. when they have questions about something I'm doing with a data analysis, so it has become an invaluable reference for that reason alone.

The chapters on structural equation modeling, MANOVA, and factor analysis are particularly useful and well-written. I recommend this book without reservations for graduate students and others who work with advanced statistics as part of their daily work.


The Magic Multivariate Book   November 20, 1999
20 out of 20 found this review helpful

I've used this book (various editions) since graduate school -- more years ago than I care to admit. It is written in English rather than in "statistics" and gives a terrific conceptual overview of the research techniques. I keep it as a reference and use it regularly. If you want to understand multivariate stats without having to wade through a lot of symbols, this book is great. I also find it very useful when I'm trying to come up with a layman's explanation for management.