Customer Reviews

Using Multivariate Statistics (4th Edition)

5 star:		(13)
4 star:		(4)
3 star:		(1)
2 star:		(1)
1 star:		(0)

 

 

I have used earlier versions of this book throughout my professional life. It is a handy quick reference for the more advanced practitioner who wants to explore techniques that they have not used before. Or, to refresh one's memory on techniques that have not been used for awhile. This book is also very useful for training junior practitioners in multivariate techniques. There is enough detail to satisfy those asking more detailed questions about techniques without overwelming those less inclined to pore over mathematical formula. Steps and tests are well laid out, with enough discussion so that the reader understands the value and importance of working through the standard routines and assumption checks. It also offers important pratical steps in how to design and run specific statistical procedures in the common statistical packages.

Given the increasingly user-friendly statistical software on the market, this book offers a quick antidote for the rising number of button pushers, by showing budding statisticians the implications of using a technique ignorantly. This is done without making the technique inscrutable to the reader.

While the new edition offers some additional information - the cost conscious buyer could easily find considerable value in older editions.

Many statistical books, particularly multivariate ones,are, - let's face it- boring, heavy-going and ugly. Formulae are used as if to terrify and frighten, not to illustrate or show, and textual passages are all too often chock full of outright fibs such as 'it will be clear that', or, 'the reader will see that' or - a sure sign that something truly monstrous is to follow - 'it is obvious that'. Not so Tabachnick and Fidell's great book. Everything is clear and well set-out, with lots of real examples. Unlike many textbooks, it does not assume that you got your data out of a textbook, it shows how to analyze real data, how to check statistical assumptions and what to do about violations of those assumptions. Although some of the information on statistical packages may now be a little dated, the program inputs and outputs are supplied, as are written-up reports of the results, similar to how they would appear in a socio-behavioral journal. I've been using the various three editions of this truly wonderful book since 1985 and think it should be on the desk of every professional, aspiring or sometime data analyst or statistician!

This is a very nicely written and popular text on applied multivariate analysis. It does not provide theory but teaches how to use and interpret results from software packages. It has a good set of examples.

Tabachnick & Fidell have produced that rare thing, a technical tome that is helpful to junior and senior statisticians, and that is even fun, at times. I've used the 2nd edition of this text since it came out in 1989, during my student days and, now, professionally. It is the first place I turn when I need a clear review of data screening techniques, when I am debating the merits of one analytic approach over another, when I need to understand the fundamental formulas underlying a technique, and when I want to see how others have written up data from the technique I've selected. The structure of the book is particularly helpful in addressing these questions; there is a chapter on most of the common statistical techniques, and each chapter has sections describing the research questions for which the technique is appropriate, limitations of the approach, its fundamental equations, miscellaneous issues, a comparison of programs (which becomes dated too quickly, of course), and examples. All of these comments concern the 2nd edition, but I'll make the wild assumption that the authors have retained the structure and improved the content in the 3rd edition...and I'll buy it.

This book is a classic. It is the first major purchase you should make for multivariate techniques. In my opinion, it is not a theoretical book, yet it is not a cookbook either. For novices, it provides enough rigor and theory to prevent one from having too many unanswered questions. However, it does not bombard the reader with so much theory that practicality is lost. It's a great way to begin looking at multivariate stats. If your research necessitates deeper analysis, you can find it in other books, but without an adequate foundation, such as that provided for by this book, it will be difficult to tackle more advanced texts. The book costs too much, which is a drawback. It is a shame that books are getting in the ridiculous category for pricing. With that said, this is a book that you will be able to keep for quite a while. The techniques presented are durable and the conepts are timeless for the most part. New statistical methods that are currently being developed are generally available in small booklets ...for cheap prices. Reading this text will make most of those 'new' methods understandable. So, in that regard, it may be a good purchase. But, your best bet is to hit the college bookstore a week before the semester to find a used copy in excellent condition. For the reviewer from Brazil, he should put down the thesaurus and re-read the book. For the rest of us, let's be thankful for people like that for they often return these books to the bookstore in a huff of frustration, with the books barely opened and ripe for the taking at a used price. Great text, should stay on your shelf for years, just try to find a good deal on one.

There's a reason why some students leave out the first and soften the second 't' in the word 'statistics'. Well, not if working with this book.
Doing a lot of multivariate analyzes in the course of my research and teaching research-methods to graduate students, I repeatedly find this book a treasure I would not want to do without. The advice is well organized, hands-on with guidelines to follow and explanations on how to run and interpret analyzes in SPSS, it's sufficiently detailed (though not overbearingly so) and quite complete, and clearly written and easy to understand (honestly, whoever tells you differently hasn't read any of the alternatives).
Yes, the price is scary - unfortunately, since that price is the only thing keeping this book from being a best-seller and a student-favourite. However, if you plan on doing any multivariate stats for a little bit longer than a few months (longer than your University Library will be happy to lend this book to you, that is), it pays off. This book is excellent, and often, after searching through my SPSS handbooks, my Stevens and Cohens (all very good books themselves), I return to this one, finally finding the information I need, and in the digestible format that I need. A definite keeper.

This is a wonderful book that includes examples from major software packages. It is easy to read and understand. I used this book in an independent study class for my graduate degree. Although I only met with the teacher a few times, I had a thorough understanding of multivariate statistics because of this book.

This is the 'statistical bible' for graduate students or professors performing multivariate statistics in their research. It explains every concept, provides examples, and explains different statistical programs. All of this information is provided in easy to understand terminology. It is worth the steep price tag because I use it all the time. As a researcher, I perform multivariate stastics frequently and this book is a great resource.

As a statistician, this is the book I turn to when I have to analyze (real) multivariate, continuous data. I've never seen anything that equals it. And, it helps me discuss the technical issues more easily with clients because I find straightforward explanations that I would have a hard time coming up with on my own. I've been using the book since 1989 (2nd edition).

The 5th edition of this popular book is, in my opinion, marred by a large number of errata (see the book's web page.) While it is common for technical books to have errata, I must raise some doubts about how carefully the book was "proofed." Needless to say, this is not exactly confidence inspiring.