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A Practical Approach to using Multivariate Analyses
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Using Multivariate Statistics, 6th edition provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics. This text’s practical approach focuses on the benefits and limitations of applications of a technique to a data set – when, why, and how to do it.
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Learning Goals
Upon completing this book, readers should be able to:
- Learn to conduct numerous types of multivariate statistical analyses
- Find the best technique to use
- Understand Limitations to applications
- Learn how to use SPSS and SAS syntax and output
- Sales Rank: #304568 in Books
- Brand: Brand: Pearson
- Published on: 2012-06-25
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x 2.20" w x 7.50" l, 4.04 pounds
- Binding: Hardcover
- 1024 pages
- Used Book in Good Condition
About the Author
Barbara Tabachnick is Professor Emerita of Psychology at California State University, Northridge, and co-author with Linda Fidell of Using Multivariate Statistics and Experimental Designs Using ANOVA. She has published over 70 articles and technical reports and participated in over 50 professional presentations, many invited.�� She currently presents workshops in computer applications in univariate and multivariate data analysis and consults in a variety of research areas, including professional ethics in and beyond academia, effects of such factors as age and substances on driving and performance, educational computer games, effects of noise on annoyance and sleep, and fetal alcohol syndrome.� She is the recipient of the 2012 Western Psychological Association Lifetime Achievement Award.
Most helpful customer reviews
94 of 96 people found the following review helpful.
Good How to Do Books
By Dr. R. Scott Evans
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.
46 of 48 people found the following review helpful.
nicely written applied book
By Michael R. Chernick
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.
35 of 38 people found the following review helpful.
Best of class for its clarity and usefulness
By Jared Freeman (jared@cog-tech.com)
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.
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