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Reading and Understanding Multivariate Statistics | 
enlarge | Author: Laurence G. Grimm Creator: Paul R. Yarnold Publisher: American Psychological Association (APA) Category: Book
List Price: $29.95 Buy Used: $9.30 You Save: $20.65 (69%)
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Avg. Customer Rating: 8 reviews Sales Rank: 41763
Media: Paperback Edition: 1 Number Of Items: 1 Pages: 373 Shipping Weight (lbs): 1.5 Dimensions (in): 9.9 x 6.9 x 0.9
ISBN: 1557982732 Dewey Decimal Number: 001.4225 EAN: 9781557982735 ASIN: 1557982732
Publication Date: January 1995 Availability: Usually ships in 1-2 business days Shipping: Expedited shipping available Shipping: International shipping available Condition: Giving great service since 2004: Buy from the Best! 4,000,000 items shipped to delighted customers. We have 1,000,000 unique items ready to ship! Find your Great Buy today!
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| Editorial Reviews:
Product Description The book presents an overview of multivariate statistics and their place in research. It describes the appropriate context for -- and the types of empirical questions that can best be addressed by -- each technique or family of techniques, as well as the distribution assumptions that must be met for the analysis to be meaningful. The most commonly used multivariate techniques are examined in detail: multiple regression and correlation, path analysis, principal-components analysis, exploratory and confirmatory factor analysis, multidimensional scaling, analysis of cross-classified data, logistic regression, multivariate an alysis of variance (MANOVA), discriminant analysis, and meta-analysis. Statistical notations are explained, underlying assumptions are described, and terms are defined clearly and understandably. Concepts and symbols are presented with minimal use of formulas and a generous use of real-world research examples. Each chapter also includes suggestions for additional reading and a glossary of statistical and related terms.
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| Customer Reviews: Read 3 more reviews...
Excellent high-level overview June 7, 2007 This book is an excellent high-level overview of multivariate statistics and the techniques for working with multivariate data.
It doesn't go into detail making it a very good read for people wanting to learn multivariate concepts.
Reading and Understanding Multivariate Statistics by Grimm February 25, 2006 0 out of 8 found this review helpful
A good resource for someone taking a psyc stat class.
Fantastic Treatment of Sophisticated Mathemeatical Concepts November 5, 2004 12 out of 15 found this review helpful
I've long wanted a better explanation of Eigenvectors and Eigenvalues than I recieved in a econometrics or statistics textbook. This book gives me an incredibly clear understanding of what they are. Now when I look back at the mathematical interpretation again it means so much more. This is a fantastic book that would highly recommend to anyone wanting a clear conceptual understanding of these sophisticated topics. 5 stars, no questions about it!
Great Resource for Statistics August 7, 2003 14 out of 15 found this review helpful
In many introductory statistics courses you usually do not cover multivariate statistics. This book and its companion volume are useful for anyone in upper level undergraduate or graduate programs. It is a great reference to have when planning research.You can read it all at once to get a general understanding of this area or you can look at it as you need it as a reference. It was much better than the statistics books I have had as required reading in courses. It's a great resource overall!
I read it - and I understood it! November 1, 2002 38 out of 39 found this review helpful
"Reading and Understanding Multivariate Statistics" achieves exactly what its title implies. Geared toward non-statisticians in behavioral and social science fields, this book provides clear and reasonably simple explanations of some of the most common multivariate analyses. Each chapter focuses on a different analysis and presents its conceptual underpinnings, underlying assumptions, and basic procedures with a minimum of equations and many concrete examples. It does not teach you how to perform the analyses but does provide references for those who wish to get more detailed information. As a research scientist who doesn't always remember everything I learned in graduate statistics class, I find this book an invaluable aid keeping up with the current literature in my field and in making the most of statistical consultations. This book is ideal for anyone whose job requires them to be a "consumer" of research; for researchers who wish to further their understanding of data analysis; and as a companion text for graduate statistics classes.
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