Reading and Understanding Multivariate Statistics

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Title: Reading and Understanding Multivariate Statistics
ISBN: 1557982732
Author: Laurence G. Grimm
Publicate Date: 1995-01
Publish: 1995-01
List Price: $29.95
Average Customer Rating: 4.5
Format: Paperback

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Customer Review:

1: Excellent high-level overview 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.
2: Reading and Understanding Multivariate Statistics by Grimm A good resource for someone taking a psyc stat class.
3: Fantastic Treatment of Sophisticated Mathemeatical Concepts 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!
4: Great Resource for Statistics 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!
5: I read it - and I understood it! "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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