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Mathematical Tools for Applied Multivariate Analysis | 
 enlarge | Authors: J. Douglas Carroll, Paul E. Green
Creator: Anil Chaturvedi
Publisher: Academic Press
Category: Book
List Price: $67.95
Buy New: $50.35
You Save: $17.60 (26%)
New (12) Used (8) from $50.35
Avg. Customer Rating:  3 reviews
Sales Rank: 901014
Media: Paperback
Edition: Rev Sub
Number Of Items: 1
Pages: 376
Shipping Weight (lbs): 1.2
Dimensions (in): 8.9 x 6 x 1.1
ISBN: 0121609553
Dewey Decimal Number: 519.535
EAN: 9780121609559
ASIN: 0121609553
Publication Date: December 1, 1997
Shipping: Eligible for Super Saver Shipping
Availability: Usually ships in 24 hours
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| Editorial Reviews:
Product Description
This revised edition presents the relevant aspects of transformational geometry, matrix algebra, and calculus to those who may be lacking the necessary mathematical foundations of applied multivariate analysis. It brings up-to-date many definitions of mathematical concepts and their operations. It also clearly defines the relevance of the exercises to concerns within the business community and the social and behavioral sciences. Readers gain a technical background for tackling applications-oriented multivariate texts and receive a geometric perspective for understanding multivariate methods."Mathematical Tools for Applied Multivariate Analysis, Revised Edition illustrates major concepts in matrix algebra, linear structures, and eigenstructures geometrically, numerically, and algebraically. The authors emphasize the applications of these techniques by discussing potential solutions to problems outlined early in the book. They also present small numerical examples of the various concepts.
Key Features
* Provides a technical base for tackling most applications-oriented multivariate texts
* Presents a geometric perspective for aiding ones intuitive grasp of multivariate methods
* Emphasizes technical terms current in the social and behavioral sciences, statistics, and mathematics
* Can be used either as a stand-alone text or a supplement to a multivariate statistics textbook
* Employs many pictures and diagrams to convey an intuitive perception of matrix algebra concepts
* Toy problems provide a step-by-step approach to each model and matrix algebra concept
* Provides solutions for all exercises
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| Customer Reviews:
The mathematics of statistics October 10, 2008
A thorough treatment of the mathematical foundations of multivariate analysis. The book is full of graphical representations and a whole chapter is dedicated to a geometric interpretation of matrix operations. It starts out very softly with some basic matrix operations and from this it gradually extends the perspective to cover more complicated topics. I can highly recommend this book to anyone desiring a deeper understanding of what goes on behind the scenes of statical modelling.
Excellent book November 4, 2003
3 out of 3 found this review helpful
If you are in a situation like me, then this might be the best book. I read some introductory long ago at university. A few years from now I needed to refresh on the subject and get a little deeper. I have browsed or read some other books, but this is now my number one choice for reference. It starts very gently with e.g. spelled out examples on matrix addition. It ends with (by my standards) advanced topics like eigenstructures, quadratic forms, generalized inverses etc. I admire the writing style which is compact, precise and at the same time a little relaxed.
A great introduction to mathematics of statistical analysis December 6, 2001
7 out of 7 found this review helpful
There are a lot of people out there who do statistical analysis but who do not possess the mathematical knowledge underpinning a lot of what they are doing (i.e., linear algebra and some calculus). Most of the time people can get away with using stastical software as a sort of 'black box' and not worry about the math. But there are situations when having the background knowledge is crucial.This book does an excellent job of facilitating self-study of the math underpinning multivariate statistical analysis ... namely, linear (matrix) algebra and some calculus. Each chapter has a set of questions and ALL of the answers are provided in the book (handy for self-study). The one slight critique of this book I can give is that I wish the book did more on the calculus aspects. However, that is a minor comment and the knowledge that this book imparts of linear algebra to self-learners is extremely valuable.
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