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Matrix Algebra Useful for Statistics

Download Matrix Algebra Useful for Statistics

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From the Back Cover

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book is intended to teach useful matrix algebra to 'students, teachers, consultants, researchers, and practitioners' in 'statistics and other quantitative methods'.The author concentrates on practical matters, and writes in a friendly and informal style . . . this is a useful and enjoyable book to have at hand." —Biometrics This book is an easy-to-understand guide to matrix algebra and its uses in statistical analysis. The material is presented in an explanatory style rather than the formal theorem-proof format. This self-contained text includes numerous applied illustrations, numerical examples, and exercises.

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About the Author

SHAYLE R. SEARLE, PhD, is Professor Emeritus of Biometry at Cornell University. He is the author of Linear Models, Linear Models for Unbalanced Data, and Generalized, Linear, and Mixed Models (with Charles E. McCulloch), all from Wiley.

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Product details

Paperback: 476 pages

Publisher: Wiley-Interscience; 1 edition (March 20, 2006)

Language: English

ISBN-10: 0470009616

ISBN-13: 978-0470009611

Product Dimensions:

6.2 x 1 x 9.2 inches

Shipping Weight: 1.3 pounds (View shipping rates and policies)

Average Customer Review:

4.1 out of 5 stars

8 customer reviews

Amazon Best Sellers Rank:

#1,767,661 in Books (See Top 100 in Books)

This book covers a lot of materials that will contribute to a solid understanding of matrix algebra. I would, by all means, recommend this book, but would still like to point out some weaknesses:1. Unattractive page layout. Page after page of dull looks. Need more visuals; I don't mean colorful graphics but black-and-white diagrams and geometric interpretations.2. From time to time, I felt like the author would give examples only on easy-to-understand topics, but avoid giving examples on difficult-to-understand ones. That didn't make sense to me.3. Proofs should be more clearly presented. It seems like the author is always in a hurry to just get the job done. I guess it was designed for uninterested readers to simply skip the proofs without making them feel they have skipped over a lot of materials. However, for an interested reader like me, who isn't particularly strong in proofs, it was a disfavor.4. Illustration topics could be more diverse. For instance, there are too many illustrations dealing with genetics. I would appreciate more everyday examples, like the taxi one.Again, I would strongly recommend this book, despite what I think are its weaknesses.

I agree with all of the positive reviews I have seen before. (They partly influenced my decision to buy the book.) I already had a good background in linear algerbra and statistics but was looking for something that did a clear job of connecting the two. I really wish I had this book when I was in grad school. The book has a nice balance between rigorous proof and conceptual discussion. The examples and exercises at the end of the chapters are very engauging and instructive. The book also does a nice job early on of anticipating matrix computations that will be useful later in the book and for statistical computations in general. My only critique is that there are no hints or answers keys for the problems but this is very minor. The book is so well laid out that the text and exercises fit together very tightly. I highly recommend this book and will be going back to it often.

I'm methodically working through ALL the example problems in this textbook with the goal of firming up my understanding of matrix algebra and -ultimately- statistics. Currently on chapter 3 but I've been impressed thus far with the clarity of explanations and organization of the material. As a statistician myself, I'm certain this will be a valuable reference and resource for me in my work.

"This book is adressed to people of limited ability or training in mathematics and is an attempt to keep the mathematical presentation as informal as possible." At least according to the preface of the book.I do not think the author has succeeded in this selfproclaimed goal. In some chapters - which I consider core chapters - results are simply offered as theorems and then proved without any comment on the significance of the result. Theres a lack of a unified approach, where new concepts are linked to old ones whenever possible, and the notation is at times inconsistent both within and across chapters. Simple matters are presented in a complicated fashion perhaps to save space. The chapters on statistical application - particularly regression - did not impress me since I have seen appendices in stat books treat the matrix algebra with more insight rather than the dry computational fashion which seems to be the drive of this book.Considering the amount of books available on linear algebra I find this book way too expensive and too dense to be worth the time.To me this was not the hoped for bridge from linear algebra to a deepened understanding of the math behind in my case regression.

Being a student of Health Economics, Statistics and Mathematical Epidemiology modeling, i have fumbled enough to understand matrix algebra.But its until i got this book; "Matrix Algebra Useful for Statistics" is when i stopped buying more books.Simply said, THIS IS THE BEST BOOK EVER WRITTEN to help you form a foundational understanding of Matrix Algebra that will make you understand ANY OTHER BOOK on matrix algebra. period

For someone who almost failed basic math, having to learn something as mad as matrix algebra from scratch for a thesis is no mean feat. This book is brilliantly written, with step by step easy to follow explanations and instructions as well as really good practice questions/ exercises to complete to help with understanding the material. Who would I recommend it to? Anyone needing a really good grasp of matrix algebra to use for animal breeding purposes!

Excellent book for students beginning graduate study in Statistics. Would recommend this book over most. I have several in related topics. If you're new to proofs, this book has great explanations behind many crucial proofs to understanding material at this level.

This is an excellent introductory book, although mostly oriented to people with a reasonably good mathematical background. Searle covers most, if not all, the matrix algebra that you may need to fully understand applications of mixed linear models. Chapters one to eight cover the essential operations (addition, multiplication, determinants, etc) as well as more advanced concepts (rank, canonical forms, inverse, etc). The rest of the book (chapters nine to fifteen) covers applications to statistics as well as advanced topics that can help you to understand how do some of the statistical packages work inside. The only mathematics book that I have read from cover to cover. Definitively a classic.

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