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Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition Paperback – June 1, 1991

ISBN-13: 978-0942154917 ISBN-10: 0942154916 Edition: 2nd

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Product Details

  • Paperback: 303 pages
  • Publisher: Radius Press; 2nd edition (June 1, 1991)
  • Language: English
  • ISBN-10: 0942154916
  • ISBN-13: 978-0942154917
  • Product Dimensions: 0.8 x 6.2 x 9.2 inches
  • Shipping Weight: 1 pounds (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (28 customer reviews)
  • Amazon Best Sellers Rank: #143,902 in Books (See Top 100 in Books)

Editorial Reviews

About the Author

Sam Kash Kachigan is the author of several innovative books in mathematics and psychology, including "Multivariate Statistical Analysis," "Statistical Analysis," "The Sexual Matrix," "The Game," and "Over 100 Traits of Truly Horrible People." His books have been used in graduate programs at over 300 leading universities, in over a dozen different academic disciplines. He is also a prolific photographer and experimental filmmaker. As such, he is one of very few individuals to have made significant contributions to both the arts and sciences. He was born in Wisconsin of immigrant Armenian parents, and received his inter-disciplinary education at the University of Wisconsin, The University of Washington, and Columbia University.

Excerpt. © Reprinted by permission. All rights reserved.

Preface to the First Edition

This book is intended as an introduction to multivariate statistical analysis for individuals with a minimal mathematics background.

The presentation is conceptual in nature with emphasis on the rationales, applications, and interpretations of the most commonly used multivariate techniques, rather than on their mathematical, computational, and theoretical aspects. As such, the book is intended primarily not for the I reader in 100 who will go on to specialize in statistical analysis, but for the other 99 who will only obtain an overview of the subject, yet will have to deal in their professional lives with the design, analysis, and interpretation of research by interfacing with specialists in the field.

Although a prior course in elementary statistics would be beneficial, it is not absolutely essential, since the fundamentals are thoroughly reviewed in the first two chapters. Consequently, the book can be used either as an introductory or intermediate level text, and will also find use as a reference volume for those already in the professional community.

Since the principles of statistical analysis are perfectly general, cutting across all academic disciplines, students in all curriculums can use the text. This is especially true since much of the book is devoted to the discussion of concepts and principles rather than to specific examples. The illustrations that are used are drawn from three major areas-monetary disciplines, including business, economics, and government; behavioral disciplines, including education, psychology, sociology, anthropology, political science, and communications; and organic disciplines, including biology, medicine, and agriculture. Students of the physical sciences and engineering are advised to take a mathematical statistics course where they can capitalize on their backgrounds in calculus and matrix algebra, although such students can also benefit from the present approach.

I am grateful to the Literary Executor of the late Sir Ronald A. Fisher, F.R.S., to Dr. Frank Yates, F.R.S. and to Longman Group Ltd. .London, for permission to use Tables II, III, and IV from their book Statistical Tables for Biological, Agricultural and Medical Research (6th edition, 1974). I am also thankful to the dozens of individuals who made helpful comments at various stages of the manuscript. While many of the suggestions were heeded, I accept responsibility for any shortcomings that remain.

S.K.K. New York, New York October, 1981

Preface to the Second Edition

Aside from some minor textual changes, the main difference of this book from the initial 1982 edition is the addition of a chapter on Multidimensional Scaling. This chapter is taken from my 1986 textbook "Statistical Analysis: An Interdisciplinary Introduction to Univariate and Multivariate Methods," which is a more full-scale text, containing all the material in this edition plus a more thorough coverage of univariate, experimental design, multiple comparisons, time series, and probability topics, as well as providing student exercises.

Another new feature of this edition is its availability as an economical paperback. For many instructors the 1986 Statistical Analysis text - which is twice the length of this book - is too comprehensive for their particular curriculum needs, despite their desire to cover multivariate methods in an introductory manner. Consequently, this paperback edition will afford instructors greater flexibility in the design of their courses.

Not only will this edition serve as a basic introductory course in multivariate methods for the many students who do not have extensive mathematical backgrounds, but it will also complement those multivariate texts which are often too technical to fully benefit all the students enrolled in such courses.

Moreover, the conceptual approach of this book should prove to be a valuable guide for both graduate and undergraduate introductory courses, providing an integrated overview of the most useful analytical techniques that students are bound to encounter in their future studies and research activities.

S.K.K. New York, New York April, 1991


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Customer Reviews

4.7 out of 5 stars
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Miraculously witty and logical, the best statistical book I've ever read.
Hai Lu
It is easy to understand and clearly explained those statistic concepts and principles covered in this book.
Kate
This book helped me earn an A+ in advanced stats in the MBA that I am enrolled in.
"prd1"

Most Helpful Customer Reviews

22 of 22 people found the following review helpful By John C. Dunbar on May 29, 2001
Format: Paperback
This book is unlike most other statistics books in that it spends lots of time giving you the rationale behind the methods.
I found this to be very helpful. This was the book that helped fill in the blanks on other (college-style) texts. This is not an easy book to read. It is a clear and quick explanation of the logic behind multivariate statistics. Sometimes that logic is involved, but you can master it by reading more slowly.
I think after finishing this book, or in parallel with it, you would want another text that has lots of practical exercises.
Highly recommended... if you're one of those that wants to know the "why" behind the "what".
John D.
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17 of 17 people found the following review helpful By A Customer on June 8, 1996
Format: Paperback
Kachigan has successfully reduced his introduction to multivariate statistics to descriptive, if somewhat figurative, explanations of the ideas behind the subject, without constantly resorting to a formulas-only approach.Some authors make the mistake of forgetting what that key word in their title means--introduction: an explanation in terms understood by those unfamiliar with the subject.But Kachigan uses analogies and examples to explain the concepts of multivariate statistical analysis to the benefit of those who want to understand the concept before they attempt the practice. This is always the best way to learn ideas. Books that ignore the need to have a clear idea of why things are done do a disservice to those who study them. After reading Kachigan's direct and concise explanations, I wished that I had found him sooner. I intend to purchase his "Statistical Analysis: An Interdisciplinary Introduction to Univariate and Multivariate Methods" as a reference to occasionally check my own explanations of statistical methods in my research papers. My professors say that my understanding of these concepts seems to have improved. They should not be surprised--they recommended this book.
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17 of 17 people found the following review helpful By David Bell on December 13, 1999
Format: Paperback
Having spent the last couple of months trying in vain to find a book on Multivariate Analysis which doesn't assume a degree in mathematics. This book is absolutely wonderful! No assumptions are made, other than simple mathematical knowledge, thus making it a must for those researchers and scientists simply looking for some techniques for visualising high-dimensional data. A thoroughly worthwhile book and cheap at half the price!
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11 of 11 people found the following review helpful By "prd1" on November 26, 2001
Format: Paperback
I just wish he would write a new book and focus it around SPSS. Although the book was published long ago, it is written to those struggling in their Multivariate classes. It is very clear and concise. I could have read this in high school and understood every word. The book is not focused on linear algebra or higher level mathematics. Instead, he provides a clear conceptual understanding of the major techniques. If you read this much, buy the book and read it. I guarentee that in no time you will be asking your prof questions that will boggle his or her mind and you will score you some brownie points. Further, after reading it you will love the subject and study stats naked. Even if you decide not to keep this as a desk reference, you can always sell it to another student and use the cash to buy some beer. After reading this review, I only ask that you write Dr. Sam and tell him to keep writing. Tell him that we will revoke his Visa if he doesn't. I love you SAM. Peace to the world. Long live Dallas, TX! This book helped me earn an A+ in advanced stats in the MBA that I am enrolled in.
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7 of 7 people found the following review helpful By MAURICIO AGUIAR on August 7, 2003
Format: Paperback
If you need to learn or review basic statistical concepts this book will be a great help. It walks you through all the relevant material without tedious proofs or cryptic formulae. The book targets both the novice and the seasoned professional. Good for engineers, software measurement professionals, social scientists and all those who would like to learn about correlation, regression, ANOVA, discriminant analysis, factor analysis, etc. without going through heavy mathematics.
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9 of 10 people found the following review helpful By jdurham@tiger.fhsu.edu on April 11, 1999
Format: Paperback
Although now somewhat dated, this book remains the best general introduction to research-grade statistics for the nonspecialist. Kachigan has a special gift for giving intuitive motivations for difficult techniques. If supplemented by a good problem set, it provides the best available general survey for most MBA-level students, and should be readily accessible to undergraduates.
It would be really nice if it were brought up to date to accommodate tree-based methods, local regression, bootstrap, and several other "modern", computer-intensive techniques. Even so, it's my choice for my MBA class.
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5 of 5 people found the following review helpful By A Customer on July 19, 2004
Format: Paperback
Statistics can be pretty daunting and this book was hard going in the initial chapters, particularly on probability. The final chapters seem easier to understand. I think the author is right to have dealt heavily with the normal distribution. This book is a good place to begin an understanding of statistical methodology.
These days you don't really have to know too much about Stats, just something about using your favourite software and correctly interpretting the data and knowing if the tests you've used are correct. This book goes some way to help such analyses but does not have too much to say on software.
I also found the book a little too wordy at times - but it does try to summarise. More chapters and a greater breakdown could have helped.
The best thing about this book is the price and and at that price it can help you to feel cleverer/more confident than you may be at first. It may also help you understand truth a bit better.
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