Multivariate Statistical Analysis: A Conceptual Introduction

by Sam Kash Kachigan

Book Overview

This classic multivariate statistics book has become the introduction of choice for researchers and students with a minimal mathematics background. In addition to providing a review of fundamental... This description may be from another edition of this product.

• Format: Paperback
• Language: English
• ISBN: 0942154916
• ISBN13: 9780942154917
• Release Date: June 1991
• Publisher: Radius Press
• Length: 303 Pages
• Weight: 1.03 lbs.
• Dimensions: 0.7" x 6.2" x 9.0"

Customer Reviews

Yo Baby, Sammy is Da' Hoochie Daddy

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.

Great at giving rationale behind the methods

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.

Multivariate Statistical Analysus

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!

Outstanding, intuitive introduction to applied statistics

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.

An intuitive introduction--not strictly mathematical.

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.