Customer Reviews

Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition

5 star:		(18)
4 star:		(2)
3 star:		(3)
2 star:		(0)
1 star:		(0)

 

 

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.

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!

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.

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.

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.

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.

I am enrolled in a Risk Management course. Without any previous statistics courses I was struggling. My professor recommended this book and it changed everything for me. I was actually able to learn and understand statistics from the beginning to multivariate analysis from this book. It made it so very plain and simple. I am now successfully going forward again. I would recommend this to anyone from beginner to Masters level who needs a reference at hand.

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.

I liked this book for the excellent examples and figures that the author has given with the explanation. I liked this book so much that I am ordering the other (more advance) book by this author. It think it is a great idea to write a "conceptual introduction" book (such as this) on a subject and accompany it with a more advance book on the same subject. Kachigan has done just that.

I agree with many of the comments other reviewers have offered. It's a solid book--clear, organized, visually fairly effective, and occasionally interesting. But since it goes into decision points or applied examples so seldom, and almost never in any depth, I kept coming away from the self-contained chapters with a feeling that something was lacking.

It may well serve as one of your more important reference books, but I doubt it will be your preferred source on any topic.