Cluster Analysis for Researchers

Back in print at a good price. To see the many websites referencing this book, in Google enter "cluster analysis" (in quotes) and Romesburg. Headlines of 5-star reviews on Amazon.com: "A very clear 'how to' book on cluster analysis" (C. Fielitz, Bristol, TN); "An excellent introduction to cluster analysis" (T. W. Powell, Shreveport, LA). A recent (2004) review in Journal of Classification (21:279-283) says: "We should be grateful to the author for his insistence in bringing forth important issues, which have not got yet that level of attention they deserve. I wish this journal could devote more efforts in promoting the scientific inquiry and discussions of methodology of clustering in scientific research [as Cluster Analysis for Researchers does]." To see or search inside the book, go to www.google.com, type in the book's title, and click on it when it comes up (or copy and paste in your browser's window the following URL: http://print.google.com/print?isbn=1411606175 ).

Customer Reviews:

An excellent introduction to cluster analysis

By Thomas W. Powell - September 27, 2004

I first ran across Romesburg's "Cluster Analysis for Researchers" when I was designing my dissertation. Unlike most books on multivariate statistics, this volumee spoke to me in a language I could understand. The author assumes no previous knowledge of the topic, and does a fine job of providing the reader with a framework. Examples are clear and well chosen.

For years, I looked for a reasonably priced copy of this book for my personal library. I'm thrilled that it is in print again. This paperback edition is published by www.lulu.com and is faithful to the original version. It is highly recommended as an introduction to cluster analysis.

Not my taste of a book

By N. Jespersen - May 10, 2008

I dont like this book. I find its structure confusing and its layout very unattractive (no margins!). I have used it with some similar book, and every time a have tried to look for some topic in this book i found it failed (or at least did at bad job).

I recomment B.S Everitt, Cluster Analysis for an overview, and Gan, Ma And Wu: Data clustering, theory, algoritms and applications for at very comprehensive how-to guide for the many different methods.

Oldie but Goodie

By Maggiexyz - January 27, 2008

I originally borrowed this book from a library rather than bought it because I was worried that the book was published before the PC age and wouldn't cover modern clustering methods. That concern is legitimate--the book didn't even mention K-means. But the author did a great job explaining the logic behind cluster analyses. There are many subjective choices to make in performing a cluster analysis, with or without the aid of modern computing powers. The author highlighted the aspects of consideration when facing such choices, for example, why one would want to standardize the data matrix, what properties the (myriad) similarity coefficients have. The explanations are clear and to the point. I feel that I now know enough about what I need/what a cluster analysis can do, that I can decide with reasonable confidence which clustering methods out there may be appropriate for my analyses. I'm now buying the book for future reference.