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Multidimensional Scaling Paperback – Jan 1 1978

5 out of 5 stars 3 customer reviews

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Product Details

  • Paperback: 96 pages
  • Publisher: Sage Publications (Jan. 1 1978)
  • Language: English
  • ISBN-10: 0803909403
  • ISBN-13: 978-0803909403
  • Product Dimensions: 14 x 0.6 x 21.6 cm
  • Shipping Weight: 177 g
  • Average Customer Review: 5.0 out of 5 stars 3 customer reviews
  • Amazon Bestsellers Rank: #966,767 in Books (See Top 100 in Books)
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About the Author

Interests, Activities, Kudos multidimensional scaling minimum spanning trees clustering statistical linguistics Past President of the Psychometric Society Past President of the Classification Society of North America Fellow of ASA Fellow of AAAS


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Suppose you are given a map showing the locations of several cities in the United States, and are asked to construct a table of distances between these cities (see Figures 1A and 1B). Read the first page
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Top Customer Reviews

Format: Paperback
It is quite hard to find easy-reading reference for MDS. Some are written in Mathematics rather than in English. Others are over comprehensive as an introductory text for laymen. In this regard, I found Kruskal and Wish's "Multidimensional Scaling" to be the most 'user friendly'( only in a relative sense).
In short, this is certainly a monograph with just the right amount of substances for any applied researcher interested in MDS to get started with their work. Fundamental knowledge of statistics is a prerequisite, of course.
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Format: Paperback
This book is an excellent layman's introduction to the topic of Multi-Dimensional Scaling (MDS). There is just the right amount of detail to quickly get started in practical use of MDS. Some of the data and projects in this text are used as examples in StatSoft's Statistica software for PC's and Mac's; establishing a much needed connection between a reference text and software that incorporates the mathematics in the topic.
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Format: Paperback
It is an authoritative and well writen book. It is crear, didactically organized and covers all issues that are of interest for beginners. I use it in my graduate course on MDS, and students love it. The authors have been pioneers in the field and the first author is the creator of one of the most used software pieces in the field.
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: HASH(0xa3edf354) out of 5 stars 3 reviews
15 of 16 people found the following review helpful
HASH(0xa3eec4e0) out of 5 stars Excellent layman's introduction to Multi-Dimensional Scaling March 27 1998
By Scott Lake (scorae@juno.com) - Published on Amazon.com
Format: Paperback
This book is an excellent layman's introduction to the topic of Multi-Dimensional Scaling (MDS). There is just the right amount of detail to quickly get started in practical use of MDS. Some of the data and projects in this text are used as examples in StatSoft's Statistica software for PC's and Mac's; establishing a much needed connection between a reference text and software that incorporates the mathematics in the topic.
7 of 7 people found the following review helpful
HASH(0xa3eec63c) out of 5 stars An MDS monograph written for applied researchers May 28 2002
By VONG TZE NGAI - Published on Amazon.com
Format: Paperback
It is quite hard to find easy-reading reference for MDS. Some are written in Mathematics rather than in English. Others are over comprehensive as an introductory text for laymen. In this regard, I found Kruskal and Wish's "Multidimensional Scaling" to be the most 'user friendly'( only in a relative sense).
In short, this is certainly a monograph with just the right amount of substances for any applied researcher interested in MDS to get started with their work. Fundamental knowledge of statistics is a prerequisite, of course.
HASH(0xa3ef160c) out of 5 stars Can't go wrong with the little green Sage books! Nov. 28 2015
By basspiper - Published on Amazon.com
Format: Paperback Verified Purchase
I have at least 15 of the books in these Sage series. I've been accumulating them for years and still go back to most of them from time to time. Some are better than others but they are all excellent for what they're intended to be--a general introduction/overview for the given topic, with a lot of good explanation. You can't go wrong with these unless you are looking for an industrial-strength, highly technical treatment of your topic. The mathematics of the topics aren't ignored but they also aren't central. The books mostly contain narrative and explanation. Any of these little Sage books will get you a good start and, if you already know MDS, Correspondence Analysis, Logistic Regression or whatever, they still offer good information and ideas for explaining it to someone who doesn't (students, lay audiences for presentations, etc.).


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