Applied Correspondence Analysis: An Introduction (Quantitative Applications in the Social Sciences) [Paperback]

Sten Erik Clausen (Author)

Book Description

ISBN-10: 0761911154 | ISBN-13: 978-0761911159 | Publication Date: June 1, 1998 | Edition: 1

This volume provides readers with a simple, non-technical introduction to correspondence analysis (CA), a technique for summarily describing the relationships among categorical variables in large tables. It begins with the history and logic of CA. The author shows readers the steps to the analysis: category profiles and masses are computed, the distances between these points calculated and the best-fitting space of n-dimensions located. There are glossaries on appropriate programs from SAS and SPSS for doing CA and the book concludes with a comparison of CA and log-linear models.

Product Details

• Paperback: 80 pages
• Publisher: Sage Publications, Inc; 1 edition (June 1, 1998)
• Language: English
• ISBN-10: 0761911154
• ISBN-13: 978-0761911159
• Product Dimensions: 8.4 x 5.4 x 0.2 inches
• Shipping Weight: 3.4 ounces (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #1,176,088 in Books (See Top 100 in Books)

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1 of 1 people found the following review helpful:

5.0 out of 5 stars Another excellent "Green Book" statistical guide., March 15, 2005

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Gaetan Lion - See all my reviews
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This review is from: Applied Correspondence Analysis: An Introduction (Quantitative Applications in the Social Sciences) (Paperback)

I am a big fan of this little "green book" statistical series. Thanks to it, I already taught myself Logit Regression, Cluster Analysis, Discriminant Analysis, and Factor Analysis. Most of these were excellent, and so is "Correspondence Analysis."

The author does an excellent job of developing a strong foundation in Correspondence Analysis in the first 25 pages of the book (out of 50 pages). Afterwards, he builds on this foundation by adding an introduction to Multiple Correspondence Analysis, and a comparison between Loglinear Models and Correspondence Analysis. These sections serve the purpose of what are the next steps you can explore after developing a solid base in Correspondence Analysis.

This green book series has allowed me to hang in there and keep up within an intense quantitative group of a major financial institution on the West Coast. Without them, I would have been left behind. For the record, I am an MBA type and not a quant type. So, if I can understand these books, so can you. I strongly recommend this one book in particular if you need to grasp this subject quickly.