Geometric Data Analysis: From Correspondence Analysis to Structured Data Analysis

✍ Scribed by Brigitte Le Roux, Henry Rouanet (auth.)

• Publisher: Springer Netherlands
• Year: 2005
• Tongue: English
• Leaves: 483
• Edition: 1
• Category: Library

✦ Synopsis

Geometric Data Analysis (GDA) is the name suggested by P. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzécri as Correspondence Analysis, an approach that has become more and more used and appreciated over the years. This book presents the full formalization of GDA in terms of linear algebra - the most original and far-reaching consequential feature of the approach - and shows also how to integrate the standard statistical tools such as Analysis of Variance, including Bayesian methods. Chapter 9, Research Case Studies, is nearly a book in itself; it presents the methodology in action on three extensive applications, one for medicine, one from political science, and one from education (data borrowed from the Stanford computer-based Educational Program for Gifted Youth ). Thus the readership of the book concerns both mathematicians interested in the applications of mathematics, and researchers willing to master an exceptionally powerful approach of statistical data analysis.

✦ Table of Contents

Overview of Geometric Data Analysis (‘ Overview ’)....Pages 1-22
Correspondence Analysis....Pages 23-74
Euclidean Cloud....Pages 75-128
Principal Component Analysis....Pages 129-178
Multiple Correspondence Analysis ( MCA )....Pages 179-250
Structured Data Analysis....Pages 251-265
Stability of a Euclidean Cloud....Pages 269-296
Inductive Data Analysis....Pages 297-332
Research Case Studies....Pages 333-418
Mathematical Bases....Pages 419-449

✦ Subjects

Statistics, general; Economic Theory; Statistics for Life Sciences, Medicine, Health Sciences; Computational Linguistics; Sociology