Geometric Data Analysis From Correspondence Analysis to Structured Data Analysis / by Brigitte Le Roux, Henry Rouanet.

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 for...

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Bibliographic Details
Main Authors: Le Roux, Brigitte (Author), Rouanet, Henry (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Dordrecht : Springer Netherlands : Imprint: Springer, 2005.
Edition:1st ed. 2005.
Series:Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.

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505 0 |a Overview of Geometric Data Analysis (‘Overview’) -- Correspondence Analysis -- Euclidean Cloud -- Principal Component Analysis -- Multiple Correspondence Analysis (MCA) -- Structured Data Analysis -- Stability of a Euclidean Cloud -- Inductive Data Analysis -- Research Case Studies -- Mathematical Bases. 
520 |a 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. 
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