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Geometric Data Analysis - From Correspondence Analysis to Structured Data Analysis (Hardcover, 2004 ed.): Brigitte Le Roux,... Geometric Data Analysis - From Correspondence Analysis to Structured Data Analysis (Hardcover, 2004 ed.)
Brigitte Le Roux, Henry Rouanet
R3,158 Discovery Miles 31 580 Ships in 10 - 15 working days

Geometric Data Analysis (GDA) is the name suggested by P. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by BenzA(c)cri 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.

Geometric Data Analysis - From Correspondence Analysis to Structured Data Analysis (Paperback, Softcover reprint of hardcover... Geometric Data Analysis - From Correspondence Analysis to Structured Data Analysis (Paperback, Softcover reprint of hardcover 1st ed. 2004)
Brigitte Le Roux, Henry Rouanet
R2,936 Discovery Miles 29 360 Ships in 10 - 15 working days

Geometric Data Analysis (GDA) is the name suggested by P. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzecri 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.

Les modeles stochastiques d'apprentissage (French, Hardcover, Reprint 2017 ed.): Henry Rouanet Les modeles stochastiques d'apprentissage (French, Hardcover, Reprint 2017 ed.)
Henry Rouanet; Foreword by J -M Faverge
R3,555 Discovery Miles 35 550 Ships in 12 - 19 working days
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