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Correspondence Analysis in the Social Sciences
 
 
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Correspondence Analysis in the Social Sciences [Hardcover]

Michael Greenacre (Editor), Jörg Blasius (Editor)

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Book Description

0121045706 978-0121045708 October 5, 1994 1
Correspondence Analysis in the Social Sciences gives a comprehensive description of this method of data visualization as well as numerous applications to a wide range of social science data. Various theoretical aspects are presented in a language accessible to both social scientists and statisticians and a wide variety of applications are given which demonstrate the versatility of the method to interpret tabular data in a unique graphical way.

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Editorial Reviews

Review

"This volume is particularly noteworthy for the chapters stressing computations and historical perspectives. There are many interesting data sets as well as detailed analyses."
--JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

From the Back Cover

Correspondence analysis is a multivariate method for exploring cross-tabular data by converting such tables into graphical displays, called 'maps', and related numerical statistics. Since cross-tabulations are so often produced in the course of social science research, correspondence analysis is valuable in understanding the information contained in these tables.
This book fills the gab in the literature between the theory and practice of this method. Various theoretical aspects are presented in a language accessible to both social scientists and statisticians and a wide variety of applications are given which demonstrate the versatility of the method to interpret tabular data in a unique graphical way.
The first part of the book deals with basic concepts of correspondence analysis and related methods for analyzing cross-tabulations. It then looks at the multivariate case when there are several variables of interest, including the relationship to cluster analysis, factor analysis and reliability of measurement. Applications to longitudinal data: event history data, panel data and trend data are demonstrated. Finally, it examines further applications in the social sciences, including the analysis of textual data, lifestyle data and data on product descriptions in marketing research.
Correspondence Analysis in the Social Sciences gives lecturers, researchers and students a detailed introduction to help them teach the method and apply it to their own research problems. Researchers in psychology, sociology, business, marketing and statistics will all find this book particularly useful.

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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
latent budget model, super indicator matrix, display number dialled, natural grouping task, lodging status, point discriminant analysis, first row profile, dialling mechanism, reparametrization method, supplementary profiles, conjoint analysis results, display number calling, reconstitution formula, mean squared correlation, historic profiles, shortening trousers, simple correspondence analysis, asymmetric map, latent budgets, objectified cultural capital, row profiles, asymmetric scaling, explained inertia, multiple correspondence analysis, indicator matrices
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Scientific American, National Geographic, Response Axis, Sports Illustrated, The Netherlands, Rolling Stone
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