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Correspondence Analysis Handbook

Correspondence Analysis Handbook
Author: Benzecri
Publisher: CRC Press
Total Pages: 690
Release: 1992-01-22
Genre: Mathematics
ISBN: 9780824784379

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This practical reference/text presents a complete introduction to the practice of data analysis - clarifying the geometrical language used, explaining the formulae, reviewing linear algebra and multidimensional Euclidean geometry, and including proofs of results. It is intended as either a self-study guide for professionals involved in experimental research, or as a text for graduate level courses in multidimensional statistics.;The book features fully worked-out exercises, without the help of a computer, illustrating the constructions of correspondence analysis. It gives details of how to prepare, read and interpret computer results, including a complete FORTRAN program listing of the basic algorithms of factor analysis and classification. Sixteen case studies from medicine and biology, economics and the humanities, demonstrate a selection of data and interpretation of results. A foundation for agglomerative hierarchical clustering is provided.


Correspondence Analysis Handbook

Correspondence Analysis Handbook
Author: Benzecri
Publisher: CRC Press
Total Pages: 684
Release: 1992-01-22
Genre: Mathematics
ISBN: 058536303X

Download Correspondence Analysis Handbook Book in PDF, ePub and Kindle

This practical reference/text presents a complete introduction to the practice of data analysis - clarifying the geometrical language used, explaining the formulae, reviewing linear algebra and multidimensional Euclidean geometry, and including proofs of results. It is intended as either a self-study guide for professionals involved in experimental


Multiple Correspondence Analysis for the Social Sciences

Multiple Correspondence Analysis for the Social Sciences
Author: Johs. Hjellbrekke
Publisher: Routledge
Total Pages: 118
Release: 2018-06-18
Genre: Social Science
ISBN: 1315516241

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Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930–2002). This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own.


Correspondence Analysis in the Social Sciences

Correspondence Analysis in the Social Sciences
Author: Michael Greenacre
Publisher: Academic Press
Total Pages: 400
Release: 1994-09-21
Genre: Business & Economics
ISBN:

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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.


Multiple Correspondence Analysis and Related Methods

Multiple Correspondence Analysis and Related Methods
Author: Michael Greenacre
Publisher: CRC Press
Total Pages: 607
Release: 2006-06-23
Genre: Mathematics
ISBN: 1420011316

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As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the su


The Oxford Handbook of Quantitative Methods in Psychology: Vol. 2

The Oxford Handbook of Quantitative Methods in Psychology: Vol. 2
Author: Todd D. Little
Publisher:
Total Pages: 785
Release: 2013-03-21
Genre: Psychology
ISBN: 0199934894

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The Oxford Handbook of Quantitative Methods in Psychology provides an accessible and comprehensive review of the current state-of-the-science and a one-stop source for learning and reviewing current best-practices in a quantitative methods across the social, behavioral, and educational sciences.


Multiple Correspondence Analysis

Multiple Correspondence Analysis
Author: Brigitte Le Roux
Publisher: SAGE
Total Pages: 129
Release: 2010
Genre: Mathematics
ISBN: 1412968976

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"Requiring no prior knowledge of correspondence analysis, this text provides anontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte Le Roux and Henry Rouanet, present the material in a practical manner, keeping the needs of researchers foremost in mind." "This supplementary text isappropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as forindividual researchers." --Book Jacket.


The Oxford Handbook of Pierre Bourdieu

The Oxford Handbook of Pierre Bourdieu
Author: Thomas Medvetz
Publisher: Oxford University Press
Total Pages: 689
Release: 2018-04-02
Genre: Social Science
ISBN: 0190874619

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Pierre Bourdieu was one of the most influential social thinkers of the past half-century, known for both his theoretical and methodological contributions and his wide-ranging empirical investigations into colonial power in Algeria, the educational system in France, the forms of state power, and the history of artistic and scientific fields-among many other topics. Despite the depth and breadth of his influence, however, Bourdieu's legacy has yet to be assessed in a comprehensive manner. The Oxford Handbook of Pierre Bourdieu fills this gap by offering a sweeping overview of Bourdieu's impact on the social sciences and humanities. Thomas Medvetz and Jeffrey J. Sallaz have gathered a diverse array of leading scholars who place Bourdieu's work in the wider scope of intellectual history, trace the development of his thought, offer original interpretations and critical engagement, and discuss the likely impact of his ideas on future social research. The Handbook highlights Bourdieu's contributions to established areas of research-including the study of markets, the law, cultural production, and politics-and illustrates how his concepts have generated new fields and objects of study.


Correspondence Analysis and Data Coding with Java and R

Correspondence Analysis and Data Coding with Java and R
Author: Fionn Murtagh
Publisher: CRC Press
Total Pages: 256
Release: 2019-08-30
Genre:
ISBN: 9780367392734

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Developed by Jean-Paul Benzérci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater than ever. Correspondence Analysis and Data Coding with Java and R clearly demonstrates why this technique remains important and in the eyes of many, unsurpassed as an analysis framework. After presenting some historical background, the author presents a theoretical overview of the mathematics and underlying algorithms of correspondence analysis and hierarchical clustering. The focus then shifts to data coding, with a survey of the widely varied possibilities correspondence analysis offers and introduction of the Java software for correspondence analysis, clustering, and interpretation tools. A chapter of case studies follows, wherein the author explores applications to areas such as shape analysis and time-evolving data. The final chapter reviews the wealth of studies on textual content as well as textual form, carried out by Benzécri and his research lab. These discussions show the importance of correspondence analysis to artificial intelligence as well as to stylometry and other fields. This book not only shows why correspondence analysis is important, but with a clear presentation replete with advice and guidance, also shows how to put this technique into practice. Downloadable software and data sets allow quick, hands-on exploration of innovative correspondence analysis applications.