Multiple Correspondence Analysis for the Social Sciences

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A01=Johs. Hjellbrekke
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Analysis
ascending hierarchical cluster analysis
asymmetrical maps
Author_Johs. Hjellbrekke
automatic-update
Barycentric Coordinate System
binary indicator matrix
Bourdieu
categorical data analysis
Category1=Non-Fiction
Category=JHB
Category=PBT
centroids
clouds of points
cluster analysis methods
coding principles
Column Categories
Concentration Ellipse
COP=United Kingdom
Correspondence Analysis
data visualisation techniques
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EGP Class
eq_bestseller
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Factor Coordinate
Factorial Plane
Father's Social Class
Father’s Social Class
French Academic Field
Geometric Data Analysis
geometric technique
Global Cloud
Guttman Effect
Hjellbrekke Johs
Interclass Variance
interpretation
Intraclass Variance
Johs. Hjellbrekke
Language_English
Low Dimensional Solution
modified inertia rates
multidimensional social space mapping
Multiple Correspondence
Multiple Correspondence Analysis
PA=Available
Passive Categories
Price_€20 to €50
PS=Active
Row Categories
Simple Correspondence Analysis
Social Sciences
social stratification research
societal perceptions
softlaunch
squared cosines
statistical details
Structured Data Analysis
symmetrical maps
Total Inertia
transition equations
Tv Preference
typology construction
USA's Position
USA’s Position
variance decomposition
Vice Versa
Ward's Criterion
Ward’s Criterion

Product details

  • ISBN 9781138699717
  • Weight: 222g
  • Dimensions: 156 x 234mm
  • Publication Date: 20 Jun 2018
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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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.

Johs. Hjellbrekke is Professor of Sociology at the University of Bergen, Norway, and Director of the Norwegian University Centre in Paris, FMSH. His research interests are in social stratification, class analysis, social mobility, the sociology of elites, geometric data analysis and statistical analysis of categorical data. Since 1995, he has taught courses in multiple correspondence analysis at more than 15 different universities.

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