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The analysis and interpretation of multivariate data for social scientists

By J. I. Galbraith, David J. Bartholomew, Irini Moustaki and Fiona Steele

Abstract

Based on a longtime course for master's level students at the London School of Economics and Politics, where the authors are based, this text concentrates on the multivariate methods so useful to social science problems involving correlational rather than causal relationships. Chapters with application examples and further readings cover data preliminaries, cluster analysis, multidimensional scaling, correspondence analysis, principal components analysis, factor analysis, and latent variable methods. While mathematical demands are minimal, these methods require use of a computer software package; an auxiliary website supplies data sets and code for use with SPSS

Topics: HA Statistics
Publisher: CRC Press
Year: 2002
OAI identifier: oai:eprints.lse.ac.uk:12923
Provided by: LSE Research Online
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