This volume provides readers with a simple, non-technical introduction to correspondence analysis (CA), a technique for summarily describing the relationships among categorical variables in large tables. It begins with the history and logic of CA. The author shows readers the steps to the analysis: category profiles and masses are computed, the distances between these points calculated and the best-fitting space of n-dimensions located. There are glossaries on appropriate programs from SAS and SPSS for doing CA and the book concludes with a comparison of CA and log-linear models.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This volume provides readers with a simple, non-technical introduction to correspondence analysis (C.A.), a technique for summarily describing the relationships among categorical variables in large tables. It begins with the history and logic of C.A. The author shows readers the steps to the analysis: category profiles and masses are computed, the distances between these points calculated and the best-fitting space of n-dimensions located. There are glossaries on appropriate programs from S.A.S. and S.P.S.S. for doing C.A. and the book concludes with a comparison of C.A. and log-linear models.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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