Article | REF: AF620 V1

Data analysis or multidimensional exploratory statistics

Authors: Philippe BESSE, Alain BACCINI

Publication date: April 10, 2011

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1. Prolegomena

1.1 Contents

The methods listed for data analysis fall into two groups (factorial and classification), depending on their purpose and the nature of the variables considered (quantitative or qualitative).

  • Various factorial methods can be deduced from principal component analysis or PCA (p quantitative variables): factorial correspondence analysis (FCA) (2 qualitative variables), multiple correspondence analysis (MCA) (p qualitative variables), discriminant factorial analysis (one qualitative variable and p quantitative variables), multidimensional positioning (distance table), canonical correlation analysis (p and q quantitative variables). This last method, much less widely used, is not described in this article. PCA is therefore given...

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Prolegomena