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Multiple correspondence analysis (MCA) is a method of analyse des données used to describe, explore, summarize, and visualize information contained within a data table of N individuals described by Q categorical variables. This method is often used to analyse questionnaire data. It can be seen as an analogue of principal components analysis (PCA) for categorical variables (rather than quantitative variables) or even as an extension of correspondence analysis (CA) to the case of more than two categorical variables. The main objectives of MCA can be defined as follows:(1) to provide a typology of the individuals, that is, to study the similarities between the individuals from a multidimensional perspective;(2) to assess the relationships between the variables and study the associations between the categories; and (3) to link together the study of individuals and that of variables in order to characterize the …