ABSTRACT
Multiple correspondence analysis (MCA) is the factorial method adapted to tables in which a set of individuals is described by several qualitative variables. The same comments can be made about the contribution of an individual in MCA as in principal component analysis (PCA). In practice, as for PCA, MCA is almost always performed using supplementary elements. In MCA, qualitative variables are represented by the same number of points as of categories. The most important elements of the results of an MCA lie in the graphical representation in which each category is represented by a point, and the proximity between two points expresses a privileged association between the two corresponding categories. Also as in PCA, this overall visualisation of the relationships will be established from the synthetic quantitative variables used to construct the factorial planes.
