ABSTRACT
This chapter aims to devote multiple factor analysis (MFA). MFA is applied to tables in which a set of individuals is described by several sets of variables. The contribution of a group of variables is the sum of the projected inertias for the variables belonging to this group. Taking into account the distribution of inertia in such a way that it can be applied no matter how many variables there are, means considering the principal direction of inertia alone. Weighting by maximum axial inertia can be applied directly to groups of unstandardised variables. The representation of individuals and variables is therefore interpreted in the same way as in Principal component analysis (PCA). The only difference, but only compared to standardised PCA, is that the presence of weights for the variables implies that it is not possible to interpret the correlation circle in terms of the contribution of the variables.
