ABSTRACT
Principal component analysis (PCA) summarises a data table where the individuals are described by (continuous) quantitative variables. PCA is used to study the similarities between individuals from the point of view of all the variables and identifies individuals’ profiles. It is also used to study the linear relationships between variables (from correlation coefficients). The two studies are linked, which means that the individuals or groups can be characterised by the variables and the links between variables illustrated from typical individuals.
