A large number of statistical methods are aimed at the analysis of different measurements or variables in an independent fashion. These methods are referred to as univariate methods.
Multivariate methods, on the other hand, allow the simultaneous analysis of a dataset for exploring its overall structure, for measuring redundancy in the measurements, for summarizing the salient features of a stufy, for forming groups of objects or individuals with common characteristics.
Training sessions in this module offer an overview of various multivariate methods, some popular and others less known, some classical as well as more recent ones. Emphasis is put on the context of use, the information obtained and methods are exemplified with an array of case studies from several fields of application.
