The study of multiple measurements on a sample. It embraces many techniques related to a range of different problems.

Cluster analysis seeks to define homogeneous classes within the sample on the basis of the measured variables. Discriminant analysis is a technique for deciding whether an individual should be assigned to a particular predefined class on the basis of the measured variables. Principle component analysis and factor analysis aim to reduce the number of variables in the study to a few (say two or three) that express most of the variation within a sample.

Multivariate probability distributions define probabilities for sets of random variables.