When only a single measurement is made from each individual (or unit) in a group, we cannot associate variation in that measurement with other characteristics of the individuals — all variation is unexplained.
When two or more measurements are made from each individual, we may be be able to associate variation in one measurement with changes in the other measurements; this can explain some of the variation. If two measurements are made from each individual, the data are called bivariate. Examples are ...
Our aim with such data is to find information about the relationship between the variables. New methods of graphical and numerical summary are required to capture this information.