1. A method of generating a reduced dimension data set Dnew of dimension m×k, m rows and k columns, from an original data set D of dimension m×n, m rows and n columns, wherein n>k by selecting a subset of k columns from a set of n columns in the original data set D where the m rows correspond to observations Ri where i&equals;1,..., m and the n columns correspond to attributes Aj where j&equals;1,..., n and dij is the data value associated with observation Ri and attribute Aj wherein the data values in the reduced data set Dnew for each of the selected k attributes is identical to the data values of the corresponding attributes in the original data set, the steps of the method comprising: a) for each of the attributes Aj in the original data set D, calculating a variance value of data values dij, i&equals;1,..., m, associated with the attribute Aj; b) selecting the k attributes having the greatest variance values; and c) generating the reduced data set Dnew by selecting data values from the original data set D corresponding to the selected k attributes.