  Galaxy diversification proceeds by transforming events like accretion,
interaction or mergers. These explain the formation and evolution of galaxies
that can now be described with many observables. Multivariate analyses are the
obvious tools to tackle the datasets and understand the differences between
different kinds of objects. However, depending on the method used,
redundancies, incompatibilities or subjective choices of the parameters can
void the usefulness of such analyses. The behaviour of the available parameters
should be analysed before an objective reduction of dimensionality and
subsequent clustering analyses can be undertaken, especially in an evolutionary
context. We study a sample of 424 early-type galaxies described by 25
parameters, ten of which are Lick indices, to identify the most structuring
parameters and determine an evolutionary classification of these objects. Four
independent statistical methods are used to investigate the discriminant
properties of the observables and the partitioning of the 424 galaxies:
Principal Component Analysis, K-means cluster analysis, Minimum Contradiction
Analysis and Cladistics. (abridged)
