1. Method for the automatic, software-driven statistical evaluation of large amounts of data that is to be assigned to statistical variables in a database, in particular, contained in one or several clusters which is characterized in that a statistical model for the approximate description of the relative frequencies of the states of the variables and the statistical dependencies between said states, is learnt and by means of the data stored in the database and is used to determine, on the basis of the statistical model, the approximate relative frequencies of states of the variables, in addition to the approximate relative frequencies belonging to the pre-determinable relative frequencies of states of the variables and expected values of the states of variables dependent thereon.