1. A method for determining with a computing apparatus an adequate number of clusters for summarizing result data which includes a large number of observation data points, each data point having at least one characterizing value, the observation data points being stored in a memory storage device of the computing apparatus, the method implemented in control memory of the computing apparatus and utilizing a clustering algorithm to examine a significant plurality of the large number of observation data points, the clustering algorithm featuring provision for applying one or more input information parameters, those input parameters including at least a designation of a specified number of clusters, the specified number of clusters describing to the clustering algorithm the number of clusters into which the results data are to be divided, the method comprising the steps of: A) setting the specified number of clusters for the clustering algorithm to be performed by the computing apparatus to a value designating a starting is number of clusters; B) clustering the significant plurality of the large number of observation data points into the specified number of clusters utilizing the clustering algorithm performed by the computing apparatus for obtaining a specific clustering of the data points for that specified number of clusters such that each of the plurality of the large number of observation data points is a member of one cluster; C) computing by the computing apparatus, a quality indicator for the specific clustering of the data points from step B); D) storing the quality indicator value and the specified number of clusters for the specific clustering of the data points related to the that specified number of clusters into the memory storage device; E) increasing the specified number of clusters and then repeating steps B through D two or more times until a preset limit on the specified number of clusters is detected by the computing apparatus or until the computer apparatus makes a selection of one of the already specified number of clusters as the adequate number of clusters based on a pattern of at least two of the already calculated or computed quality indicators.