ABSTRACT
Data sets are often analyzed in the form of collections of histogram frequencies or percentiles derived from equivalent cumulative frequency distributions. Decisions concerning the number of intervals and interval width obviously affect the quality of the data in subsequent analysis. Particle scientists have traditionally cast data in the form of frequency histograms or their equivalent, cumulative frequency distributions. Conversely, high-frequency portions of the histograms may contain more observations than needed in terms of precision, and might be profitably subdivided in order to test for the presence of polymodality in these intervals. Entropy, as applied to frequency plots, is a measure of contrast between intervals. Low entropy values represent frequency plots with large differences between intervals and high entropies characterize frequency plots with relatively slight contrast between intervals. The total entropy of a set of frequency plots is a measure of the total contrast between intervals and is a measure of the total amount of useful information contained within that system.
