The Selection of Class Intervals

The selection of class intervals, which can strongly affect the visual impression given by a map, is currently a totally anarchic branch of cartography. While practising cartographers have barely accustomed themselves to the routine techniques of class selection, recent work has widened the choice available and extended the opportunity to produce a desired bias. Systems of class intervals, apart from those fixed exogenously or in arbitrary fashion, are classified into idiographic or serial types, the latter being recommended here. Scale transformations leading towards symmetrical frequency distribu- tions are important and are required for proportional as well as graded symbolization. It is suggested that class intervals should not be optimized in relation to details of the statistical frequency distribution, but should be selected according to the overall shape of this distribution. For rectangular distributions, equal division of the range is appropriate: for dominantly unimodal distributions, intervals related to the standard deviation (on a scale which makes the distribution symmetrical): and for J-shaped distributions, geometric progressions to bases which are greater as skewness increases. Techniques are given for calibrating geometric progressions relative to the median, and for dealing with the special characteristics of percentages. An analysis of maps prepared by authors in various academic disciplines fails to show any rational or standardized procedures for the selection of class intervals. Evidently intuition, inspiration, revelation, mystical hunches, prejudices, legerdemain and predetermined ideas of what the class intervals should be have characterized the work of most map-makers ... Apparently many authors believe that maps are an art-form which allow liberties not admissible in verbal or tabular presentation. (Jenks and Coulson, 1963, p. 120)

Class (philosophy · Selection (genetic algorithm · Statistics · Artificial Intelligence · Categorization, perception, and language · Computer Science · Data Visualization and Analytics · Geographic Information Systems Studies · Mathematics

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