Class Interval Systems on Maps of Observed Correlated Distributions

Bibliographic Data

ID14701066
AuthorsJudy M Olson (University of Georgia, corresponding author), Judy Olson (University of Georgia/Athens)
Year1972
Volume9
Issue2
Pages122-131
Publication date1972-12-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueCartographica The International Journal for Geographic Information and Geovisualization (JOURNAL)
Journal identifiersISSN: 0317-7173 • E-ISSN: 1911-9925
PublisherUniversity of Toronto Press Inc. (UTPress) (PUBLISHER)
DOI10.3138/l6np-1628-663g-3862
OpenAlexW2004812936
LanguageEN
Citations received5

The degree to which choropleth maps accurately reflect product-moment correlation between sets of data depends upon the statistical distributions of the data and the system by which they are divided into class intervals. Comparing results for observed distributions with earlier results for normal distributions, it is found that: (1) the expected values of rank correlations between maps (given the product-moment correlation between the data sets) appear to be similar regardless of class interval method and regardless of whether data are normal or not; (2) class intervals based on standard deviation units have relatively smaller degrees of variation about expected values when observed data are being compared, while quantiles have small variations on the normal data (quantiles being a special case of standard deviations in that situation); and (3) the choice of interval system remains important for higher numbers of observations when observed, rather than normal, data are being considered

Class (philosophy · Combinatorics · Correlation · Geometry · Interval (graph theory · Moment (physics · Normal distribution · Physics · Quantile · Standard deviation · Statistical parameter · Statistics · Computer Science · Mathematics · Neural Networks and Applications

Tools

Open DOISci-Hub