Premium
Perception of clusters in statistical maps
Author(s) -
Lewandowsky Stephan,
Herrmann Douglas J.,
Behrens John T.,
Li ShuChen,
Pickle Linda,
Jobe Jared B.
Publication year - 1993
Publication title -
applied cognitive psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 100
eISSN - 1099-0720
pISSN - 0888-4080
DOI - 10.1002/acp.2350070606
Subject(s) - categorical variable , perception , centroid , psychology , monochrome , recall , cluster (spacecraft) , cartography , artificial intelligence , hue , pattern recognition (psychology) , stimulus (psychology) , cognition , statistics , geography , cognitive psychology , computer science , mathematics , neuroscience , programming language
Two experiments observed performance on a cluster identification task across a variety of common statistical maps. Stimulus maps displayed mortality rates for several diseases and subjects had to identify regions of the map that were perceived to form a cluster of particularly high (or low) mortality. Subjects marked the perceived centroid of each cluster, and analyses focused on the dispersion of centroid location across subjects. Under these circumstances, monochrome classed choropleth maps were found to minimize dispersion, compared to a two opposing colours scheme, a dot density map, a pie map, and a categorical (hue‐based) colour scheme. Maps using a familiar geographical unit (i. e. a U. S. state) supported better recall of the information than maps using less familiar and smaller geographical units. The results were found to be interpretable within current cognitive theory.