Perception of clusters in statistical maps

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Stephan Lewandowsky - , University of Oklahoma (Author)
  • Douglas J. Herrmann - , Centers for Disease Control and Prevention (Author)
  • John T. Behrens - , University of Oklahoma (Author)
  • Shu‐Chen ‐C Li - , University of Oklahoma (Author)
  • Linda Pickle - , Centers for Disease Control and Prevention (Author)
  • Jared B. Jobe - , Centers for Disease Control and Prevention (Author)

Abstract

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.

Details

Original languageEnglish
Pages (from-to)533-551
Number of pages19
JournalApplied Cognitive Psychology
Volume7
Issue number6
Publication statusPublished - Nov 1993
Peer-reviewedYes
Externally publishedYes

External IDs

ORCID /0000-0001-8409-5390/work/142254976