Literature DB >> 1634243

Judgments of change and proportion in graphical perception.

J G Hollands1, I Spence.   

Abstract

Subjects judged change and proportion when viewing graphs in two experiments. Change was judged more quickly and accurately with line and bar graphs than with pie charts or tiered bar graphs, and this difference was larger when the rate of change was smaller. Without a graduated scale, proportion was judged more quickly and accurately with pie charts and divided bar graphs than with line or bar graphs. Perception is direct when it requires simpler or fewer mental operations; we propose that perception of change is direct with line and bar graphs, whereas perception of proportion is direct with pie charts and divided bar graphs. The results are also consistent with the proximity compatibility principle. Suggestions for improving the design of graphical displays are given.

Mesh:

Year:  1992        PMID: 1634243     DOI: 10.1177/001872089203400306

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  5 in total

1.  Effect of arrangement of stick figures on estimates of proportion in risk graphics.

Authors:  Jessica S Ancker; Elke U Weber; Rita Kukafka
Journal:  Med Decis Making       Date:  2010-07-29       Impact factor: 2.583

2.  Improving understanding of adjuvant therapy options by using simpler risk graphics.

Authors:  Brian J Zikmund-Fisher; Angela Fagerlin; Peter A Ubel
Journal:  Cancer       Date:  2008-12-15       Impact factor: 6.860

3.  Men's interpretations of graphical information in a videotape decision aid.

Authors:  Jan Pylar; Celia E Wills; Janet Lillie; David R Rovner; Karen Kelly-Blake; Margaret Holmes-Rovner
Journal:  Health Expect       Date:  2007-06       Impact factor: 3.377

Review 4.  Decision making with visualizations: a cognitive framework across disciplines.

Authors:  Lace M Padilla; Sarah H Creem-Regehr; Mary Hegarty; Jeanine K Stefanucci
Journal:  Cogn Res Princ Implic       Date:  2018-07-11

5.  Toward a Taxonomy for Adaptive Data Visualization in Analytics Applications.

Authors:  Tristan Poetzsch; Panagiotis Germanakos; Lynn Huestegge
Journal:  Front Artif Intell       Date:  2020-03-20
  5 in total

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