Cited by 1,796Data Visualization and AnalyticsVisual and Cognitive Learning ProcessesVisual perception and processing mechanisms

Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods

Cleveland, William S., McGill, Robert·1984·Journal of the American Statistical Association

Abstract

The subject of graphical methods for data analysis and for data presentation needs a scientific foundation. In this article we take a few steps in the direction of establishing such a foundation. Our approach is based on graphical perception—the visual decoding of information encoded on graphs—and it includes both theory and experimentation to test the theory. The theory deals with a small but important piece of the whole process of graphical perception. The first part is an identification of a set of elementary perceptual tasks that are carried out when people extract quantitative information from graphs. The second part is an ordering of the tasks on the basis of how accurately people perform them. Elements of the theory are tested by experimentation in which subjects record their judgments of the quantitative information on graphs. The experiments validate these elements but also suggest that the set of elementary tasks should be expanded. The theory provides a guideline for graph construction: Graphs should employ elementary tasks as high in the ordering as possible. This principle is applied to a variety of graphs, including bar charts, divided bar charts, pie charts, and statistical maps with shading. The conclusion is that radical surgery on these popular graphs is needed, and as replacements we offer alternative graphical forms—dot charts, dot charts with grouping, and framed-rectangle charts.

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Registry

Crossref · 10.1080/01621459.1984.10478080

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15 of 39 references verified0 citation errors · 24 not checkable

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Authors
Cleveland, W. S., & McGill, R.
Affiliations
AT&T (United States) (US)
Venue
Journal of the American Statistical Association
Published
1984-09
Volume
79
Issue
387
Pages
531-554
ISSN
  • 0162-1459 (ISSN-L)
  • 1537-274X
OpenAlex
W1971781829
Cited by
1,796
References
39
Citations by year
2026: 86 · 2025: 141 · 2024: 84 · 2023: 75 · 2022: 69 · 2021: 119 · 2020: 94 · 2019: 81 · 2018: 116 · 2017: 73 · 2016: 71 · 2015: 82 · 2014: 73 · 2013: 60 · 2012: 70
FWCI
12.93
Type
journal article
Language
en
Open access
closed
Locations
Journal of the American Statistical Association (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
Keywords
graphical perception, task sequencing, graph construction, bar charts, pie charts, statistical maps, shading, data visualization, data presentation

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