Testing Perceptual Accuracy in a U.S. General Population Survey Using Stacked Bar Charts
Volume 22, Issue 2 (2024): Special Issue: 2023 Symposium on Data Science and Statistics (SDSS): “Inquire, Investigate, Implement, Innovate”, pp. 280–297
Pub. online: 13 March 2024
Type: Statistical Data Science
Open Access
Open Access
Received
31 July 2023
31 July 2023
Accepted
2 February 2024
2 February 2024
Published
13 March 2024
13 March 2024
Abstract
The use of visuals is a key component in scientific communication. Decisions about the design of a data visualization should be informed by what design elements best support the audience’s ability to perceive and understand the components of the data visualization. We build on the foundations of Cleveland and McGill’s work in graphical perception, employing a large, nationally-representative, probability-based panel of survey respondents to test perception in stacked bar charts. Our findings provide actionable guidance for data visualization practitioners to employ in their work.
Supplementary material
Supplementary MaterialThe source code and data used in this paper and an example stimulus image are available on a GitHub repository at https://github.com/kiegan/testing-charts-jds.
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