Literature DB >> 26356929

Four Experiments on the Perception of Bar Charts.

Justin Talbot, Vidya Setlur, Anushka Anand.   

Abstract

Bar charts are one of the most common visualization types. In a classic graphical perception paper, Cleveland & McGill studied how different bar chart designs impact the accuracy with which viewers can complete simple perceptual tasks. They found that people perform substantially worse on stacked bar charts than on aligned bar charts, and that comparisons between adjacent bars are more accurate than between widely separated bars. However, the study did not explore why these differences occur. In this paper, we describe a series of follow-up experiments to further explore and explain their results. While our results generally confirm Cleveland & McGill's ranking of various bar chart configurations, we provide additional insight into the bar chart reading task and the sources of participants' errors. We use our results to propose new hypotheses on the perception of bar charts.

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Year:  2014        PMID: 26356929     DOI: 10.1109/TVCG.2014.2346320

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  1 in total

1.  Political affiliation moderates subjective interpretations of COVID-19 graphs.

Authors:  Jonathan D Ericson; William S Albert; Ja-Nae Duane
Journal:  Big Data Soc       Date:  2022-03-04
  1 in total

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