The Relative Merits of Circles and Bars for Representing Component Parts
Integrity signals
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Cites
Statistics
Claims the paper makes
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Sorted by citations
Cleveland, W. S., & McGill, R. (1984) · Journal of the American Statistical Association · doi:10.1080/01621459.1984.10478080 · Cited by 1,797 · see citing works
“This was a controversy (Eells 1926; Croxton 1927; Crox-ton and Stryker 1927; von Huhn 1927) about whether the divided bar chart or the pie chart was superior for por-traying the parts of a whole.”
BackgroundMaking Sense of Graphs: Critical Factors Influencing Comprehension and Instructional Implications
Friel, S. N., Curcio, F. R., & Bright, G. W. (2001) · Journal for Research in Mathematics Education · doi:10.2307/749671 · Cited by 819 · see citing works
“Mathematics knowledge and experience have been identified as other characteristics necessary for graph comprehension (e.g., Curcio, 1987; Eells, 1926; Fisher, 1992; Gal, 1993, 1998; Maichle, 1994; McKnight & Fisher, 1991; Russell, 1991; Thomas, 1933).”
BackgroundCleveland, W. S., & McGill, R. (1984) · Journal of the American Statistical Association · doi:10.2307/2288400 · Cited by 1,796 · see citing works
COMPUTER GRAPHICS AS DECISION AIDS: DIRECTIONS FOR RESEARCH*
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A Brief History of Data Visualization
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“As well, experimental comparisons of the efficacy of various graphics forms were begun (Eells, 1926, von Huhn, 1927, Washburne, 1927), a set of standards and rules for graphic presentation was finally adopted by a joint committee (Joint Committee on Standards for Graphic Presentation, 1914), and a…”
BackgroundMilestones in the history of thematic cartography, statistica l graphics, and data visualization
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BackgroundTask-based effectiveness of basic visualizations
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Displaying proportions and percentages
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“Eells (1926) showed that subjects could estimate the size of a proportion more quickly and accurately when the data were in pie chart rather than bar chart form.”
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“Since Eells’ pioneering work [23] in 1926, investigating the effectiveness of different graph types became a major subject in graphical perception.”
BackgroundThe Incidence and Quality of Graphics in Annual Reports: An International Comparison
Frownfelter-Lohrke, C., & Fulkerson, C. L. (2001) · Journal of Business Communication · doi:10.1177/002194360103800308 · Cited by 73 · see citing works
Judgments of Change and Proportion in Graphical Perception
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“For example, Eells (1926) showed subjects proportional data and had them compare one of the proportions to the whole (a part-to-whole judgment of proportion).”
BackgroundInfluentialIllusion of Causality in Visualized Data
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“Although many have looked at the effect of visualization designs on perceptual analytic tasks such as determining anomalies or estimating data trends [42, 6, 7, 11, 16, 48, 5, 24], researchers have only begun to explore the effect of visualization design on cognitive reasoning tasks, such as understanding uncertainty…”
BackgroundThe Effects of Modes of Information Presentation on Decision-Making: A Review and Meta-Analysis
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A Survey of Perception-Based Visualization Studies by Task
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“in cluster perception in pie charts can be traced back to its effectiveness in facilitating proportional judgments through a part-to-whole relationship [105], [106].”
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A study of graph comprehension difficulties
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“In a study conducted long before visualization as a field existed, Walter Crosby Eells asked about 100 students in an introductory psychology course to read percentages off of a collection of pie and bar charts [11].”
BackgroundVisual and statistical assessment of spatial clustering in mapped data
Walter, S. D. (1993) · Statistics in Medicine · doi:10.1002/sim.4780121402 · Cited by 52 · see citing works
How accurately are different kinds of graphs read?
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Testing Statistical Charts: What Makes a Good Graph?
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Scents and Sensibility: Evaluating Information Olfactation
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“Some of the early work in this vein dates back to paper-based statistical graphics, such as results by Eells et al. [28] from 1927, by Croxton et al. [20] in 1927 on pie charts, bar charts, and circle diagrams, and by Croxton et al. [19] in 1932 on shapes for comparison.”
BackgroundVisualization in Motion: A Research Agenda and Two Evaluations
Yao, L., Bezerianos, A., Vuillemot, R., & Isenberg, P. (2022) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2022.3184993 · Cited by 28 · see citing works
“stacked bar charts found that often pie charts outperformed or were en par with stacked bars according to accuracy [20], [27], [46] but that stacked bar tasks were often completed more quickly [27], [46], [83].”
BackgroundSuggestions for Basic Graph Use When Reporting Wildlife Research Results
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“[8] from 1926, well before computers were able to generate such graphics.”
BackgroundVisual Inference and Graphical Representation in Regression Discontinuity Designs
Korting, C., Lieberman, C., Matsudaira, J. D., Pei, Z., & Shen, Y. (2023) · The Quarterly Journal of Economics · doi:10.1093/qje/qjad011 · Cited by 26 · see citing works
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“The 1926 study by Eells [4] had many gaps and hardly had enough statistical power to remain unquestioned for so long.”
Background16 Reading Graphs: Interactions of Processing Requirements and Stimulus Structure
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Evidence for Area as the Primary Visual Cue in Pie Charts
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“Eells [9] found pie charts to be superior to bars, and von Huhn [22] was unable to draw a clear conclusion in his studies.”
BackgroundAn experimental evaluation of multivariate graphical point representations
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BezelGlide: Interacting with Graphs on Smartwatches with Minimal Screen Occlusion
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“To assess the legibility of such visualizations, researchers resort to a set of canonical data exploration tasks [4, 8, 9, 22, 32, 38].”
BackgroundAssessing the Graphical Perception of Time and Speed on 2D+Time Trajectories
Périn, C., Wun, T., Pusch, R., & Carpendale, S. (2017) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2017.2743918 · Cited by 25 · see citing works
“Graphical perception studies for statistical data graphics have a long history with studies of factors such as types of representations and shapes dating back to 1926 [26,27,33,61].”
BackgroundModels of Graphical Perception
Lohse, G. L. (1997) · Elsevier eBooks · doi:10.1016/b978-044481862-1.50072-8 · Cited by 25 · see citing works
Modeling the Influence of Visual Density on Cluster Perception in Scatterplots Using Topology
Quadri, G. J., & Rosen, P. (2020) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2020.3030365 · Cited by 24 · see citing works
“The performance in cluster perception in pie charts is traced back to its effectiveness in facilitating proportional judgments through a part-whole relationship [26, 74].”
Judgment Error in Pie Chart Variations
Kosara, R., & Skau, D. (2016) · Eurographics · doi:10.2312/eurovisshort.20161167 · Cited by 25 · see citing works
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“Several studies exploring users’ graphical perception with varying graph types [8–10, 18, 27] identified three essential perceptual tasks.”
BackgroundVisual Data Analysis with Task-Based Recommendations
Shen, L., Shen, E., Tai, Z., Xu, Y., Dong, J., & Wang, J. (2022) · Data Science and Engineering · doi:10.1007/s41019-022-00195-3 · Cited by 19 · see citing works
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BackgroundAnalysis of Metagenomic Data Containing High Biodiversity Levels
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“Indeed, current studies usually include minimal analyses to understand relative OTU distribution in the underlying populations, often reporting Shannon-Weaver’s biodiversity index or using long-standing controversial methods, such as pie charts [22].”
G-Sparks: Glanceable Sparklines on Smartwatches
Neshati, A., Sakamoto, Y., Leboe-McGowan, L. C., Leboe-McGowan, J. P., Serrano, M., & Irani, P. (2019) · Open Archive Toulouse Archive Ouverte (University of Toulouse) · doi:10.20380/gi2019.23 · Cited by 25 · see citing works
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A Study of the Effect of Doughnut Chart Parameters on Proportion Estimation Accuracy
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An investigation of the relative presentation efficiency of computer-displayed graphs
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Teaching Students about Graphs
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“%] and 22 ◦ = 25% [21%, 28%], and with 0 ◦ = 28% [26%, 30”
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Visual Cues in Estimation of Part-To-Whole Comparisons
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“Eells [6] used the mean of absolute variance as the measure to compare performance however, in their seminal paper experimentally evaluating different visual elements, Cleveland and McGill [16] used the log of the absolute error, calculated as log2(|judged value – true value|+ c).”
BackgroundMethodResultInfluentialData Visualizations and Human Resource Management: The State of Science and Practice
Caughlin, D. E., & Bauer, T. N. (2019) · Emerald Group Publishing Limited eBooks · doi:10.1108/s0742-730120190000037004 · Cited by 12 · see citing works
The empirical investigation of factors affecting graphical visualization
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Display of Quantitative Information: Are Grables better than Plain Graphs or Tables?
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“For example, some research supports the use of bar charts over pie charts; other research finds the opposite (Croxton, 1927; Von Huhn, 1926; Eells, 1926; Spence and Lewandowsky, 1991).”
ResultSkipping the Replication Crisis in Visualization: Threats to Study Validity and How to Address ThemPreprint
Kosara, R., & Haroz, S. (2018) · doi:10.31219/osf.io/f8qey · Cited by 9 · see citing works
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“The theory of graphical perception suggests it is difficult to accurately judge the relative values of two or more areas if the circles are not in close proximity to each other or the values encoded are similar [10, 14].”
BackgroundStudies of the Effectiveness of Graphic Materials
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Theories and Models in Graph Comprehension
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Toward a Taxonomy for Adaptive Data Visualization in Analytics Applications
Pötzsch, T. H., Germanakos, P., & Huestegge, L. (2020) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.00009 · Cited by 7 · see citing works
“Research on data visualization was first concerned with the optimization of single chart visualizations, starting with Eells (1926).”
MethodGraph schema and best graph type to compare discrete groups: Bar, line, and pie
Zhao, F., & Gaschler, R. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.991420 · Cited by 6 · see citing works
“While there have been earlier studies on bar, line, and pie graphs (Eells, 1926; Simkin andHastie, 1987; Hollands and Spence, 1992; Shah et al., 1999; Zacks and Tversky, 1999), we aimed to investigate whether or not they share a common graph schema when the task is to assess numerical differences…”
BackgroundMethodDo grables enable the extraction of quantitative information better than pure graphs or tables?
Hink, J. K., Eustace, J. K., & Wogalter, M. S. (1998) · International Journal of Industrial Ergonomics · doi:10.1016/s0169-8141(97)00017-6 · Cited by 7 · see citing works
“For example, some research supports the use of bar charts over pie charts; other research finds the opposite (Von Huhn, 1926; Eells, 1926; Croxton, 1927; MacDonald-Ross, 1977; Spence and Lewandowsky, 1991).”
BackgroundResultAre pie charts evil? An assessment of the value of pie and donut charts compared to bar charts
Hill, A. A. (2024) · Information Visualization · doi:10.1177/14738716241259432 · Cited by 7 · see citing works
Moreira, J., Mendes, D., & Gonçalves, D. J. V. (2020) · International Conference on Advanced Visual Interfaces (AVI) · doi:10.1145/3399715.3399841 · Cited by 6 · see citing works
“In early studies, accuracy was measured by looking at how users could read information from charts, to justify their use against tables [8, 9, 12].”
BackgroundBars, Pies, Doughnuts & Tables – Visualization of Proportions
Siirtola, H. (2014) · Electronic workshops in computing · doi:10.14236/ewic/hci2014.38 · Cited by 5 · see citing works
Web Accessibility of Mobile and Desktop Representations
Fernandes, N., Rodrigues, A., Duarte, C., Hijón‐Neira, R., & Carriço, L. M. (2014) · Electronic workshops in computing · doi:10.14236/ewic/hci2014.30 · Cited by 5 · see citing works
“Eells (1926) did the first comparisons between pie charts and stacked (‘segmented’) bar charts where the experimental task was to estimate the percentage of the whole represented by an element, as a number.”
BackgroundUnderstanding and designing animations in the user interfaces
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“Eells (1926) did the first comparisons between pie charts and stacked bar charts.”
Integrating complex information with object displays: psychophysical evaluation of outlines
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“However, pie charts (and simple bar charts; Simkin and Hastie 1987) outperformed the divided bar chart when the data point was evaluated as a proportion of the whole (Eells 1926).”
BackgroundStatistical Computing and Graphics Let's Practice What We Preach: Turning Tables into Graphs
Gelman, A., Pasarica, C., & Dodhia, R. M. (2002) · Cited by 4 · see citing works
Data avatars: A theory-guided design and assessment for multidimensional data visualization
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Graphic illustrations with geographic text: On exploring a vast unknown
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MediVizor: Visual Mediation Analysis of Nominal Variables
Lan, J., Zhou, Z., Xie, X., Wu, Y., Zhang, H., & Wu, Y. (2023) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2023.3282801 · Cited by 2 · see citing works
“Some studies find that a pie chart is more accurate than a stacked bar for estimating the part-to-whole ratios [42], [43], [44].”
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Illusion of Causality in Visualized DataPreprint
Xiong, C., Shapiro, J., Hullman, J. R., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.00215 · Cited by 2 · see citing works
“Although many have looked at the effect of visualization designs on perceptual analytic tasks such as determining anomalies or estimating data trends [42, 6, 7, 11, 16, 48, 5, 24], researchers have only begun to explore the effect of visualization design on cognitive reasoning tasks, such as understanding uncertainty…”
BackgroundEvaluating Perceptual Judgements on 3D Printed Bar Charts
Wiederich, T., & VanderPlas, S. (2024) · Journal of Data Science · doi:10.6339/24-jds1131 · Cited by 1 · see citing works
Luo, J., Zhang, Y., & Song, Y. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.800789 · Cited by 2 · see citing works
“Since then, an increasing number of researchers have attempted to adopt this graphical representation tool and explore its potential advantages and disadvantages among different graphs (15).”
BackgroundUNEXPLORED POSSIBILITIES OF INSTRUCTION IN GRAPHIC METHODS
Schaaf, W. L. (1941) · School Science and Mathematics · doi:10.1111/j.1949-8594.1941.tb05423.x · Cited by 1 · see citing works
Polygons, Stars, and Clusters; an Investigation of Polygon Displays
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Cluster analysis of visual perception of data structure
Владимирович, Л. В., & Orlov, P. A. (2015)
A Study on 3D Surface Graph RepresentationsPreprint
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“at [8] starting toward a higher demand which different graphical representations are compared to obtain a greater visual effect.”
BackgroundMagyarország Nemzeti Atlasza új kiadásának digitális margójára
Tanszék, E. T. É. G., & Klinghammer, I. (2019) · Geodézia és Kartográfia · doi:10.30921/gk.71.2019.2.1
Task-Based Effectiveness of Basic VisualizationsPreprint
Saket, B., Endert, A., & Demiralp, Ç. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1709.08546 · Cited by 11 · see citing works
“Earlier work [19, 15, 57, 23, 14, 26, 14, 34, 16] has also studied the effectiveness of visualization types with their common design configurations for a select number of tasks.”
BackgroundInfluentialThe Application of Machine Learning to Enhance Performance Analysis in Australian Rules football
Browne, P. R. (2020) · Victoria University Research Repository (Victoria University)
A kognitív tudományok hatása a kartográfiára
Szigeti-Pap, C. (2021) · Geodézia és Kartográfia · doi:10.30921/gk.73.2021.5.4
“Emellett kutatásokat végeztek adatvizualizációval kapcsolatban, például diagramok (Eells 1926), vagy geometriai jelek értelmezhetőségéről (Croxton 1932).”
Beh, E. J., & Lombardo, R. (2014) · Wiley series in probability and statistics · doi:10.1002/9781118762875.ch01
(2004) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess1964
- Authors
- Eells, W. C.
- Affiliations
- Whitman College (US)
- Corresponding author
- Eells, Walter Crosby
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1926-06
- Volume
- 21
- Issue
- 154
- Pages
- 119-132
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2060296236
- Cited by
- 108
- References
- 0
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 4 · 2023: 7 · 2022: 5 · 2021: 4 · 2020: 6 · 2019: 10 · 2018: 7 · 2017: 3 · 2016: 3 · 2015: 1 · 2014: 4 · 2013: 1
- FWCI
- 0.00
- 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
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Manufacturing Process and Optimization
- Keywords
- bar charts, data visualization
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