The Relative Merits of Circles and Bars for Representing Component Parts

Eells, Walter Crosby

doi:10.1080/01621459.1926.10502165

Cited by 79 publications

(48 citation statements)

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“…However, pie charts produced the smallest absolute error values in all three experiments. Despite the opinions of some critics (e.g., Cleveland, 1985;Macdonald-Ross, 1977;Tufte, 1983), the accumulated evidence suggests that the pie is an eective format for judgments of proportion and yields accuracies as good as or better than other graph types for that task (Eells, 1926;Hollands and Spence, 1992;Simkin and Hastie, 1987;Spence, 1990;Spence and Lewandowsky, 1991). It appears that the pie chart is the graph of choice for communicating part-towhole relationships, with divided bars and reference bars serving as reasonable alternatives.…”

Section: Implications For Designmentioning

confidence: 87%

Judging proportion with graphs: the summation model

Hollands

Spence

1998

Appl. Cognit. Psychol.

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Section: Implications For Designmentioning

confidence: 87%

Judging proportion with graphs: the summation model

Hollands

Spence

1998

Appl. Cognit. Psychol.

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“…Walter Eells (1926) apparently had shown the superiority of the pie chart over the divided horizontal bar chart. In a simple but well-executed experiment he had subjects estimate the percentage associated with a single component (a slice of the pie or an individual bar) and found that the magnitude estimation was performed more accurately and more quickly when the data were in pie chart form.…”

Section: Early Experiments On Statistical Graphsmentioning

confidence: 99%

“…In addition to the fact that the shape of the sub-area is idiosyncratic, subjects can use perceptual anchor points that are otherwise unavailable: with the pie chart it is easy to compare the size of a component with imaginary quarters, or halves, as well as the whole, before making either absolute or relative judgements. A crude linear scale is thus available to the observer, and subjects report making use of this scale (Eells, 1926;Simkin and Hastie, 1987;Spence, 1989). Indeed, Spence (1989) found that the estimated exponent for the judged size of pie chart segments is about one.…”

Section: The Psychophysics Of Magnitude Estimationmentioning

confidence: 99%

Displaying proportions and percentages

Spence

Lewandowsky

1991

Applied Cognitive Psychology

146

125

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Pie and bar charts are commonly used to display percentage or proportional data, but professional data analysts have frowned on the use of the pie chart on the grounds that judgements of area are less accurate than judgements of length. Thus the bar chart has been favoured. When the amount of data to be communicated is small, some authorities have advocated the use of properly constructed tables, as another option. The series of experiments reported here suggests that there is little to choose between the pie and the bar chart, with the former enjoying a slight advantage if the required judgement is a complicated one, but that both forms of chart are superior to the table. Thus our results do not support the commonly expressed opinion that pie charts are inferior. An analysis of the nature of the task and a review of the psychophysical literature suggest that the traditional prejudice against the pie chart is misguided.The display of proportions and percentages is a common activity: opinion polls and market surveys appear almost daily in the popular press; scientific articles and technical reports frequently exhibit results expressed in percentage form; and proportional data are the very stuff of handbooks, almanacs, and compendia of every kind. Despite the ubiquity of these data, and their widespread presentation in tables and graphs, comparative evaluations of the relative merits of these displays have been largely based on intuition rather than experimental data.Some modern commentators recommend the use of tables to display small data sets. Ehrenberg (1975), for example, prefers properly constructed tables to graphical displays, and Tufte (1983), in one of the most influential recent books on the visual display of data, suggests that tables are more appropriate than graphs for data sets containing fewer than 20 observations. However, contrasting views, advocating graphical displays over tables for most purposes (e.g. Mahon, 1977;Wainer and Thissen, 1988), are perhaps more common, and many authorities lean towards the bar chart as the most appropriate graph for the display of proportional data; evidence from early studies on graphical displays, and a large body of psychophysical work, has been interpreted to favour the bar chart over the pie chart (see MacDonald-Ross,

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“…Criticisms like this provoked the first psychological experiments on graphs, where subjects were required to estimate quantities represented in graphic form. 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. His advocacy quickly produced critics who conducted their own experiments (Croxton, 1927;Croxton & Stein, 1932;Croxton & Stryker, 1927;von Huhn, 1927), but these early empirical studies were of widely varying quality, were generally inconclusive, and did not convincingly reverse Eells's findings.…”

Section: Empirical Evaluation Of the Pie Chart And Other Formsmentioning

confidence: 99%

No Humble Pie: The Origins and Usage of a Statistical Chart

Spence

2005

Journal of Educational and Behavioral Statistics

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The Relative Merits of Circles and Bars for Representing Component Parts

Cited by 79 publications

References 0 publications

Judging proportion with graphs: the summation model

Judging proportion with graphs: the summation model

Displaying proportions and percentages

No Humble Pie: The Origins and Usage of a Statistical Chart

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