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A Study of the Effect of Doughnut Chart Parameters on Proportion Estimation Accuracy
- Source :
- Computer Graphics Forum. 37:300-312
- Publication Year :
- 2018
- Publisher :
- Wiley, 2018.
-
Abstract
- Pie and doughnut charts nicely convey the part–whole relationship and they have become the most recognizable chart types for representing proportions in business and data statistics. Many experiments have been carried out to study human perception of the pie chart, while the corresponding aspects of the doughnut chart have seldom been tested, even though the doughnut chart and the pie chart share several similarities. In this paper, we report on a series of experiments in which we explored the effect of a few fundamental design parameters of doughnut charts, and additional visual cues, on the accuracy of such charts for proportion estimates. Since mobile devices are becoming the primary devices for casual reading, we performed all our experiments on such device. Moreover, the screen size of mobile devices is limited and it is therefore important to know how such size constraint affects the proportion accuracy. For this reason, in our first experiment we tested the chart size and we found that it has no significant effect on proportion accuracy. In our second experiment, we focused on the effect of the doughnut chart inner radius and we found that the proportion accuracy is insensitive to the inner radius, except the case of the thinnest doughnut chart. In the third experiment, we studied the effect of visual cues and found that marking the centre of the doughnut chart or adding tick marks at 25% intervals improves the proportion accuracy. Based on the results of the three experiments, we discuss the design of doughnut charts and offer suggestions for improving the accuracy of proportion estimates.
- Subjects :
- Estimation
Computer science
Bar chart
Pie chart
020207 software engineering
02 engineering and technology
01 natural sciences
Computer Graphics and Computer-Aided Design
law.invention
010104 statistics & probability
Chart
law
Statistics
0202 electrical engineering, electronic engineering, information engineering
0101 mathematics
Subjects
Details
- ISSN :
- 01677055
- Volume :
- 37
- Database :
- OpenAIRE
- Journal :
- Computer Graphics Forum
- Accession number :
- edsair.doi...........2c33bd4635b26c6691a74ec60dbccab0
- Full Text :
- https://doi.org/10.1111/cgf.13325