Graphical perception

Suggested answers

Application exercise
Answers
Modified

September 3, 2026

Graphical perception

In 1984, William Cleveland and Robert McGill ran an experiment to answer a question that sounds simple but had never been tested: when a chart encodes a quantity as a position, a length, an angle, or an area, how accurately can people actually read it back out? They asked subjects to compare two marked values on a chart and estimate how much smaller one was than the other, then ranked the encodings by how much error each produced. Jeffrey Heer and Michael Bostock replicated the study on Mechanical Turk in 2010 and extended it to areas – bubble charts and treemaps.

Answer key

Each chart marks two values, one orange and one blue. Students identified the smaller and estimated what percentage it is of the larger.

Table 1: Marked values and true answers for seed 3312.
Chart Encoding Orange Blue Smaller True %
1 Length, same bar 40 14 blue 35.0
2 Position, common scale (adjacent) 22 45 orange 48.9
3 Length, different bars 48 36 blue 75.0
4 Rectangular area 54 44 blue 81.5
5 Position, common scale (separated) 39 16 blue 41.0
6 Circular area 38 22 blue 57.9
7 Angle 29 44 orange 65.9
8 Rectangular area (treemap) 41 11 blue 26.8
9 Position, non-aligned scales 41 8 blue 19.5

Chart 1 — Length, same bar Smaller: blue, and it is 35% of the larger.

Chart 1 — Length, same bar
Smaller: blue, and it is 35% of the larger.

Chart 2 — Position, common scale (adjacent) Smaller: orange, and it is 48.9% of the larger.

Chart 2 — Position, common scale (adjacent)
Smaller: orange, and it is 48.9% of the larger.

Chart 3 — Length, different bars Smaller: blue, and it is 75% of the larger.

Chart 3 — Length, different bars
Smaller: blue, and it is 75% of the larger.

Chart 4 — Rectangular area Smaller: blue, and it is 81.5% of the larger.

Chart 4 — Rectangular area
Smaller: blue, and it is 81.5% of the larger.

Chart 5 — Position, common scale (separated) Smaller: blue, and it is 41% of the larger.

Chart 5 — Position, common scale (separated)
Smaller: blue, and it is 41% of the larger.

Chart 6 — Circular area Smaller: blue, and it is 57.9% of the larger.

Chart 6 — Circular area
Smaller: blue, and it is 57.9% of the larger.

Chart 7 — Angle Smaller: orange, and it is 65.9% of the larger.

Chart 7 — Angle
Smaller: orange, and it is 65.9% of the larger.

Chart 8 — Rectangular area (treemap) Smaller: blue, and it is 26.8% of the larger.

Chart 8 — Rectangular area (treemap)
Smaller: blue, and it is 26.8% of the larger.

Chart 9 — Position, non-aligned scales Smaller: blue, and it is 19.5% of the larger.

Chart 9 — Position, non-aligned scales
Smaller: blue, and it is 19.5% of the larger.

The conceptual tasks

The charts are not nine arbitrary designs. They are the nine stimuli from Experiment 1 of Heer and Bostock (2010), which recreate Cleveland and McGill’s (1984) position-length experiment and extend it to areas. Each one isolates a single elementary perceptual task – the visual operation a reader has to perform to recover the number.

The nine elementary perceptual tasks
Task Encoding What the reader has to do
T1 Position, common scale (adjacent) Compare two bars sharing a baseline, side by side
T2 Position, non-aligned scales Compare two segments that each start at their own bar’s zero
T3 Position, common scale (separated) Same as T1, but the bars are far apart
T4 Length, different bars Compare two floating segments in two different bars
T5 Length, same bar Compare two floating segments in one bar
T6 Angle Compare two pie wedges
T7 Circular area Compare two circles
T8 Rectangular area Compare two rectangles
T9 Rectangular area (treemap) Compare two rectangles embedded in a treemap

References

  • Cleveland, William S., and Robert McGill. 1984. “Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods.” Journal of the American Statistical Association 79: 531–554.
  • Cleveland, William S., and Robert McGill. 1987. “Graphical Perception: The Visual Decoding of Quantitative Information on Graphical Displays of Data.” Journal of the Royal Statistical Society Series A 150: 192–229.
  • Heer, Jeffrey, and Michael Bostock. 2010. “Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design.” Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 203–212. https://doi.org/10.1145/1753326.1753357