Overestimation Underestimation Perceptual Pull line position estimate bar position estimate Fig. 1. Reproductions of average line and bar positions are systematically biased, such that people tend to underestimate average line positions (toward the bottom of the display) and overestimate average bar positions (toward the top of the display). This bias appears in displays containing one data series (e.g., two outermost images on each side: a visualization containing only one line or only one set of bars). When a display consists of two data series (e.g., middle image: a visualization containing two lines, two bars, or a combination of the two), an additional effect of "perceptual pull" occurs: perception of average line and bar positions are pulled toward each other. This pull is shown to diminish or exaggerate the effect of underestimation and/or overestimation depending on the spatial arrangement of the data series representations.Abstract-In visual depictions of data, position (i.e., the vertical height of a line or a bar) is believed to be the most precise way to encode information compared to other encodings (e.g., hue). Not only are other encodings less precise than position, but they can also be prone to systematic biases (e.g., color category boundaries can distort perceived differences between hues). By comparison, position's high level of precision may seem to protect it from such biases. In contrast, across three empirical studies, we show that while position may be a precise form of data encoding, it can also produce systematic biases in how values are visually encoded, at least for reports of average position across a short delay. In displays with a single line or a single set of bars, reports of average positions were significantly biased, such that line positions were underestimated and bar positions were overestimated. In displays with multiple data series (i.e., multiple lines and/or sets of bars), this systematic bias still persisted. We also observed an effect of "perceptual pull", where the average position estimate for each series was 'pulled' toward the other. These findings suggest that, although position may still be the most precise form of visual data encoding, it can also be systematically biased.
Fig. 1. The Mekko chart at left uses height to encode relative market share, similar to a bar chart. But the present results suggest that the aspect ratio of each mark may bias this height judgment. When asked to reproduce the vertical position of a single bar mark in a bar chart, bars with wide aspect ratios were overestimated, bars with tall ratios were underestimated, and bars with square ratios showed no systematic bias. This pattern of bias appeared within memory, suggesting that value comparisons that occur across time and space (e.g., bars in separate graphs) would most likely be distorted.
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