The Weighted Average Illusion: Biases in Perceived Mean Position in Scatterplots
The Weighted Average Illusion: Biases in Perceived Mean Position in Scatterplots
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DOI：
10.1109/tvcg.2021.3114783
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发表时间：
2021-08
影响因子：
5.2
通讯作者：
Matt-Heun Hong;J. Witt;D. Szafir
中科院分区：
文献类型：
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作者：
Matt-Heun Hong;J. Witt;D. Szafir
散点图可以通过使用其他通道（如大小或颜色）来编码第三维（例如气泡图）。我们探讨了一个潜在的三变量散点图的误解，我们称之为加权平均错觉，其中较大和较暗的点的位置被赋予更多的权重对x和y均值估计。这种系统偏差对设计者选择的尺寸或映射到数据上的亮度范围很敏感。在本文中，我们量化这种偏见对不同的大小/亮度范围和数据相关性。我们讨论了可能的解释，其原因是通过测量注意到个别数据点使用视觉科学技术称为质心方法。我们的工作说明了合奏处理机制和心理捷径如何显着扭曲数据的视觉摘要，并可能导致误判，如加权平均错觉。
Scatterplots can encode a third dimension by using additional channels like size or color (e.g. bubble charts). We explore a potential misinterpretation of trivariate scatterplots, which we call the weighted average illusion, where locations of larger and darker points are given more weight toward x- and y-mean estimates. This systematic bias is sensitive to a designer's choice of size or lightness ranges mapped onto the data. In this paper, we quantify this bias against varying size/lightness ranges and data correlations. We discuss possible explanations for its cause by measuring attention given to individual data points using a vision science technique called the centroid method. Our work illustrates how ensemble processing mechanisms and mental shortcuts can significantly distort visual summaries of data, and can lead to misjudgments like the demonstrated weighted average illusion.