The Weighted Average Illusion: Biases in Perceived Mean Position in Scatterplots.

Autor: Hong MH, Witt JK, Szafir DA
Jazyk: angličtina
Zdroj: IEEE transactions on visualization and computer graphics [IEEE Trans Vis Comput Graph] 2022 Jan; Vol. 28 (1), pp. 987-997. Date of Electronic Publication: 2021 Dec 24.
DOI: 10.1109/TVCG.2021.3114783
Abstrakt: 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.
Databáze: MEDLINE