Journal of Data Science

This study investigates how user ability to manipulate plot features affects graphical perception, by extending a previous graphical study (Vanderplas and Hofmann, 2017) with an interactive framework. Similar to the original study, statistical lineups included two target patterns (a linear trend and a clustering pattern), as well as eighteen null plots generated from three different mixture proportions of the combined cluster and trend models. Participants were asked to select two plots that they perceived as ‘most different’, and were able to interact with the graphics by toggling aesthetic features such as cluster coloring, cluster ellipses, linear trendlines, and regression error bands.