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.

Abstract: Despite the availability of software for interactive graphics, current survey processing systems make limited use of this modern tool. Interactive graphics offer insights, which are difficult to obtain with traditional statis tical tools. This paper shows the use of interactive graphics for analysing survey data. Using Labour Force Survey data from Pakistan, we describe how plotting data in different ways and using interactive tools enables analysts to obtain information from the dataset that would normally not be possible using standard statistical methods. It is also shown that interacative graphics can help the analyst to improve data quality by identifying erroneous cases.