Prof. Andrew Gelman (Columbia University)

Title: Infovis vs. Statistical Graphics

Abstract: The importance of graphical displays in statistical practice has been indicated sporadically in the statistical literature over the past century, with wider awareness following Tukey’s Exploratory Data Analysis (1977) and Tufte’s books in the succeeding decades. But statistical graphics still occupies an awkward in-between position: Within statistics, exploratory and graphical methods represent a minor subfield and are not well-integrated with larger themes of modeling and inference. Outside of statistics, infographics (also called information visualization or Infovis) is huge, but their purveyors and enthusiasts appear largely to be unaware of and uninterested in statistical principles.

We present here a set of goals for graphical displays from the statistical and Infovis points of view and discuss some inherent contradictions in these goals that may be impeding communication between these allied fields. (One of our constructive suggestions, to Infovis practitioners and statisticians alike, is to try not to cram into a single graph what can be better displayed in two or more.) Our goal in this work (joint with Antony Unwin) is to broaden the communication among graphics designers, statisticians, and users of statistical methods.