My talk on statistical graphics at Mit this Thurs aft

November 28, 2012

(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)

Infovis and Statistical Graphics: Different Goals, Different Looks (and here’s the article)

Speaker: Andrew Gelman, Columbia University
Date: Thursday, November 29 2012
Time: 4:00PM to 5:00PM

Location: 32-D463 (Star Conference Room)
Host: Polina Golland, CSAIL
Contact: Polina Golland, 6172538005,

The importance of graphical displays in statistical practice has been recognized 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 uninterested in statistical principles.

We present a set of goals for graphical displays discussed primarily from the statistical point of view and discuss some inherent contradictions in these goals that may be impeding communication between the fields of statistics and Infovis. 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.

We recognize that we offer only one perspective and intend this work to be a starting point for a wide-ranging discussion among graphics designers, statisticians, and users of statistical methods. Our purpose is not to criticize but to explore the different goals that lead researchers in different fields to value different aspects of data visualization.

P.S. Following my recent thoughts, I wish I’d called it Tradeoffs in information graphics.

Please comment on the article here: Statistical Modeling, Causal Inference, and Social Science