Graphs in statistical analysis: Is the medium the message?

R. Dennis Cook, Sanford Weisberg

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

In an influential article in the February 1973 issue of The American Statistician Frank Anscombe remarked that “[m]ost textbooks on statistical methods, and most statistical computer programs, pay too little attention to graphs.” This general observation no longer holds. Graphs of data are everywhere. Our children learn to draw and use bar charts in kindergarten and boxplots in the elementary grades; most newspapers and magazines regularly use graphical representation of data, and nearly all books on statistical methods use graphs. Graphs can be drawn in statistical packages, in spreadsheet programs, and in stand-alone graphics packages. Statisticians often bemoan the poor construction of the graphs produced, but even when the construction is adequate, graphs can be of little value. In this article, we argue that useful graphs must have a context induced by associated theory, and that a graph without the well-understood statistical context is hardly worth drawing.

Original languageEnglish (US)
Pages (from-to)29-37
Number of pages9
JournalAmerican Statistician
Volume53
Issue number1
DOIs
StatePublished - Feb 1999

Bibliographical note

Funding Information:
R. Dennis Cook and Sanford Weisberg are both Professors with the Department of Applied Statistics, University of Minnesota, St. Paul, MN 55108 (E-mail: sandy@stat.umn.edu). Work supported by National Science Foundation grants DUE 96-52887 and DMS 97-03777.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

Keywords

  • Dimension-reduction subspaces
  • Regression
  • Regression graphics
  • Residual plots
  • Scatterplot matrices

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