Article Text

PDF
SP0046 Improving your Graphs for Publications
  1. M. Boers1
  1. 1Epidemiology & Biostatistics; Rheumatology, Vu University Medical Center, Amsterdam, Netherlands

Abstract

This workshop is an introduction to the principles of good graph design as pioneered by Cleveland1 and Tufte2 and updated by Few3 so that the participant can better answer the following questions:

Which of the messages in my research results requires a graph? Recognizing how graphs improve on simple statistics and convey much more information.

How can I best convey the message? Striving for clear vision by choice of graph, scaling, discrimination of data series, minimizing non-data ink, avoiding chart junk. Striving for clear understanding through a balance between data and explanation.

Is my graph truthful? Creating a direct proportion between graph and data quantities, avoiding forms prone to misinterpretation, labels to prevent ambiguity; keeping data in context, avoiding more dimensions in the graph than in the data.

  1. Cleveland WS. The elements of graphing data: Hobart Press, Summit, NJ, U.S.A.; 1994.

  2. Tufte E. The visual display of quantitative information. 2nd ed: Graphics Press, Cheshire, CT, U.S.A.; 2001.

  3. Few S. Show me the numbers. Designing tables and graphs to enlighten. Analytics Press, Oakland, CA, U.S.A.; 2004.

Disclosure of Interest None Declared

Statistics from Altmetric.com

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.