In praise of simple graphics


'Tis a gift to be simple.
-- Shaker hymn

In June 2015 I published a short article for Significance, a magazine that features statistical and data-related articles that are of general interest to a wide a range of scientists.

The title of my article is "In Praise of Simple Graphics." It is based on a blog post "Visualizing the causes of airline crashes."

My article compares infographics and statistical graphics. Infographics are designed to appeal as well as to inform. Unfortunately, a beautiful artistic display can sometimes obscure the data.

In contrast, a statistician usually has a different goal: represent the data objectively and let the data speak for themselves. Standard statistical graphics are purposely free of excess adornment in a Tuftean effort to maximize the data-ink ratio. Their beauty is in their minimalist simplicity.

Yes, I sometimes create complex graphs on my blog. In the past three weeks I've featured spaghetti plots, lasagna plots, and effect plots. However, I create complex graphs only to visualize complex data or models. For simple data, I advocate using a simple graph. I strive to never let the graph get in the way of the data. To paraphrase Einstein, graphs should be as complex as necessary, but no more complex.

Graphs should be as complex as necessary, but no more complex. #DataViz #StatWisdom Click To Tweet

You can read my article "In Praise of Simple Graphics" at the Significance web site. If you like data analysis, graphics, and statistical ideas, the Significance magazine archives are a great resource. All issues of Significance are freely available one year after publication. Enjoy!


About Author

Rick Wicklin

Distinguished Researcher in Computational Statistics

Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. His areas of expertise include computational statistics, simulation, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.


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