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Effective strategies for scientific graphics
Joel [email protected]
October 31, 2013
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Why care about graphics as a scientist?
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Quick Poll
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Data
Graphics (scatterplot,spectrum, micrograph, etc)
Presentation(to your professor, other
researchers, general public)
Exploration:“What conclusions
do my data support?”
Visual Intuition
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Graphics reveal data.
• Dual purposes: to explore data, and to present data.
• Excellent graphics do so with clarity, efficiency and precision.
• Richness beyond what any summary statistics (average, standard deviation, correlation, etc) can provide.
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Anscombe’s quartet
• All datasets: mean, variance & correlation are all identical
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Scientific graphics should:
• Show the data
• Allow the viewer to think about the substance, rather than the methodology of the experiment (or something else- font/color/etc)
• Avoid distorting the data
• Reveal multiple layers of detail: big picture & fine structure
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Some examples: the bad
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Some examples: the bad
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Lie factor: effect shown in graphic effect shown in data
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• Bad data = bad graphics!
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Some examples: the bad
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Types of graphics
• Most popular in mass media:time series & data maps
• Excel is optimized for business users (earnings reports, market share, etc).
• Beware “chartjunk”!
• Chemistry is most concerted with relational graphics.
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Effective strategies:1. Maximize “data ink”: % of graphic
actually used to plot your data.
2. Maximize data density.
• Use small multiples
• Combine graphics, images & numbers to tell a visual story.
3. Use color effectively
4. Revise & edit.
12Tufte’s rules: http://www.sealthreinhold.com/tuftes-rules/index.phpThursday, October 31, 2013
Maximize data ink:
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Maximize data ink:
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Data density
15dougmccune.com/blog
Small multiples:
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Data density
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Frankel & DePace. “Visual Strategies: A Practical Guide to Graphics for Scientists and Engineers” (Yale University Press 2012)
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Data density
• Not all data needs to be presented as a graphic
• For example, tables are sometimes more effective for small data sets
17(most infographics are silly)
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(some infographicsare pretty neat!)
from Wired Magazine’s best infographics & scientific figures
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Using color effectively
• Colorbrewer (colorbrewer2.org)
• Colorblind people are scientists too!
• Beware the black & white photocopier19
Sequential: data that runs from low to highDiverging: emphasize max/min extremes of dataQualitative: no difference implied between data classes (best for nominal/categorical data)
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Using color effectively
• Minimal color highlights data: builds a visual story
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Tools of the trade
• Understand the limitations of Excel
• Lots of field-specific options: gnuplot, Origin, R, Matlab, SPSS, Sigmaplot, etc. (see handout)
• Revise and edit: develop your own personal style
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