Selecting The Right Graph For Your Message

What's the right graph for your BI message? Here are practical ideas that remove the guesswork from successful data presentation.
Now that I've presented the topics of quantitative vs. categorical data and the best means to encode quantitative values in graphs, you have the conceptual foundation necessary to get back to the main topic: the primary types of quantitative messages and how to graph them.

And Then There Were Seven

The seven types of quantitative messages differ in how separate values relate to one another. Quantitative messages always reveal relationships, and it's these relationships that tell the great stories that deserve attention. Almost every quantitative message that you'll ever need to present in a graph can be described as one or as a combination of more than one of the seven types in the following list (in no particular order):

  • Nominal comparison
  • Time-series
  • Ranking
  • Part-to-whole
  • Deviation
  • Frequency distribution
  • Correlation.

Table 1 describes each of these seven quantitative relationships and also identifies the best ways to encode their values. Knowing what you do now about the relative strengths and weaknesses of points, lines, and bars for encoding values, try determining which objects would work best before looking at the encoding method guidelines that I provide.

By understanding these seven types of quantitative relationships and the graphical methods that present them most effectively, you've already won half the battle. Knowing the best means to present data is the first big step; knowing how to design the separate components of a graph to communicate your message clearly, powerfully, and without distraction is the other big step, which we'll examine in the next article of this series.

Stephen Few is the founder of Perceptual Edge [], a consulting firm that specializes in information design for insight and communication.

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