According to statlit.org, statistical literacy is the ability to read and interpret summary statistics in the everyday media: in graphs, tables, statements, surveys and studies. Statistical literacy is needed by data consumers.
The importance of statistical literacy in the Internet age is clear, but the concept is not exclusive to designers. I’d like to focus on it because designers must consider it in a way that most people do not have to: statistical literacy is more than learning the laws of statistics; it is about representations that the human mind can understand and remember (source: Psychological Science in the Public Interest).
With data, though, careless designers all too readily sacrifice truth for the sake of aesthetics. Lovecraft’s eldritch horrors will rise only when the stars are right, but the preconditions for bad visual representations are already in place:
- Demand for graphs, charts, maps and infographics has increased.
- Increased data availability and more powerful tools have made it easier than ever to create them.
- But you probably don’t have a solid understanding of how to interpret or process data.
- Nor likely do your readers.
- And there’s a good chance that neither of you know that.
Do you hear that fateful, fearsome ticking? You’ve given your audience a time bomb of misinformation, just waiting to blow up in their faces. Perhaps they will forget your inadvertent falsehood before they harm someone with it, but perhaps they will be Patient Zero in an outbreak of viral inaccuracy. Curing that disease can be excruciatingly difficult, and even impossible: one of the more depressing findings in psychology is that trying to set the record straight can muddle it further. The lesson is clear: provide the right story the first time. But the staggering variety of awful visualizations online makes it equally clear that designers haven’t learned that lesson yet. Let’s see just how bad it can get.