this graphic causes confusion, ignore the entire product.” This footnote appeared on an official spaghetti-like weather map tweeted by Donald Trump on September 4th. It was not on the crudely doctored version that he wheeled out at the White House on the same day, to justify his mistaken warning that, among other places, Alabama would “most likely be hit harder than anticipated” by Hurricane Dorian. But perhaps it should have been.
There are plenty out there. In one of the author’s examples, global warming is all but erased when the annual temperature for the past 130 years is plotted with a baseline starting at zero, resulting in a reassuringly flat line; in another, a dual-axis chart appears to show a shocking rise in abortions carried out by Planned Parenthood, a health-care provider, while their life-saving cancer-screenings plummet. In both cases, the structure is designed to mislead.
Deception can begin before the axes are drawn, when the content is selected. Truncating a time-scale to exclude awkward data—for instance, to omit a downturn in profits—is a well-known shady practice. So is overloading a graph to obscure an inconvenient truth. Sometimes the numbers are just plain wrong. In 2014 a blogger made a splash when he plotted state-level data from Pornhub, a website, and found Kansans were viewing far more porn than other Americans.
Mr Cairo uses this incident to consider the fallacy of drawing conclusions about individuals from group data. He commends the blogger for admitting his mistake, pointing out that this increases perceptions of trustworthiness. And his book reminds readers not to infer too much from a chart, especially when it shows them what they already wanted to see. Mr Cairo has sent a copy to the White House.
Another shot of his tiny hands.
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