As numbers-oriented folk here at TDS, we can’t resist a shout-out for Paul Waldman’s article for The American Prospect today, which examines why the extraordinary availability of good data these days hasn’t translated into a rejection of bad data, at least in the United States.
Waldman blames some of the bogus credibility of bad data on the media, where the quality of data is rarely policed::
How many times in recent years has [the press] treated some bogus figure put out by one side of a political debate as though it might be true, depending on how you look at it? To take just one example, consider the gift that The New York Times offered up to anti-union forces last November, when a now notorious article by Andrew Ross Sorkin claimed that Big Three autoworkers were being paid $70 per hour. It was false — the average worker was actually making $28 an hour. The $70 figure came from disingenuously combining four separate expenses incurred by the automakers, only one of which is actual wages. But that didn’t stop conservative opponents of aid to the automakers from turning factory workers into the villains of the story, a bunch of greedy layabouts sucking the companies dry and driving them to ruin. The truth didn’t much matter — the idea ricocheted around the media for weeks.
The right thing for any reporter to do when confronted with the claim would have been to say, “I’m sorry, Mr. Conservative Think Tank guy, but you and I both know that autoworkers don’t make $70 an hour. Is there anything else you’d like to add — that’s not a lie — that I can use in my story?” But reporters don’t necessarily say that sort of thing. And this is just one case. Journalists’ lack of even the most rudimentary understanding of statistics is evident on the news pages and broadcasts nearly every day.
But Waldman goes on to suggest that cultural factors are at play, including the taste for quackery evidence in popular culture; the poor math and statistical skills of the American population; and a general inability to differentiate between those questions “the numbers” can help answer, and those they can’t.