On Friday afternoon I asked Wonkblog readers to identify a mystery dataset that I'd mapped at the county level. Boy, did you deliver: I received a ton of responses via tweet and comment. Plus like, 37 guesses from The Switch's Brian Fung, all of which were wrong.
Many respondents thought it had something to do with race. Hari Nair saw a similarity with the 'black belt' in the South.
— Hari Nair (@SaintCopious) July 18, 2014
And indeed, the mystery data does seem to track pretty closely with the areas with a high black population, especially in the South. But black population doesn't explain the high shares of the mystery quantity in New England and parts of the Southwest. Another popular guess was prevalence of obesity. But that isn't right, either. Reid Wilson and I actually mapped this over at GovBeat not too long ago. You can see that obesity rates are relatively high in the Dakotas and Plains states, but the mystery quantity is fairly low in those areas.
Plenty of you pointed out that I screwed up a "less than" sign in the key - sorry, guys. Some of you went meta:
@_cingraham Population that has now been driven completely nuts by this question.
— The Political Game (@politicgame) July 18, 2014
Others went political:
Others tried to brute-force the problem:
— Ariel Edwards-Levy (@aedwardslevy) July 18, 2014
Still others weren't having it at all:
In the end, roughly 10 percent of you got it right. The data in question is the share of people in each county who have never been married.
This explains the high concentrations in certain Southern counties. These counties have large African-American populations, who have a significantly lower marriage rate than whites or Hispanics. On the other hand, people in Northeastern states like Massachusetts and New York tend to marry later in their lives than elsewhere, while people in the Midwest tend to marry younger.
Commenter Deweena was the first person to submit a correct answer, at 3:12 PM on Friday. I hereby award Deweena the Early Bird Prize for Prompt and Expeditious Accuracy.
But this wasn't the most precise answer. The good folks behind the Twitter account at Policy Map nailed it down to the data source and year, an impressive feat no matter how they pulled it off. For this, I grant them the title of Data Wizards/Ninjas/Unicorns/Whatevs, and hereby certify that, at least last Friday, they were Right on the Internet when so many others were wrong.
This was fun, wasn't it? Come back this Friday afternoon and we'll do another one.