CONVENTIONAL WISDOM WATCH….Brendan Nyhan crunches some numbers to test the conventional wisdom about Barack Obama’s support and concludes that some of it is true and some isn’t. He looks at five pieces of CW: (1) Obama does better in caucus states, (2) he does better in states with either few blacks or lots of blacks, (3) he does worse in states with lots of Hispanics, (4) he does worse in big states, and (5) he does worse in heavily Democratic states. He concludes that only (1) and (2) are true:
It’s hard to separate the associations between these variables because larger states are (on average) more black and Hispanic, more Democratic, and less likely to have caucuses. But when we put all these factors together in a linear regression (including both black population and black population squared), we find that the U-shaped quadratic relationship for black population and the positive relationship for caucuses are statistically significant, while the other factors are not. In other words, the evidence so far is consistent with the conventional wisdom that Obama does best in heavily black and heavily white states and in caucuses and he does less well in moderately black states and primaries.
I’d add a caveat to this. Brendan actually finds that all five pieces of CW are true, but that the last three aren’t statistically significant. In other words, there’s at least a 5% possibility that they might be the result of chance.
But this is a one shot deal, and I wonder if the results are significant at, say, a 90% level? In an academic setting this wouldn’t be good enough, but in a real-life setting where this is the only data you have (no followup studies, folks!), most people would probably think that 90% certainty was fairly convincing. For better or worse, it looks to me like the CW is likely true on all five counts.
UPDATE: In a demonstration of the blogosphere at work, Brendan responds almost instantly:
To answer the question, the other variables aren’t close to being significant. However, I wouldn’t put too much stock in the results of any of these hypothesis tests because (a) hypothesis testing is riddled with epistemological problems and (b) it’s difficult to achieve significance in small samples.
So don’t pay any attention to any of this stuff. But at least there are some nifty charts for you to go look at.