“The evidence of lived experience” vs. the statistics

John Kastellec sends in this blog entry by Jay Nordlinger, entitled “Dept. of Enduring Myths”:

I’ve just come back from a weekend in Vermont — and here’s how I understand it: Modestly off people — “real Vermonters,” as some people say — are voting for McCain and Palin. Comfortably off people, such as those who own ski chalets, are voting for Obama and Biden. And the following has been frequently noted about the city of my residence, New York: The rich are voting Democratic. And those who work for them — driving cars, cleaning rooms, and so on — are voting Republican.

Yet, when I was growing up, the Republican party was always called the party of the rich, and it still suffers from that label. Over and over, that which I was taught is contradicted by the evidence of my lived experience.

Here are the results from the 2000 and 2004 exit polls:


At a national level, Republicans did much better among the rich than the poor. In New England, the relation between income and voting is weak, with richer voters being slightly more likely to vote Republican. We’ll have to see what happens in 2008.

P.S. As statisticians we’re taught to rely less on our lived experience and on impressions from a weekend visit to Vermont, and more on random-sample survey data. And that’s what I’m doing here. But I have to admit that in many areas of my professional life (for example, in considering strategies for teaching and for research), I rely pretty much only on my lived experience and on the research equivalents of weekend visits to Vermont. Somehow, for things that affect me directly, statistical principles become less important. So I can see how, for a political journalist such as Nordlinger, it can be difficult to discount one’s personal impressions. Nonetheless, I hope he can do so.

7 thoughts on ““The evidence of lived experience” vs. the statistics

  1. Razib: The funny thing is, I never look at that site. It just happens that my collaborator saw this and emailed it to me. Also, thanks for the link. I looked up Maine at the CNN site and for some reason the numbers look slightly different from my graph above. So I'll have to figure out what's going on here at some point. . . .

  2. What it takes to be a statistician these days.

    Not much.

    You can't even plot data correctly. Columbia!

    Those data points aren't connected! Why would you connect them? Ever hear of error bars? Box and whisker plots?

    I wish I could be this careless and teach statistics at a supposed "Ivy League" school.

  3. MikeTee: Yep, I agree. Standards are just getting lower and lower. It's distressing to see the low qualifications of statistics faculty nowadays. Something's gotta be done about this!

  4. MikeTee: lighten up!

    (a) box and whisker plots might not be appropriate in this context, since the lines are estimates from multi-level models that already assuming things like normality (b&w are better for raw data) [but perhaps you just meant "b&w plots OR error bars?];
    (b) yes, error bars would be nice, but I think the general idea with continuous or ordinal covariates (it looks like there are 6 categories here) is that the amount of "random" (i.e. non-smooth) variation is supposed to give the reader a sense of the "error variance" and hence of the reliability of some smooth relationship.
    (c) the connected lines are presumably to give a sense of the response, if any, of voting preference as f(income). Why *not* connect these data? (I probably wouldn't for 3 categories, but for 6 I would).

    [Andrew: would you like to comment on the choice of binning the data (how many cutpoints?) vs. polynomial vs. spline regression in this case?]

    Ben Bolker

  5. "So I can see how, for a political journalist such as Nordlinger, it can be difficult to discount one's personal impressions. Nonetheless, I hope he can do so."

    I would say that a political jounalist should not fall for a variation on the famous 'nobody *I* know voted for Nixon' trap.

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