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Andrew Gelman: Ivy Jew Update: Noted

Andrew Gelman: Ivy Jew update:

Nurit Baytch posted a document, A Critique of Ron Unz’s Article “The Myth of American Meritocracy”, that is relevant to an ongoing discussion we had on this blog. Baytch’s article....

I shall demonstrate that Unz’s conclusion that Jews are over-admitted to Harvard... relied on faulty assumptions and spurious data: Unz substantially overestimated the percentage of Jews at Harvard while grossly underestimating the percentage of Jews among high academic achievers, when, in fact, there is no discrepancy.... Unz’s analysis of Jewish academic achievement is predicated on his ability to identify Jews on the basis of their names, which proved spectacularly wrong for the one data set on which there exists confirmed, peer-reviewed data....

Here’s the background. Several months ago we discussed a claim from Ron Unz that Ivy League colleges discriminate in favor of Jews, a claim that received wide attention after it was featured in the New York Times column of David Brooks. I originally reported statistical Unz’s claims uncritically.... I came to the conclusion that some of Unz’s numbers were way off.... This sort of thing happens: data can be slippery, and that’s one reason why open discussion and critique is so essential in much of science....

My take on all this is that it can be harder than it looks to do research using statistics. Unz’s original numbers appeared authoritative (enough so to fool Cowen, Brooks, and me, along with Unz himself) but they had big errors. To put it another way, Unz put in the effort to compile the statistics for his original article, and then Mertz and Baytch put in the effort to come up with cleaner, better numbers. That’s how things go.... Unfortunately, our blog discussion of all this with Unz did not go so well, in my judgment because we were seeing a mix of two different modes of discourse.... I think he sees the statistics provided by Mertz and Baytch as attacks to be dodged or parried rather than as useful information.... But for those of us how are not so invested... Baytch’s article, and Mertz’s from a few months ago, should be helpful....

This isn’t the first time that someone has made a high-profile claim that collapses in light of a careful look at the numbers. It’s the nature of statistics (and science more generally) that a researcher can see some data and put all the pieces together to form an appealing theory that explains many disparate observations, only to find later that the pattern was explained by various combinations of errors, missing data, and wishful thinking.

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