Those Radical Bayesians

2 July 2007 at 8:45 am Leave a comment

| Peter Klein |

Statistics is apolitical, right? Maybe not.

I remember that in graduate school, Xiao-Li Meng, now editor of [Statistica Sinica], told me they didn’t teach Bayesian statistics in China because the idea of a prior distribution was contrary to Mao’s quotation, “truth comes out of empirical/practical evidence.” I have no idea how Thomas Bayes would feel about this, but Pierre-Simon Laplace, who is often regarded as the first applied Bayesian, was active in politics during and after the French Revolution.

In the twentieth-century Anglo-American statistical tradition, Bayesianism has certainly been seen as radical. As statisticians, we are generally trained to respect conservatism, which can sometimes be defined mathematically (for example, nominal 95% intervals that contain the true value more than 95% of the time) and sometimes with reference to tradition (for example, deferring to least-squares or maximum-likelihood estimates).

This is from Andrew Gelman’s introduction to a special issue of Statistica Sinica on Bayesian statistics. The China referencce reminds me of this LA Times story on the challenge of teaching Marxist theory in today’s China, where students couldn’t care less.

Entry filed under: - Klein -, Methods/Methodology/Theory of Science.

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