P(“hee haw haw”|Mr) = P(hee|Mr)*P(haw|Mr)*P(haw|Mr) = .2*.8*.8 = 8/125

P(“hee haw haw”|Mrs) = P(hee|Mrs)*P(haw|Mrs)*P(haw|Mrs) = .6*.4*.4 = 12/125

So the odds for the Mr are 12:8 == 3:2 (since he’s the underdog).

]]>I’d hate to be arguing about priors in a theological context!

My first year at Edinburgh Uni (1984/85) I lived in the international dorm, which is next to New College, the seat of Presbyterianism. Bayes and I pounded the same pavement!

]]>Sex Ratio Theory, Ancient and Modern

Elliott Sober

http://tinyurl.com/7kjts9

God of Chance

David J. Bartholomew

http://www.godofchance.com/godofchance_ch3.pdf

http://www.godofchance.com/

This was one of the first applications of Bayes’ Theorem:

The Reverend Thomas Bayes, FRS: A Biography to Celebrate the Tercentenary of His Birth

D. R. Bellhouse

http://www.york.ac.uk/depts/maths/histstat/bayesbiog.pdf

(I’m an atheist with an interest in the history of ideas.)

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