DEC 7, 2010 10:31am ET

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Bayes and Risk Management – Part 2


Last week's blog introduced Bayes theorem for conditional probability and contrasted the Bayesian and frequentist approaches in modern statistics, noting that the frequentist camp dominated when I studied 30 years ago. Now, however, though frequentism is still on top, the playing surface is much more level, with a steeper trajectory for Bayes.

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Comments (2)
Although it has been 30+ years since I took statistics, I had the good fortune (as an undergrad) to have a professor spend a fair amount of time equating if|then to Bayesian statistics. Even though this pre-dated the advent of the personal computer and lots of programming coursed, it struck me as reasonable. It still does.

So, from a perspective of "reasonable", would it be reasonable to assume the "frequentist" model of statistics could be used, over time, to validate the quality of the "priors" used in Bay3sian analysis to at least some degree, thus over time improving the quality of the information and utilizing the best aspects of both analytical approaches? Or should I go back to sleep for another 30+ years?

Thanks for your blogs, I always thoroughly enjoy and appreciate your perspective.

Posted by Gary B | Wednesday, December 08 2010 at 6:07PM ET
Gary --

Please stay awake -- you're absolutely correct!

The evolution from subjective to uninformative priors puts the scientific rigor of frequentistism to work for the Bayesian method. As Brad Efron notes, Empirical Bayes and computational statistics offer much promise for the field.


Posted by steve m | Thursday, December 09 2010 at 8:08AM ET
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