Bayesian Blues

Bayesian methods continue to gain attention as a better means to solve problems and predict outcomes. It was Google that used such algorithms to tune its brilliant search engine, and much more. Nate Silver carried the Bayesian chorus along with his depiction of the method in "The Signal and the Noise." Today, in fact, Bayesian thinking is very broadly adapted - enough so for the New York Times to devote a feature entitled "The Odds, Continually Updated" in this week's Science Times section.

Thomas Bayes writer F.T. Flam [I am not making this up] says set out to calculate the probability of God's existence. This was back in the 19th Century in jolly old England. The math was difficult and really beyond the ken of calculastion - until the recent profusion of clustered computer power. Almost a MacGuffin in the narrative is the overboard Long Island fisherman John Aldrich who the Coast Guard found in the Atlantic Ocean to that services use of Bayesian methods.

"The Odds, Continually Updated'' places more import on the possibility that Bayesian statistics have narrowed down the possible correct answers for the age of the earth (from existing estimations that it was 8 B to 15 B years old, to conjectures that it is 13.8 B years old. - Jack Vaugahn


An extended version* of this piece would consider:
Who was Bayes and what is Bayesian math?
How does it compare to frequentist statistics (the main point of the story)? If frequentist methods were aptly applied would they work in most cases?
How does this all relate to the looming question (smaller)of how much we can  trust data science and (bigger) how much we can trust science?

*for now this site like most blogs comprises free ruminations - and sometimes you get what you pay for.