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Bayes and BI


I've witnessed a practical illustration of this Bayesian thinking over the past several months. Since early January, I've spent half a dozen Saturdays and Sundays watching the  league matches for my daughter's 15 year old volleyball team. 160 Midwest teams started competition at 3 locales in the Chicagoland area at the beginning of 2009. The teams were seeded prior to play based on last year's performance, coaches' evaluations, random assignment of new clubs, etc. They then went through several rounds of pool play to further determine rankings for initial league competition that started later in the month. Won/Loss record and score differential determined the movement, if any, from initial ratings. Based on the preliminary rankings and the results of the first weekends of play, the teams were divided into 16 progressive brackets of 10 each for inter-bracket competition that will ultimately yield seedings for the national tournaments to be held in June. Teams migrate between ranked brackets during the season based on league performance, their likelihood function. At the end of the season, the initial rankings, the priors, and league/tournament performance, the likelihood, determine the ultimate team rankings after finals – the posteriors. Of course, the whole process starts over in 2010 for 16 year olds, with the 2009 posterior rankings becoming next year’s priors.

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Comments (2)
I would like to see an example of a calculation following the example situation. While the example situation is clear, the use of ~E and ~D in the proposed formula appears to be in error. While ~E appears twice in the formula, I don't see ~D in use at all. This may be a simple typo, but it muddies the concept for me.
Posted by Roy L | Tuesday, May 12 2009 at 12:58PM ET
Thanks for noting the oversight. There were actually 2 problems: a missing right parenthesis in the equation and the unnecessary reference to ~D. Both have been fixed.

Sorry for the confusion.

Posted by steve m | Wednesday, May 13 2009 at 7:36AM ET
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