Posts

Showing posts with the label Bayesian inference

Will the Cubs Be Swept?

Major league baseball analysts were asked the above question after the Mets had won the first two games against the Cubs. Several of them respond, "No, the Cubs are too good a team to be swept." I think they were not being good Bayesian reasoners. They had a prior: "The Cubs are a good team, and the Mets cannot sweep them." In other words, the Mets cannot win four straight games against a team as good as the Cubs. But they were failing to update this prior given new data. First of all, having won the first two games, the odds of the Mets "winning four straight games" became irrelevant: the only relevant odds were of their now winning two straight games. Secondly, the Mets' decisive wins in games one and two should have altered their evaluation of the relative strength of the two teams: the Mets were playing particularly well, while the Cubs were not, and thus the odds of the Mets winning two (more) straight games ought to have increased in t...

A Bayesian Spirit Catcher

Image
Since my recent posts on material and spiritual explanations have been so egregiously misunderstood by some commenters, let me try again, with a new tack. Bayesian inference is given by the rule: Our H is: "Hildegard of Bingen had visions sent from God." Our E is that we discover that Hildegard was suffering from migraines. (By the way, this idea is just sheer speculation on the part of Oliver Sacks, with little evidence behind it. But let us imagine it confirmed.) Let us say someone like my friend Ben Kay has the prior P(H) that Hildegard experienced divine visions of 0. (Ben is a committed atheist.) Then E arrives. Ben touts it as, "See, she just had migraines." But this is insincere: with a P(H) of 0, for any evidence that arrives, Ben will have a P(H | E) of 0! I have another friend, an Inuit fellow named Nahallak, who thinks Hildegard's life story makes her report of divine visions likely, so that he has a P(H) of .8. But he is also...

Sitting on the Dock of the Bayes

Over at Think Markets , I discuss the limits of Bayesian inference .