Posts Tagged With: Colin Howson

Does the Bayesian Diet Call For Error-Statistical Supplements?

Some of the recent comments to my May 20 post leads me to point us back to my earlier (April 15) post  on dynamic dutch books, and continue where Howson left off:

“And where does this conclusion leave the Bayesian theory? ….I claim that nothing valuable is lost by abandoning updating rules.  The idea that the only updating policy sanctioned by the Bayesian theory is updating by conditionalization was untenable even on its own terms, since the learning of each conditioning proposition could not  itself have been by conditionalization.” (Howson 1997, 289).

So a Bayesian account requires a distinct account of empirical learning in order to learn “of each conditioning proposition” (propositions which may be statistical hypotheses).  This was my argument in EGEK (1996, 87)*. And this other account, I would go on to suggest, should ensure the claims (which I prefer to “propositions”) are reliably warranted or severely corroborated.

*Error and the Growth of Experimental Knowledge (Mayo 1996):  Scroll down to chapter 3.

Categories: Statistics | Tags: , , | 32 Comments

Blog at