Graduate studies at Western
Philosophy of Science 40 (2):227-233 (1973)
|Abstract||It has been alleged that Bayesian usage of prior probabilities allows one to obtain empirical statements on the basis of no evidence whatever. We examine this charge with reference to several examples from the literature, arguing, first, that the difference between probabilities based on weighty evidence and those based on little evidence can be drawn in terms of the variance of a distribution. Moreover, qua summaries of vague prior knowledge, prior distributions only transmit the empirical information therein contained and, therefore, their consequences for long-run frequency behavior are "a priori" in at best a Pickwickian sense|
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
|Through your library||Configure|
Similar books and articles
Henry E. Kyburg Jr (1992). Getting Fancy with Probability. Synthese 90 (2):189 - 203.
Henry E. Kyburg (1992). Getting Fancy with Probability. Synthese 90 (2):189-203.
Paul K. Moser (1988). The Foundations of Epistemological Probability. Erkenntnis 28 (2):231 - 251.
Jukka Corander & Pekka Marttinen (2006). Bayesian Model Learning Based on Predictive Entropy. Journal of Logic, Language and Information 15 (1-2):5-20.
Festa, Roberto, Optimum Inductive Methods. A Study in Inductive Probability, Bayesian Statistics, and Verisimilitude.
Bengt Autzen (2011). Constraining Prior Probabilities of Phylogenetic Trees. Biology and Philosophy 26 (4):567-581.
Keith Lehrer (1983). Rationality as Weighted Averaging. Synthese 57 (3):283 - 295.
Richard Swinburne (2008). Bayes's Theorem. Gogoa 8 (1):138.
Added to index2009-01-28
Total downloads2 ( #246,859 of 739,080 )
Recent downloads (6 months)0
How can I increase my downloads?