Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-17T14:41:39.454Z Has data issue: false hasContentIssue false
  • English
  • Français

Dutch Book Arguments and Consistency

Published online by Cambridge University Press:  19 June 2023

Colin Howson
Colin Howson*
Affiliation:
The London School of Economics and Political Science
Rights & Permissions [Opens in a new window]

Extract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Classical Bayesian methodology is based on the following three principles:

  1. (i) individuals have degrees of belief which, measured in the closed unit interval, and subject to a mild consistency constraint, are fonnally probabilities.

  2. (ii) belief functions are updated with the acquisition of new evidence by Bayesian conditionalisation. In other words, if B is learned to be true, then your new probability function P′ takes the value P′(A) = P(A/B) on every A in domain P′, where P is your probability function prior to learning B.

  3. (iii) where Hi is a statistical hypothesis and E sample data, the tenns P(E|Hi) in Bayes’ Theorem calculations are set equal to the probability assigned E by Hi.

Type
Part V: Bayesian Philosophy of Science
Information
PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association , Volume 1992 , Issue 2: Volume Two: Symposia and Invited Papers 1992 , 1993 , pp. 161 - 168
Copyright
Copyright © 1993 by the Philosophy of Science Association

References

Armendt, B. (1980), “ Is there a Dutch Book Argument for Probability Kinematics?”, Philosophy of Science, 47: 583-588CrossRefGoogle Scholar
Christensen, D. (1991), “Clever Bookies and Coherent Beliefs”, Philosophical Review, 229-247.CrossRefGoogle Scholar
de Finetti, B. (1937), “Foresight: its Logical Laws, its Subjective Sources”, (English translation of “La prevision: ses lois logiques, ses sources subjectives“) Studies in Subjective Probability, H.E. Kyburg and H. Smokler (eds), New York: Krieger, 1980.Google Scholar
Hacking, I. (1967), “Slightly More Realistic Personal Probability”, Philosophy of Science, 34: 311-325.CrossRefGoogle Scholar
Halmos, P. (1950), Measure Theory, New York: van Nostrand.CrossRefGoogle Scholar
Howson, C. and Urbach, P. (1993), Scientific Reasoning: the Bayesian Approach (second edition). Chicago: Open Court.Google Scholar
Jeffrey, R. C. (1987), Probability and the Art of Reasoning. Cambridge: Cambridge University Press.Google Scholar
Lewis, D. (1976), “Probabilities of Conditionals and Conditional Probabilities”, Philosophical Review, 85: 297-315.CrossRefGoogle Scholar
Mellor, D. H. (1971), The Matter of Chance. Cambridge: Cambridge University Press.Google Scholar
Skyrms, B. (forthcoming), “A Mistake in Dynamic Coherence Arguments”Google Scholar
Teller, P. (1973), “Conditionalisation and Observation”, Synthese, 26: 218-258.CrossRefGoogle Scholar
van Fraassen, B.C. (1984), “Belief and the Will”, Journal of Philosophy, 81: 235-256.CrossRefGoogle Scholar
van Fraassen, B.C. (1989), Laws and Symmetry, Oxford: the Clarendon Press.CrossRefGoogle Scholar