this paper - William M. Briggs
... usually assigned equal probability. The usual reasons given for equiprobable assignment are: ignorance, “no reason” or indifference, noninformativeness, symmetry, randomness, and some very well known mathematical arguments. All of these arguments, by no means mutually exclusive, will be shown to be ...
... usually assigned equal probability. The usual reasons given for equiprobable assignment are: ignorance, “no reason” or indifference, noninformativeness, symmetry, randomness, and some very well known mathematical arguments. All of these arguments, by no means mutually exclusive, will be shown to be ...
Coherent conditional probabilities and proper scoring rules
... In ([33], p. 204) the authors leave open the question of whether their results still hold if one restricted the notion of coherence to require that the axioms of probability conditional on events with zero probability be satisfied. Our answer to this open question is that the equivalence between coh ...
... In ([33], p. 204) the authors leave open the question of whether their results still hold if one restricted the notion of coherence to require that the axioms of probability conditional on events with zero probability be satisfied. Our answer to this open question is that the equivalence between coh ...
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... for all 1 ≤ i 1 < i 2 < · · · < i k ≤ n, 2 ≤ k ≤ n. The following examples (cf. Majerak et al. 2005) show that the independence of events does not imply conditional independence and that the conditional independence of events does not imply their independence. Example 1 Let = {1, 2, 3, 4, 5, 6, 7, ...
... for all 1 ≤ i 1 < i 2 < · · · < i k ≤ n, 2 ≤ k ≤ n. The following examples (cf. Majerak et al. 2005) show that the independence of events does not imply conditional independence and that the conditional independence of events does not imply their independence. Example 1 Let = {1, 2, 3, 4, 5, 6, 7, ...
From Cournot`s Principle to Market Efficiency
... he argued, for a heavy cone to stand in equilibrium on its vertex, but it is physically impossible. The event’s probability is vanishingly small. Similarly, it is physically impossible for the frequency of an event in a long sequence of trials to differ substantially from the event’s probability [31 ...
... he argued, for a heavy cone to stand in equilibrium on its vertex, but it is physically impossible. The event’s probability is vanishingly small. Similarly, it is physically impossible for the frequency of an event in a long sequence of trials to differ substantially from the event’s probability [31 ...
The "slippery" concept of probability: Reflections on possible
... to what Konold (1991) terms the “outcome approach” in which pupils think they are being asked whether an event will occur, rather than quantifying how likely the event is. Pupils using this approach therefore do not see the result of a single trial as one of many such trials in an experiment, but re ...
... to what Konold (1991) terms the “outcome approach” in which pupils think they are being asked whether an event will occur, rather than quantifying how likely the event is. Pupils using this approach therefore do not see the result of a single trial as one of many such trials in an experiment, but re ...
Confirmation Theory
... never arise in ordinary life. So much for Ramsey’s argument. Another popular argument against the existence of logical probabilities is based on the “paradoxes of indifference”. The argument is this: Judgments of logical probability are said to presuppose a general principle, called the Principle of ...
... never arise in ordinary life. So much for Ramsey’s argument. Another popular argument against the existence of logical probabilities is based on the “paradoxes of indifference”. The argument is this: Judgments of logical probability are said to presuppose a general principle, called the Principle of ...
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... P(desired order) = s s+f = (2 favorite 1st in order)(3 least last, any order) total possible order = (1 nPr 1)(3 nPr 3)/(6 nPr 6) ≈ 0.0083 ≈ 0.8% ...
... P(desired order) = s s+f = (2 favorite 1st in order)(3 least last, any order) total possible order = (1 nPr 1)(3 nPr 3)/(6 nPr 6) ≈ 0.0083 ≈ 0.8% ...