Probability

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PROBABILITY. That which is likely to happen; that which is most consonant to reason; for example, there is a strong probability that a man of a good moral character, and who has heretofore been remarkable for truth, will, when examined as a witness under oath, tell the truth; and, on the contrary, that a man who has been guilty of perjury, will not, under the same circumstances, tell the truth; the former will, therefore, be entitled to credit, while the latter will not.

A Law Dictionary, Adapted to the Constitution and Laws of the United States. By John Bouvier. Published 1856.
References in periodicals archive ?
As depicted in figure 1, Probabilistic reasoning is used in the decision-making module for arriving at a rational decision.
There is something to be said for the opinion of the mathematician George Polya, that pure mathematics is the best place to appreciate probabilistic reasoning. For in mathematics, there are no distractions from subjective factors or laws of nature.
by SAT scores, has been shown to correlate significantly with probabilistic reasoning skill (Jepson, Krantz, & Nisbett, 1983; Stanovich & West, 1998).
Probabilistic Reasoning: Many forms of information are inherently probabilistic--for example, given certain symptoms, we may be 80% confident the patient has hepatitis, or given some evidence, we may be 10% sure a specific stock will go up in price.
Further, we know the importance of probabilistic reasoning, and that the exigencies of human action often call for us to proceed on the basis of the "best" knowledge we can get in the circumstances.
In general, probabilistic reasoning is notoriously tricky.
Connectionist coherence models like ECHO provide a computationally efficient way of dealing with large numbers of elements (propositions).(5) In contrast, Achinstein has no working model of how probabilistic reasoning can produce the acceptance of the wave theory.
Probabilistic reasoning based on intensional semantics overcomes the difficulties described before.
Approximately probabilistic reasoning in Bayesian belief networks is NP-hard.
Ermon is recognized for his foundational work on probabilistic reasoning, machine learning, and decision making, with a range of novel applications in areas with broad societal impact.
Rather, we should understand (4) propensity via Aristotle's analysis of spontaneity (5) and probabilistic reasoning via the anti-PP and (6) the practice of bundling one-offs, where (7) forced bad-odds one-offs illuminate how extensive a role luck plays in our lives.

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