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Popper's view of probability, his propensity theory, differs from either of the two approaches discussed above.
Finite frequentism remains the dominant view of probability in statistics, and in the sciences more generally.
Bayesian induction incorporates a subjectivistic view of probability, according to which probability is identified with strength of belief.
For this reason Peirce is often considered to be the originator of the sort of "propensity view" of probability that is associated with Karl Popper.
Peirce's earliest account of the meaning of probability, then, is a version of what is called the "long run relative frequency view" of probability.
Presumably due to the influence of his colleague Richard von Mises, Reichenbach moved towards a view of probability as a property of sequences.
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Taking medicine as our focus we develop three lines of argument (historical, practical and cognitive) that suggest that traditional views of probability cannot accommodate all the competing demands and diverse constraints that arise in complex real-world domains.
(Indeed, it has zero chance even on most non-standard views of probability: Williamson 2007).
The chapter discusses problems of linking between structural analysis and design code procedures, especially from the point of view of semi-probability and probability approaches that, in general, lead to more transparent understanding of the reliability of structural members.
Popper also dabbled in some measures of verisimilitude, based on measures of content, which in turn he derived from measures of logical probability (somewhat ironically, given his dim view of logical probability).
In the Bayesian view of subjective probability, all unknown parameters are treated as uncertain and therefore should be described by a probability distribution.
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