law of parsimony kinesiology

of what has been called the "principle of parsimony." Ockham and Morgan The first statement of such a principle is usually credited to William of Ockham, a fourteenth century English scholastic and philosopher, though the concept can be found in Aristotle and though, in Ockham's day, it was first stated by Duns Scottus (Boehner; 1957). It is not clear as to whom this principle can be conclusively . Possibility B is that your dog ate it. Often equated with Occam's Razor, the law is not . The model they propose balances the precision of a theory's predictions against their sharpness, preferring theories that sharply make correct predictions over theories that accommodate a wide range of other possible results. [6] There are, however, notable exceptions where Occam's razor turns a conservative scientist into a reluctant revolutionary. Occams razor is also often used to debunk conspiracy theories. Berkeley was an idealist who believed that all of reality could be explained in terms of the mind alone. For example, if a man, accused of breaking a vase, makes supernatural claims that leprechauns were responsible for the breakage, a simple explanation might be that the man did it, but ongoing ad hoc justifications (e.g. Though it is impossible to appreciate the spiritual when limiting oneself to the physical[citation needed], Smart maintained that identity theory explains all phenomena by assuming only a physical reality. Zoology provides an example. The concept is related but not identical to the legal concept of proportionality. A person, in 1300, Occam penned these words "numquam nenena plurality sine necessitate," which can be . One justification of Occam's razor is a direct result of basic probability theory. Likewise, in science, Nicole dOresme, a 14th-century French physicist, invoked the law of economy, as did Galileo later, in defending the simplest hypothesis of the heavens. [40] They state, "A hypothesis with fewer adjustable parameters will automatically have an enhanced posterior probability, due to the fact that the predictions it makes are sharp.

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