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Hasty generalization is the fallacy of examining just one or very few examples or studying a single case and generalizing that to be representative of the whole class of objects or phenomena. The opposite, slothful induction , is the fallacy of denying the logical conclusion of an inductive argument, dismissing an effect as "just a coincidence ...
Style over substance – embellishing an argument with compelling language, exploiting a bias towards the esthetic qualities of an argument, e.g. the rhyme-as-reason effect [85] Wishful thinking – arguing for a course of action by the listener according to what might be pleasing to imagine rather than according to evidence or reason.
The full generalization rule allows for hypotheses to the left of the turnstile, but with restrictions.Assume is a set of formulas, a formula, and () has been derived. The generalization rule states that () can be derived if is not mentioned in and does not occur in .
Bird with earthworm: Shepard gives example of bird using "generalization," based on experience with one previous worm, to decide if another worm is edible. The universal law of generalization is a theory of cognition stating that the probability of a response to one stimulus being generalized to another is a function of the “distance ...
An example is a probabilistically valid instance of the formally invalid argument form of denying the antecedent or affirming the consequent. [ 12 ] Thus, "fallacious arguments usually have the deceptive appearance of being good arguments, [ 13 ] because for most fallacious instances of an argument form, a similar but non-fallacious instance ...
For example: Almost all people are taller than 26 inches; Gareth is a person; Therefore, Gareth is taller than 26 inches; Premise 1 (the major premise) is a generalization, and the argument attempts to draw a conclusion from that generalization. In contrast to a deductive syllogism, the premises logically support or confirm the conclusion ...
Goodhart's law is an adage often stated as, "When a measure becomes a target, it ceases to be a good measure". [1] It is named after British economist Charles Goodhart , who is credited with expressing the core idea of the adage in a 1975 article on monetary policy in the United Kingdom: [ 2 ]
The law of truly large numbers (a statistical adage), attributed to Persi Diaconis and Frederick Mosteller, states that with a large enough number of independent samples, any highly implausible (i.e. unlikely in any single sample, but with constant probability strictly greater than 0 in any sample) result is likely to be observed. [1]