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Plausible reasoning is commonly based on appearances from perception. Stability is an important characteristic of plausible reasoning. Plausible reasoning can be tested, and by this means, confirmed or refuted. Probing into plausible reasoning in a dialogue is a way of testing it.
Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...
Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the possibility of common and alternative ("special") causes.
One viewpoint on this question is that cause and effect are of one and the same kind of entity, causality being an asymmetric relation between them. That is to say, it would make good sense grammatically to say either "A is the cause and B the effect" or "B is the cause and A the effect", though only one of those two can be actually true.
Therefore, to the same natural effects we must, as far as possible, assign the same causes." [20] [21] In the sentence hypotheses non fingo, Newton affirms the success of this approach. Bertrand Russell offers a particular version of Occam's razor: "Whenever possible, substitute constructions out of known entities for inferences to unknown ...
Causal reasoning is the process of identifying causality: the relationship between a cause and its effect.The study of causality extends from ancient philosophy to contemporary neuropsychology; assumptions about the nature of causality may be shown to be functions of a previous event preceding a later one.
Torrens found that “the extent of an individual's belief bias effect was unrelated to a number of measures of reasoning competence” but was, instead, related to that person's ability “to generate alternative representations of premises: the more alternatives a person generated, the less likely they were to show a belief bias effect." [20]
Cum hoc ergo propter hoc (Latin for 'with this, therefore because of this'; correlation implies causation; faulty cause/effect, coincidental correlation, correlation without causation) – a faulty assumption that, because there is a correlation between two variables, one caused the other. [57]