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A logical fallacy of the questionable cause variety, it is subtly different from the fallacy cum hoc ergo propter hoc ('with this, therefore because of this'), in which two events occur simultaneously or the chronological ordering is insignificant or unknown. Post hoc is a logical fallacy in which one event seems to be the cause of a later ...
This fallacy is also known by the Latin phrase cum hoc ergo propter hoc ('with this, therefore because of this'). This differs from the fallacy known as post hoc ergo propter hoc ("after this, therefore because of this"), in which an event following another is seen as a necessary consequence of the former event, and from conflation , the errant ...
The flaw is failing to account for natural fluctuations. It is frequently a special kind of post hoc fallacy. Gambler's fallacy – the incorrect belief that separate, independent events can affect the likelihood of another random event. If a fair coin lands on heads 10 times in a row, the belief that it is "due to the number of times it had ...
Post hoc analysis or post hoc test, statistical analyses that were not specified before the data were seen; Post hoc theorizing, generating hypotheses based on data already observed; Post hoc ergo propter hoc (after this, therefore because of this), a logical fallacy of causation "Post Hoc, Ergo Propter Hoc" (The West Wing), an episode of the ...
The post hoc fallacy assumes that because B comes after A, A caused B. It gets its name from the Latin phrase "post hoc, ergo propter hoc", which translates as "after this, therefore because of this".
Since the question of "true causality" is deeply philosophical, and because of the post hoc ergo propter hoc fallacy of assuming that one thing preceding another can be used as a proof of causation, econometricians assert that the Granger test finds only "predictive causality". [2]
In a scientific study, post hoc analysis (from Latin post hoc, "after this") consists of statistical analyses that were specified after the data were seen. [ 1 ] [ 2 ] They are usually used to uncover specific differences between three or more group means when an analysis of variance (ANOVA) test is significant. [ 3 ]
In statistics, hypotheses suggested by a given dataset, when tested with the same dataset that suggested them, are likely to be accepted even when they are not true.This is because circular reasoning (double dipping) would be involved: something seems true in the limited data set; therefore we hypothesize that it is true in general; therefore we wrongly test it on the same, limited data set ...