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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 ...
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 (sometimes written as post-hoc) is a Latin phrase, meaning "after this" or "after the event". Post hoc may refer to: 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
Boudry coined the term fallacy fork. [27] For a given fallacy, one must either characterize it by means of a deductive argumentation scheme, which rarely applies (the first prong of the fork), or one must relax definitions and add nuance to take the actual intent and context of the argument into account (the other prong of the fork). [27]
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 ...
Propter hoc may refer to: Cum hoc ergo propter hoc (Latin: "with this, therefore because of this"), an informal fallacy suggesting that when two events happen together, one must cause the other Post hoc ergo propter hoc (Latin: "after this, therefore because of this"), an informal fallacy suggesting that when an event follows another event, the ...
The regression (or regressive) fallacy is an informal fallacy. It assumes that something has returned to normal because of corrective actions taken while it was abnormal. This fails to account for natural fluctuations. It is frequently a special kind of the post hoc fallacy.
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 ...