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Informal fallacies – arguments that are logically unsound for lack of well-grounded premises. [14] Argument from incredulity – when someone can't imagine something to be true, and therefore deems it false, or conversely, holds that it must be true because they can't see how it could be false. [15]
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 ...
This category is for inductive fallacies, or faulty generalizations, arguments that improperly move from specific instances to general rules. Pages in category "Inductive fallacies" The following 21 pages are in this category, out of 21 total.
An example of a language dependent fallacy is given as a debate as to who in humanity are learners: the wise or the ignorant. [18]: 3 A language-independent fallacy is, for example: "Coriscus is different from Socrates." "Socrates is a man." "Therefore, Coriscus is different from a man." [18]: 4
In logic and mathematics, proof by example (sometimes known as inappropriate generalization) is a logical fallacy whereby the validity of a statement is illustrated through one or more examples or cases—rather than a full-fledged proof. [1] [2] The structure, argument form and formal form of a proof by example generally proceeds as follows ...
The false implication is that their foreign policy always helps other countries. The rhetorical use of the fallacy can be used to comic effect, as in the below examples: "All right, but apart from the sanitation, the medicine, education, wine, public order, irrigation, roads, a fresh water system, and public health...
An example of the base rate fallacy is the false positive paradox (also known as accuracy paradox). This paradox describes situations where there are more false positive test results than true positives (this means the classifier has a low precision). For example, if a facial recognition camera can identify wanted criminals 99% accurately, but ...
G. I. Joe fallacy, the tendency to think that knowing about cognitive bias is enough to overcome it. [66] Gambler's fallacy, the tendency to think that future probabilities are altered by past events, when in reality they are unchanged. The fallacy arises from an erroneous conceptualization of the law of large numbers. For example, "I've ...