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Hasty induction; Law of small numbers; Unrepresentative sample; Secundum quid; When referring to a generalization made from a single example, the terms fallacy of the lonely fact, [8] or the fallacy of proof by example, might be used. [9] When evidence is intentionally excluded to bias the result, the fallacy of exclusion—a form of selection ...
Hasty generalization (fallacy of insufficient statistics, fallacy of insufficient sample, fallacy of the lonely fact, hasty induction, secundum quid, converse accident, jumping to conclusions) – basing a broad conclusion on a small or unrepresentative sample. [55]
In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample [ 1 ] of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected ...
Generalizing quickly and sloppily (hasty generalization) (secundum quid) Using an argument's connections to other concepts or people to support or refute it, also called "guilt by association" (association fallacy) Claiming that a lack of proof counts as proof (appeal to ignorance) In humor, errors of reasoning are used for comical purposes.
[16]: 147 The generalization, in this case, ignores that insanity is an exceptional case to which the general rights of property do not unrestrictedly apply. Hasty generalization, on the other hand, involves the converse mistake of drawing a universal conclusion based on a small number of instances.
Despite samples being hand-picked, the goal is to ensure that no conscious bias exists within the choice of samples, but often fails due to selection bias. [19] Haphazard sampling is generally opted for due to its convenience, when the tools or capacity to perform other sampling methods may not exist.
Inductive reasoning is any of various methods of reasoning in which broad generalizations or principles are derived from a body of observations. [1] [2] This article is concerned with the inductive reasoning other than deductive reasoning (such as mathematical induction), where the conclusion of a deductive argument is certain, given the premises are correct; in contrast, the truth of the ...
The selective effect of cellular telephones on data collection (discussed in the Overgeneralization section) is one potential example; If young people with traditional telephones are not representative, the sample can be biased. Sample surveys have many pitfalls and require great care in execution. [18]