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The fallacy can take many forms, such as cherry picking, hasty generalization, proof by assertion, and so on. [1] The fallacy does not mean that every single instance of sense data or testimony must be considered a fallacy, only that anecdotal evidence, when improperly used in logic, results in a fallacy.
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]
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 ...
Hasty generalization often follows a pattern such as: X is true for A. X is true for B. Therefore, X is true for C, D, etc. While never a valid logical deduction, if such an inference can be made on statistical grounds, it may nonetheless be convincing. This is because with enough empirical evidence, the generalization is no longer a hasty one.
Blind men and the elephant, 1907 American illustration. Blind Men Appraising an Elephant by Ohara Donshu, Edo Period (early 19th century), Brooklyn Museum. The parable of the blind men and an elephant is a story of a group of blind men who have never come across an elephant before and who learn and imagine what the elephant is like by touching it.
[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.
Anecdotal evidence is considered the least certain type of scientific information. [24] Researchers may use anecdotal evidence for suggesting new hypotheses, but never as validating evidence. [25] [26] If an anecdote illustrates a desired conclusion rather than a logical conclusion, it is considered a faulty or hasty generalization. [27]
Inductive reasoning refers to a variety of methods of reasoning in which broad generalizations or principles are derived from a set of observations. [1] [2] Unlike deductive reasoning (such as mathematical induction), where the conclusion is certain, given the premises are correct, inductive reasoning produces conclusions that are at best probable, given the evidence provided.