Hasty generalization is a logical fallacy of faulty generalization by reaching an inductive generalization based on insufficient evidence — essentially making a hasty conclusion without considering all of the variables. In statistics, it may involve basing broad conclusions regarding the statistics of a survey from a small sample group that fails to sufficiently represent an entire population.[1] Its opposite fallacy is called slothful induction, or denying the logical conclusion of an inductive argument (e.g. "it was just a coincidence").
Context is also relevant; in mathematics, the Pólya conjecture is true for numbers less than 906,150,257, but fails for this number. Assuming something to be true for all numbers when it has been shown for over 906 million cases would not generally be considered hasty, but in mathematics a statement remains a conjecture until it is shown to be universally true.
Hasty generalization can also be a basis for racist beliefs and prejudices, in which inferences regarding a large group is based upon knowledge of only a small sample size of that group. For example, stereotypical notions that are portrayed in mass media, such as a given person who is Jewish is also inherently greedy, the notion of a person being black equates to that person being poor and/or criminal, or the notion that a caucasian person is therefore lacking in style are all logical fallacies. This includes positive racist ideologies as well, such as the belief that Asians are better off academically than other racial sectors.[2][3]
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The fallacy is also known as the fallacy of insufficient statistics, fallacy of insufficient sample, generalization from the particular, leaping to a conclusion, hasty induction, law of small numbers, unrepresentative sample, and secundum quid. When referring to a generalization made from a single example it has been called the fallacy of the lonely fact[4] or the proof by example fallacy.[5]
When evidence is intentionally excluded to bias the result, it is sometimes termed the fallacy of exclusion and is a form of selection bias.[6]
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