Wikipedia:

hasty generalization

Hasty Generalization, is a logical fallacy of faulty generalization by reaching an inductive generalization based on insufficient evidence. It commonly involves basing a broad conclusion upon the statistics of a survey of a small group that fails to sufficiently represent the whole population. By induction we find that hasty generalizations by induction can be logically accurate if they are the specification of a broader hasty generalization.


Alternative Names

The fallacy is also known as: fallacy of insufficient statistics, fallacy of insufficient sample, fallacy of the lonely fact, leaping to a conclusion, hasty induction, law of small numbers, unrepresentative sample and secundum quid.

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