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Hasty generalization

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Title: Hasty generalization  
Author: World Heritage Encyclopedia
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Subject: Anecdotal evidence, Fallacy of composition, Slothful induction, Converse accident, Accident (fallacy)
Collection: Inductive Fallacies, Informal Fallacies
Publisher: World Heritage Encyclopedia

Hasty generalization

Hasty generalization is an informal 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 a reasonable conclusion of an inductive argument (e.g. "it was just a coincidence").


  • Examples 1
  • Alternative names 2
  • See also 3
  • References 4
  • External links 5


Hasty generalization usually shows this pattern

  1. X is true for A.
  2. X is true for B.
  3. X is true for C.
  4. X is true for D.
  5. Therefore, X is true for E, F, G, etc.

For example, if a person travels through a town for the first time and sees 10 people, all of them children, he may erroneously conclude that there are no adult residents in the town.

Or: A person is looking at a number line. The number 1 is a square number; 3 is a prime number, 5 is a prime number, and 7 is a prime number; 9 is a square number; 11 is a prime number, and 13 is a prime number. Therefore, the person says, all odd numbers are either prime or square.

Alternative names

The fallacy is also known as:

  • Illicit generalization
  • Fallacy of insufficient sample
  • Generalization from the particular
  • Leaping to a conclusion
  • Hasty induction
  • Law of small numbers
  • Unrepresentative sample
  • Secundum quid

When referring to a generalization made from a single example it has been called the fallacy of the lonely fact[2] or the proof by example fallacy.[3]

When evidence is intentionally excluded to bias the result, it is sometimes termed the fallacy of exclusion and is a form of selection bias.[4]

See also


  1. ^ "Fallacy: Hasty Generalization (Nizkor Project)". Retrieved 2008-10-01. 
  2. ^ Fischer, David Hackett (1970). Historians' Fallacies: Toward a Logic of Historical Thought. HarperCollins. pp. 109–110.  
  3. ^ Marchant, Jamie. "Logical Fallacies". Retrieved 2011-04-26. 
  4. ^ "Unrepresentative Sample". Retrieved 2008-09-01. 

External links

  • Common Logical Fallacies in Propaganda and Debate
  • Fallacy: Hasty Generalization, Michael C. Labossiere's Fallacy Tutorial Pro
  • Hasty Generalization, The Fallacy Files
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