Hasty generalization

From Wikipedia, the free encyclopedia
Jump to: navigation, search

Hasty generalization is an informal fallacy of generalisation by making decisions based on too little evidence or without recognizing all of the variables. In statistics, it may mean basing broad conclusions of a survey from a small sample group.[1]

A hasty generalization made from a single example is sometimes 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".[4]

Example[change | change source]

Hasty generalization may follow this pattern

X is true for A.
X is true for B.
X is true for C.
X is true for D.
Therefore, X is true for E, F, G, etc.

Related pages[change | change source]

References[change | change source]

  1. "Fallacy: Hasty Generalization" at Nizkor.org; retrieved 2013-4-18.
  2. Fisher, David Hackett. (1970). Historians' Fallacies: Toward a Logic of Historical Thought, pp. 109-110.
  3. Marchant, Jamie. "Logical Fallacies"; retrieved 2013-4-18.
  4. "Unrepresentative Sample"; retrieved 2013-4-18.

Other websites[change | change source]