Jump to content

Hasty generalization

From Simple English Wikipedia, the free encyclopedia

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]

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.
[change | change source]


[change | change source]
  1. "Fallacy: Hasty Generalization" at Nizkor.org Archived 2008-12-17 at the Wayback Machine; 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" Archived 2012-06-30 at Archive.today; retrieved 2013-4-18.
  4. "Unrepresentative Sample"; retrieved 2013-4-18.

Other websites

[change | change source]