Hasty generalization
informal fallacy of faulty generalization by reaching an inductive generalization based on insufficient evidence—essentially making a rushed conclusion without considering all of the variables
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]
ExampleEdit
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 pagesEdit
ReferencesEdit
- ↑ "Fallacy: Hasty Generalization" at Nizkor.org Archived 2008-12-17 at the Wayback Machine; retrieved 2013-4-18.
- ↑ Fisher, David Hackett. (1970). Historians' Fallacies: Toward a Logic of Historical Thought, pp. 109-110.
- ↑ Marchant, Jamie. "Logical Fallacies" Archived 2012-06-30 at Archive.today; retrieved 2013-4-18.
- ↑ "Unrepresentative Sample"; retrieved 2013-4-18.