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.
Examples
Person A travels through Town X for the first time. He sees 10 people, all of them children. Person A returns to his town and reports that there are no adult residents in Town X.Person A and Person B walk past a pawn shop. Person A remarks that a watch in a window display looks like the one his grandfather used to wear. On the basis of this remark, Person B concludes that:
- Person A's grandfather pawned his watch; or
- Person A's grandfather had expensive tastes in jewellery; or
- Person A's grandfather was ostentatious; or
- Person A's grandfather can not tell the time any more.
In mathematics the Pólya conjecture is true for numbers less than 906150257, but fails for this number. Believing conjectures to be true because they hold for some number of examples (however large that may be) would be an example of hasty generalization.
Alternative names
The fallacy is also known as: fallacy of insufficient statistics, fallacy of insufficient sample, fallacy of the lonely fact, generalization from the particular, leaping to a conclusion, hasty induction, law of small numbers, unrepresentative sample, and secundum quid.When evidence is intentionally excluded to bias the result, it is sometimes termed the fallacy of exclusion and is a form of selection bias.
References
See also
- Accident (fallacy)
- Blind Men and an Elephant
- Converse accident
- Cognitive distortion
- Hypercorrection
- Loki's Wager
- Syllogism
External links
- Fallacy: Hasty Generalization, Michael C. Labossiere's Fallacy Tutorial Pro
This article is licensed under the GNU Free Documentation License.
Last updated on Thursday October 02, 2008 at 05:39:37 PDT (GMT -0700)
View this article at Wikipedia.org - Edit this article at Wikipedia.org - Donate to the Wikimedia Foundation
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.
Examples
Person A travels through Town X for the first time. He sees 10 people, all of them children. Person A returns to his town and reports that there are no adult residents in Town X.Person A and Person B walk past a pawn shop. Person A remarks that a watch in a window display looks like the one his grandfather used to wear. On the basis of this remark, Person B concludes that:
- Person A's grandfather pawned his watch; or
- Person A's grandfather had expensive tastes in jewellery; or
- Person A's grandfather was ostentatious; or
- Person A's grandfather can not tell the time any more.
In mathematics the Pólya conjecture is true for numbers less than 906150257, but fails for this number. Believing conjectures to be true because they hold for some number of examples (however large that may be) would be an example of hasty generalization.
Alternative names
The fallacy is also known as: fallacy of insufficient statistics, fallacy of insufficient sample, fallacy of the lonely fact, generalization from the particular, leaping to a conclusion, hasty induction, law of small numbers, unrepresentative sample, and secundum quid.When evidence is intentionally excluded to bias the result, it is sometimes termed the fallacy of exclusion and is a form of selection bias.
References
See also
- Accident (fallacy)
- Blind Men and an Elephant
- Converse accident
- Cognitive distortion
- Hypercorrection
- Loki's Wager
- Syllogism
External links
- Fallacy: Hasty Generalization, Michael C. Labossiere's Fallacy Tutorial Pro
This article is licensed under the GNU Free Documentation License.
Last updated on Thursday October 02, 2008 at 05:39:37 PDT (GMT -0700)
View this article at Wikipedia.org - Edit this article at Wikipedia.org - Donate to the Wikimedia Foundation
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