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Faulty generalization
From Wikipedia, the free encyclopedia
A faulty generalization, also known as an inductive fallacy, is any of several errors of inductive inference:
The proportion Q of the sample has attribute A.
therefore
The proportion Q of the population has attribute A.
Such a generalization proceeds from a premise about a sample to a conclusion about the population.
"All generalizations are dangerous, even this one." -Alexandre Dumas, fils
- Hasty generalization is the fallacy of examining just one or very few examples or studying a single case, and generalizing that to be representative of the whole class of objects or phenomena.
- The overwhelming exception is related to the hasty generalization, but working from the other end. It is a generalization which is accurate, but tags on a qualification which eliminates enough cases (as exceptions); that what remains is much less impressive than what the original statement might have led one to assume.
- Biased sample
- Misleading vividness is a kind of hasty generalization that appeals to the senses.
- Statistical special pleading occurs when the interpretation of the relevant statistic is "massaged" by looking for ways to reclassify or requantify data from one portion of results, but not applying the same scrutiny to other categories.