Hasty generalization is a fallacy where someone assumes something about a large group based on a small sample size. It can occur due to bias or lazy reasoning and is often used in both formal and casual discussions. The appropriate sample size varies depending on the population in question, and hasty generalizations can lead to false and unfair assumptions about groups of people.
Also called a statistic fallacy or a small sample, hasty generalization fallacy occurs when someone assumes something to be true about a large group based on an extremely small sample size. Fallacies, as flaws in logical reasoning in an argument, are seen in both speech and writing. The fallacy of hasty generalization, however, is often — and often unintentionally — used in everything from formal discussions to casual conversations. It often occurs due to bias or lazy reasoning.
In a hasty generalization error, the writer or speaker claims that because something is true about a sample of a larger group, it is true for the group as a whole. For example, some might say, “I dated three redheads and they all had tempers. Therefore, all redheads have a bad temper.” This is a hasty generalization because three is not a large enough sample size to accurately determine the character of all redheads.
Hasty generalization is a fallacy of an informal argument. Informal arguments are about the content of the argument over structure. This means that the actual structure of the hasty generalization fallacy is logically correct. In other words, if the information presented by the generalization is reasonable and accurate, an error has not occurred.
For example, one researcher who surveyed 600 students on a campus with a total population of 1,000 found that 85 percent of students surveyed typically went to parties on Friday nights. Based on this sample size, stating that the majority of undergraduates at that university spend Friday nights partying would be a valid conclusion. If, however, the researcher interviewed only ten people and reached the same conclusion, that researcher would be guilty of the fallacy of hasty generalization. Even if the conclusion is correct, the sample collected by the researcher to support the claim is too small and, therefore, not credible.
The appropriate sample size will vary depending on the size of the total population in question. Sample sizes can be small and still be valid if the population in question is small. For example, although the survey of ten people in the university example resulted in an insufficient sample size, and thus the fallacy of hasty generalization, the survey of ten people in a club with only twenty members would generally have a sample size sufficient.
While the hasty generalization fallacy is seen in formal written and oral discussions, it is also often used in casual conversation. Stemming from prejudice or a desire to place groups into quick categories, hasty generalizations can often lead to false and unfair assumptions about large groups of people. From the man who decides no woman can drive because of the woman who cut him off to the woman who decides all foreigners are thieves because a foreigner stole her purse, hasty generalizations slip into everyday thinking, often without the person in charge realizing the fallacy at all.
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