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Insensitivity to sample size is a cognitive bias that occurs when people judge the probability of obtaining a sample statistic without respect to the sample size.For example, in one study, subjects assigned the same probability to the likelihood of obtaining a mean height of above six feet [183 cm] in samples of 10, 100, and 1,000 men.
Extension neglect [a] is a type of cognitive bias which occurs when the sample size is ignored when its determination is relevant. [1] For instance, when reading an article about a scientific study, extension neglect occurs when the reader ignores the number of people involved in the study (sample size) but still makes inferences about a population based on the sample.
Scope neglect or scope insensitivity is a cognitive bias that occurs when the valuation of a problem is not valued with a multiplicative relationship to its size. Scope neglect is a specific form of extension neglect .
Insensitivity to sample size, the tendency to under-expect variation in small samples. Less-is-better effect, the tendency to prefer a smaller set to a larger set judged separately, but not jointly. Neglect of probability, the tendency to completely disregard probability when making a decision under uncertainty. [53]
Representativeness heuristic is also employed when subjects estimate the probability of a specific parameter of a sample. If the parameter highly represents the population, the parameter is often given a high probability. This estimation process usually ignores the impact of the sample size.
[14] [15] It would have been incorrect, and an example of prosecutor's fallacy, to rely solely on the "1 in 400" figure to deduce that a given person matching the sample would be likely to be the culprit. Frequency tree of 100 000 battered American women showing the base rate fallacy made by the defense in the O. J. Simpson murder trial
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Related biases are the illusion of control which the clustering illusion could contribute to, and insensitivity to sample size in which people don't expect greater variation in smaller samples. A different cognitive bias involving misunderstanding of chance streams is the gambler's fallacy.