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The base rate fallacy, also called base rate neglect [2] or base rate bias, is a type of fallacy in which people tend to ignore the base rate (e.g., general prevalence) in favor of the individuating information (i.e., information pertaining only to a specific case). [3]
The following are forms of extension neglect: Base rate fallacy or base rate neglect, the tendency to ignore general information and focus on information only pertaining to the specific case, even when the general information is more important. [47]
The continuum between the extremes is ignored. The term probability neglect was coined by Cass Sunstein. [1] There are many related ways in which people violate the normative rules of decision making with regard to probability including the hindsight bias, the neglect of prior base rates effect, and the gambler's fallacy. However, this bias is ...
For example, if the control group, using no treatment at all, had their own base rate of 1/20 recoveries within 1 day and a treatment had a 1/100 base rate of recovery within 1 day, we see that the treatment actively decreases the recovery. The base rate is an important concept in statistical inference, particularly in Bayesian statistics. [2]
The base rate fallacy describes how people do not take the base rate of an event into account when solving probability problems. [12] This was explicitly tested by Dawes, Mirels, Gold and Donahue (1993) who had people judge both the base rate of people who had a particular personality trait and the probability that a person who had a given ...
In cognitive psychology and decision science, conservatism or conservatism bias is a bias which refers to the tendency to revise one's belief insufficiently when presented with new evidence. This bias describes human belief revision in which people over-weigh the prior distribution ( base rate ) and under-weigh new sample evidence when compared ...
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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.