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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]
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]
Base rate fallacy – making a probability judgment based on conditional probabilities, ... fallacy of the mean, ... (fallacy of insufficient statistics, ...
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] Compassion fade, the tendency to behave more compassionately towards a small number of identifiable victims than to a large number of ...
A base rate is a phenomenon's basic rate of incidence. 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 ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.
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 different, in that, rather than incorrectly using probability, the actor disregards it.
Confusion of the inverse, also called the conditional probability fallacy or the inverse fallacy, is a logical fallacy whereupon a conditional probability is equated with its inverse; that is, given two events A and B, the probability of A happening given that B has happened is assumed to be about the same as the probability of B given A, when there is actually no evidence for this assumption.