The Base Rate Fallacy states that people routinely ignore
base rate frequencies and that it is an error to do so
and base your conclusions instead on the similarity between
an individuals personality and the prototypes of the
categories under consideration.
You will find in most experiments that base rates will be
equated with prior probabilities. Subjects' judgements and
their deviations between the Bayesian posterior probability
are used to measure the extent to which the base rate
fallacy has been committed.
For example if there was a disease which takes two forms,
both of which are fatal and require two different medicines,
only one of which can be taken at any time. Form A occurs
10% of the time, form B 90% of the time. There is a test to
see which type of the disease a patient has, this test is
80% reliable and it says that the patient has form A of the
disease. The patient is likely to take the treatment for
form A of the disease even though there is only a 10% chance
that he has form A, and a 20% chance that the test was wrong
and that he has form B. The patient is ignoring the base
rate.
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