| Representativeness Heuristic |
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People trying to estimate the probability of an occurrence tend to forget the underlying base rates associated with it. This neglect usually leads to an overestimation of the occurrence. The representative heuristic was first identified by Amos Tversky and Daniel Kahneman . Two examples are commonly used when explaining this heuristic. Tom W. In a study done in 1973, Kahneman and Tversky gave their subjects the following information: Tom W. is of high intelligence, although lacking in true creativity. He has a need for order and clarity, and for neat and tidy systems in which every detail finds its appropriate place. His writing is rather dull and mechanical, occasionally enlivened by somewhat corny puns and by flashes of imagination of the sci-fi type. He has a strong drive for competence. He seems to have feel little sympathy for other people and does not enjoy interacting with others. Self-centered, he nonetheless has a deep moral sense. They then asked the subjects to consider how similar Tom W. was to a student in one of nine types of college graduate majors (business administration, computer science, engineering, humanities/education, law, library science, medicine, physical/life sciences, or social science/social work). Most subjects associated Tom W. with an engineering student, and thought he was least like a student of social science/social work. Another group was asked instead to estimate the probability that Tom W. was a grad student in each of the nine majors. The probabilities were in line with the judgments from the previous group. However, earlier, a third group of subjects had been asked to estimate the proportion of first-year grad students there were in each of the nine majors. Using those base rates as a means for comparison, the probabilities the second group had made about Tom W. were inconsistent with themselves. Their probabilities were based mainly on how much they thought Tom W. was representative of each of the majors, and complete neglected the base rate probability of being that kind of student in the first place. Had the subjects thought about those base rates, their estimated probability that Tom W. was an engineer would have been much lower (there were few engineering grad students at the time.) The Taxicab problem In another study done by Tversky and Kahneman, subjects were given the following problem. A cab was involved in a hit and run accident at night. Two cab companies, the Green and the Blue, operate in the city. You are given the following data: (a) 85% of the cabs in the city are Green and 15% are Blue. (b) A witness identified the cab as Blue. The court tested the reliability of the witness under the same circumstances that existed on the night of the accident and concluded that the witness correctly identified each one of the two colors 80% of the time and failed 20% of the time. What is the probability that the cab involved in the accident was Blue rather than Green? Most subjects gave probabilities over 50%, some over 80%. However, using Bayes' Theorem , the correct answer found through adding and multiplying the probabilities is actually only 41%. We all use the representative heursitic to make decisions every day. From choosing brands in a supermarket, to hiring a new employee, we use what we know to make selections about things we don't. Using such heuristics usually work in your favor, making seemingly difficult choices much quicker and easier. However, using stereotypes can also prolong predjudices and cause you to miss valuable opportunities. Thinking about what facts you are basing a decision on and remembering to account for base rates can help to reduce judgement errors based on stereotypes. Representativeness is cited in the similar effect of the Gambler's Fallacy , the Regression Fallacy and the Conjunction Fallacy . Another psychological heuristic found by Tversky and Kahneman is the Availability Heuristic . REFERENCES
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