UCSB ESM 204 - Heuristics and Biases (9 pages)

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Heuristics and Biases



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Heuristics and Biases

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Pages:
9
School:
University of California, Santa Barbara
Course:
Esm 204 - The Economics of Envirnomental Management
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Judgment under Uncertainty Heuristics and Biases Author s Amos Tversky and Daniel Kahneman Source Science New Series Vol 185 No 4157 Sep 27 1974 pp 1124 1131 Published by American Association for the Advancement of Science Stable URL http www jstor org stable 1738360 Accessed 04 01 2010 13 17 Your use of the JSTOR archive indicates your acceptance of JSTOR s Terms and Conditions of Use available at http www jstor org page info about policies terms jsp JSTOR s Terms and Conditions of Use provides in part that unless you have obtained prior permission you may not download an entire issue of a journal or multiple copies of articles and you may use content in the JSTOR archive only for your personal non commercial use Please contact the publisher regarding any further use of this work Publisher contact information may be obtained at http www jstor org action showPublisher publisherCode aaas Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission JSTOR is a not for profit service that helps scholars researchers and students discover use and build upon a wide range of content in a trusted digital archive We use information technology and tools to increase productivity and facilitate new forms of scholarship For more information about JSTOR please contact support jstor org American Association for the Advancement of Science is collaborating with JSTOR to digitize preserve and extend access to Science http www jstor org occupation from a list of possibilities for example farmer salesman airline pilot librarian or physician How do people order these occupations from most to least likely In the representativeness heuristic the probability that Steve is a librarian for example is assessed by the degree to which he is representative of or similar to the stereotype of a librarian Indeed reBiases in judgments reveal some heuristics of search with problems of this type has shown that people order the occupathinking under uncertainty tions by probability and by similarity in exactly the same way 1 This apto the judgment of probability proach Amos Tversky and Daniel Kahneman leads to serious errors because similarity or representativeness is not influenced by several factors that should affect judgments of probability mated when visibility is good because Many decisions are based on beliefs Insensitivity to prior probability of concerning the likelihood of uncertain the objects are seen sharply Thus the outcomes One of the factors that have events such as the outcome of an elec reliance on clarity as an indication of no effect on representativeness but tion the guilt of a defendant or the distance leads to common biases Such should have a major effect on probabilfuture value of the dollar These beliefs biases are also found in the intuitive ity is the prior probability or base rate are usually expressed in statements such judgment of probability This article frequency of the outcomes In the case as I think that chances are describes three heuristics that are em of Steve for example the fact that it is unlikely that and ployed to assess probabilities and to there are many more farmers than liso forth Occasionally beliefs concernpredict values Biases to which these brarians in the population should enter ing uncertain events are expressed in heuristics lead are enumerated and the into any reasonable estimate of the numerical form as odds or subjective applied and theoretical implications of probability that Steve is a librarian rather than a farmer Considerations of probabilities What determines such be these observations are discussed liefs How do people assess the probbase rate frequency however do not affect the similarity of Steve to the ability of an uncertain event or the value of an uncertain quantity This Representativeness stereotypes of librarians and farmers article shows that people rely on a If people evaluate probability by repof the limited number of heuristic principles probabilistic questions Many resentativeness therefore prior probawhich reduce the complex tasks of as with which people are concerned belong bilities will be neglected This hypothesis sessing probabilities and predicting val to one of the following types What is was tested in an experiment where prior ues to simpler judgmental operations the probability that object A belongs to probabilities were manipulated 1 In general these heuristics are quite class B What is the probability that Subjects were shown brief personality useful but sometimes they lead to severe event A originates from process B descriptions of several individuals alWhat is the probability that process B legedly sampled at random from a and systematic errors The subjective assessment of proba will generate event A In answering group of 100 professionals engineers bility resembles the subjective assess such questions people typically rely on and lawyers The subjects were asked ment of physical quantities such as the representativeness heuristic in to assess for each description the probdistance or size These judgments are which probabilities are evaluated by the ability that it belonged to an engineer all based on data of limited validity degree to which A is representative of rather than to a lawyer In one experiwhich are processed according to heu B that is by the degree to which A mental condition subjects were told ristic rules For example the apparent resembles B For example when A is that the group from which the descripdistance of an object is determined in highly representative of B the proba tions had been drawn consisted of 70 part by its clarity The more sharply the bility that A originates from B is judged engineers and 30 lawyers In another object is seen the closer it appears to to be high On the other hand if A is condition subjects were told that the be This rule has some validity because not similar to B the probability that A group consisted of 30 engineers and 70 in any given scene the more distant originates from B is judged to be low lawyers The odds that any particular For an illustration of judgment by description belongs to an engineer objects are seen less sharply than nearer objects However the reliance on this representativeness consider an indi rather than to a lawyer should be rule leads to systematic errors in the vidual who has been described by a higher in the first condition where there estimation of distance Specifically dis


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