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Shvoong Home>Social Sciences>Economics>Judgement under Uncertainty: Heuristics and Biases Summary

# Judgement under Uncertainty: Heuristics and Biases

Article Summary   by:Limonad     Original Author: Tversky and Kahneman

A heuristic is a strategy that can be applied to a variety of problems and that usually - but not always - yields a correct solution. People often use heuristics (or shortcuts) that reduce complex problem solving to more simple judgmental operations. Three of the most popular heuristics are discussed in this article: Representativeness heuristic: What is the probability that person A (Steve, a very shy and withdrawn man) belongs to group B (librarians) or C (exotic dancers)? In answering such questions, people typically evaluate the probabilities by the degree to which A is representative of B or C (Steve´s shyness seems to be more representative for librarians than for exotic dancers) and sometimes neglect base rates (there are far more exotic dancers than librarians in a certain sample). Availability heuristic: This heuristic is used to evaluate the frequency or likelihood of an event on the basis of how quickly instances or associations come to mind. When examples or associations are easily brought to mind, this fact leads to an overestimation of the frequency or likelihood of this event.
Example: People are overestimating the divorce rate if they can quickly find examples of divorced friends. People tend to be biased by information that is easier to recall. They are swayed by information that is vivid, well-publicized, or recent. People also tend to be biased by examples that they can easily retrieve. Anchoring and adjustment: People who have to make judgements under uncertainty use this heuristic by starting with a certain reference point (anchor) and then adjust it insufficiently to reach a final conclusion. Example: If you have to judge another person''s productivity, the anchor for your final (adjusted) judgement may be your own level of productivity. Depending on your own level of productivity you might therefore underestimate or overestimate the productivity of this person.
Published: August 18, 2007
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