In one of these experiments, experienced horserace handicappers were shown a long list of variables that included data related to the recent performances of the horses, the weight of the jockeys, the time since the last race, the weather conditions, etc. Each handicapper was asked to order these variables according to its perceived importance in the making of his prediction.
Next the handicappers were shown real data that had been renamed to ensure that they could not remember the events. Each of them was then given the five variables he had listed as the most useful. At that point they were asked to make a prediction as well as an estimate of the degree of accuracy of his prediction (from 0% to 100%). The same exercise was repeated after the handicappers were given 10, 20 and 40 variables. Key findings from these experiments:
1) Once an experienced analyst has the minimum information necessary to make an informed judgment, obtaining additional information generally does not improve the accuracy of his or her estimates. Additional information does, however, lead the analyst to become more confident in the judgment, to the point of overconfidence.
2) Experienced analysts have an imperfect understanding of what information they actually use in making judgments. They are unaware of the extent to which their judgments are determined by a few dominant factors, rather than by the systematic integration of all available information. Analysts actually use much less of the available information than they think they do.
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