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the mixing of evidence. For instance, if objective evidence indicates the probability of an event occurs is 1, i.e., P(A) = 1 and P(¬A) = 0, whereas according to the memory of a subject, the probabilities are P(A') = 0.727 and P(¬A') = 0.273 respectively. When the evidence is noised by memory with probability of P(Á | A') = 0.8, p(¬Á | A') = 0.2, P(Á | ¬A') = 0.2 and P(¬Á | ¬A') = 0.8, the estimate (judgement) is smoothed to be P(Á) = 0.636 and P(¬Á)=0.364. The estimated values (0.636, 0.364) are less extreme or more conservative than the actual evidence (1 and 0). In an incentivized experimental study, it has been shown that the conservatism bias decreased in those with greater cognitive ability, though it did not disappear.
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generative mechanism that assumes a noisy conversion of objective evidence (observation) into subjective estimates (judgement). The study explains that the estimates of conditional probabilities are conservative because of noise in the retrieval of information from memory, whereas noise is defined as
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There are two bookbags, one containing 700 red and 300 blue chips, the other containing 300 red and 700 blue. Take one of the bags. Now, you sample, randomly, with replacement after each chip. In 12 samples, you get 8 reds and 4 blues. what is the probability that this is the predominantly red
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391:). Edwards suggested that people updated beliefs conservatively, in accordance with Bayes' theorem, but more slowly. They updated from .5 incorrectly according to an observed bias in several experiments.
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In finance, evidence has been found that investors under-react to corporate events, consistent with conservatism. This includes announcements of earnings, changes in
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Kadiyala, Padmaja; Rau, P. Raghavendra (2004). "Investor
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Edwards, Ward. "Conservatism in Human
Information Processing (excerpted)". In Daniel Kahneman, Paul Slovic and Amos Tversky. (1982).
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Most subjects chose an answer around .7. The correct answer according to Bayes' theorem is closer to .97 ( based on Bayes' theorem:
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which refers to the tendency to revise one's belief insufficiently when presented with new evidence. This bias describes human
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may be too technical for most readers to understand
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