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Unformatted text preview: Expected utility theory – helps with risky choices Know all the options Decision trees Framing – can reverse choices (riskaverse in a gain domain, but risk seeking in a loss domain) Frequency formulas – visualize the probabilities Signal Detection Theory – helps with repeated decisions with ambiguity Bayes – probabilities Multiattribute utility theory – evaluations Information that is available Overconfidence Bad at combining different information Don’t use information the same way twice Primacy effects Recency effects Dilution effects – the more irrelevant information you have, the further away you get from the true evalutation Prescriptive o Seek the advice of independent crowds Multiple Regression – Predictions Predicting causes of death (think there are more homicides than suicides) Bad at putting information together to make valid predictions We don’t naturally regress information when making predictions o Predict that the student will have less than a 4.0, even though that was what he got in high school (though our intuition is not to regress and say he will still have a 4.0)he will still have a 4....
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This note was uploaded on 01/14/2012 for the course PPE 253 taught by Professor Mellers during the Fall '11 term at UPenn.
 Fall '11
 Mellers

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