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Unformatted text preview: Expected utility theory – helps with risky choices- Know all the options- Decision trees- Framing – can reverse choices (risk-averse 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 Multi-attribute 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