Transcript Chap10c
Cognitive Processes PSY 334 Chapter 10 – Reasoning & Decision-Making Judgments of Probability People can be biased in their estimates when they depend upon memory. Tversky & Kahneman – differential availability of examples. Proportion of words beginning with k vs words with k in 3rd position (3 x as many). Sequences of coin tosses – HTHTTH just as likely as HHHHHH. Gambler’s Fallacy The idea that over a period of time things will even out. Fallacy -- If something has not occurred in a while, then it is more likely due to the “law of averages.” People lose more because they expect their luck to turn after a string of losses. Dice do not know or care what happened before. Chance, Luck & Superstition We tend to see more structure than may exist: Avoidance of chance as an explanation Conspiracy theories Illusory correlation – distinctive pairings are more accessible to memory. Results of studies are expressed as probabilities. The “person who” is frequently more convincing than a statistical result. Decision Making Choices made based on estimates of probability. Described as “gambles.” Which would you choose? $400 with a 100% certainty $1000 with a 50% certainty Utility Theory Prescriptive norm – people should choose the gamble with the highest expected value. Expected value = value x probability. Which would you choose? A -- $8 with a 1/3 probability B -- $3 with a 5/6 probability Most subjects choose B Subjective Utility The utility function is not linear but curved. It takes more than a doubling of a bet to double its utility ($8 not $6 is double $3). The function is steeper in the loss region than in gains: A – Gain or lose $10 with .5 probability B -- Lose nothing with certainty People pick B Framing Effects Behavior depends on where you are on the subjective utility curve. A $5 discount means more when it is a higher percentage of the price. $15 vs $10 is worth more than $125 vs $120. People prefer bets that describe saving vs losing, even when the probabilities are the same.