D ECISION M AKING

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Presentation transcript:

D ECISION M AKING

I MPORTANT ASPECTS OF DECISION MAKING

B ASIC CONCEPTS OF PROBABILITY Probability 0 (no probability) – 1 (definitely will happen) Most people overestimate

B ASIC CONCEPTS OF PROBABILITY Probability

P HASES OF DECISION MAKING Rationality

Heuristics Ex. “take the best” Biases (Cognitive Illusions) C OGNITIVE ILLUSIONS

Availability C OGNITIVE ILLUSIONS

Representativeness Conjunction fallacy Linda is a bank teller. Linda is a bank teller and is active in the feminist movement. C OGNITIVE ILLUSIONS

Representativeness Law of small numbers Gambler’s Fallacy “hot hand” “man who” arguments C OGNITIVE ILLUSIONS

Framing Effect C OGNITIVE ILLUSIONS

Anchoring C OGNITIVE ILLUSIONS 8x7x6x5x4x3x2x1 1x2x3x4x5x6x7x8

Sunk Cost Effects C OGNITIVE ILLUSIONS

Illusory Correlation Under stress Not under stress Hair-twister 2010 Not a hair- twister 8040 C OGNITIVE ILLUSIONS

Hindsight Bias C OGNITIVE ILLUSIONS

Confirmation Bias C OGNITIVE ILLUSIONS

Overconfidence Questionnaire examples What magazine had the largest circulation in 1978? A) TimeB) Reader’s Digest Who began the profession of nursing? A) NightingaleB) Barton C OGNITIVE ILLUSIONS

E XAMPLE OF A CALIBRATION CURVE. Overconfidence C OGNITIVE ILLUSIONS

T YPES OF D ECISION MODELS Normative models Prescriptive models Descriptive models

Expected Utility Theory Lottery A #1 = 10% of winning $10 # 2-4 = 10% of winning $5 # 5-10 = no money (.1 X $10) + (.3 X $5) + (.6 X $0) + $1.60 U TILITY MODELS

Expected Utility Theory Lottery A #1 = 10% of winning $10 # 2-4 = 10% of winning $5 # 5-10 = no money Lottery B #1 = 10% of winning $100 # 2-4 = 10% of winning $1 # 5-10 = no money (.1 X $10) + (.3 X $5) + (.6 X $0) + $1.60 (.1 X $100) + (.3 X $1) + (.6 X $0) + $10.30 U TILITY MODELS

D ESCRIPTIVE M ODELS Recognition-Primed Decision Making

W HAT ARE SOME WAYS TO AVOID POOR DECISIONS ? Be wary of over-confidence Intuition vs. equations/computers