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Expected value is the average of the earnings you get if you play an infinite amount of
times = 3.83
Decision analysis is prescriptive –
Utility theory – normative
Descriptive – hypothesis testing (biases) seeking useless info
Heuristic – is rule of thumb
Normative – correspondence and coherence – probability (are your judgments consistent)
Correspondence – fit with the real world
Bayes and utility are normative
Expected value of decision of knowledge of which number is going to come up = 5.33
The value of this information
Value of the decision WITH perfect information – value of the decision WITHOUT
perfect information = $1.50
Miracle movers rents out trucks, but discovers it is one truck short.
Small truck = $130
Large = $200
Extra cost of second trip = $150
Probability of 2 trips = 40%
Perfect information means = probability of needing a large truck meaning you really need
a large truck is 1
Probability of needing a large truck when really you need a small truck is 0
Expected value of the decision with perfect information
The value of the decision with perfect information
Formula for a joint probability
P(“NL” and NL) = P(“NL”NL)*P(NL) = 1.0*(.4) =.4
P(“NS” and NS) = P(“NS”NS)*P(NS) = 1.0*(.6)=.6
.4 x 200 + .6 x 130 = 158
EV of the decision – EV of the decision with perfect information = value of the
information
Value of the information = 190 – 158 = 32
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 Fall '11
 Mellers

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