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Lecture 8

BU275 Lecture Notes - Lecture 8: Perfect InformationPremium

2 pages46 viewsWinter 2018

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David Wheatley

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BU-25 Lecture
Intro to Decision Analysis
Payoff Tables and Decision Making under Uncertainty
You have the opportunity to co-op for a fried’s start-up, working part-time or full-time and even invest
in the company.
States of Nature
Company Takes Off
Company does bad
Part Time
Full Time
Full Time and
The choices you have are called alternatives. The outcomes are determined by states of nature
and each combo has a payoff
If we can assign probabilities to the states of nature (events), then we can use expected value
o Unfortunately, we may not have any idea what probabilities to assign, even if you have
historical (empirical) data, it may not be applicable in your case
Decision Making without Probabilities
Decision Criteria:
o Maximax (optimistic)
Find the best payoff by alternative
Pick the highest best case
o Maximin (pessimistic)
Find the worst payoff by alternative, and pick the highest (worst case)
Safest choice
o Minimax Regret
First, we need a regret table, built by finding the best payoff by state of nature,
the calculating regret in $ for the other payoffs
What you could have had minus what you have = regret
By alternative, find the largest regret, then pick the option whose worst-case
regret is the smallest
Substitutes for Probabilities
o Equal likelihood criterion
Here use 50% for each and calculate the expected value
o Hurwicz Criterion
Use α, a oeffiiet of optiis α= is optiisti, α= is pessiisti
Assign α to best case, and 1-α to the worst case
Ex. α=0.4, Best case*(0.4)+Worst case*(0.6)=Expected Value
Decision Making with Probabilities:
find more resources at
find more resources at
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