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Lecture 8

# BU275 Lecture Notes - Lecture 8: Perfect InformationPremium

2 pages46 viewsWinter 2018

Department
Course Code
BU275
Professor
David Wheatley
Lecture
8

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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
Alternatives
Part Time
40,000
20,000
Full Time
70,000
10,000
Full Time and
Investment
110,000
-10,000
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
calculations.
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 oneclass.com
find more resources at oneclass.com