QMT437
Pn. Paezah
TOPIC 2:
DECISION THEORY
LEARNING OUTCOMES
Students will be able to
•
list the steps of decision-making process
•
describe the decision-making environments
•
apply various modeling techniques to analyze decisions under risk.
Modeling Techniques
Quantitative techniques used in decision analysis include:
1.
Maximax, Maximin, Laplace, Criterion of Realism,
Minimax Regret
2.
Expected Monetary Value (EMV)
3.
Expected Opportunity Loss (EOL)
4.
Expected Value of Perfect Information (EVPI)
5. Decision Trees
6.
Expected Value of Sample Information
I.
INTRODUCTION
Decision theory
is an analytic and systematic approach to the study of decision making.
A good decision is based on logic, considers all available data and possible alternatives, and
applies an appropriate quantitative technique.
The 6 steps in decision making:
1.
Clearly define the problem
2.
List all possible decision alternatives/plans of actions
.
•
A decision alternative is a course of action or a strategy that may be chosen by a
decision maker
3.
Identify the possible states of nature (or outcomes)
and, if available, their associated
probabilities.
•
A state of nature is an outcome or occurrence over which the decision maker has
little or no control
.
4.
Determine the payoffs
or returns accruing to each decision under each state of nature.
5.
Select one decision model and evaluate each alternative using the model.
6.
Make a decision, i.e. select the best alternative.
The decision analysis can be summarized using a
payoff table
:
Decision
alternatives
State of Nature
S
1
S
2
...
S
m
d
1
r
11
r
12
...
r
1m
d
2
r
21
r
21
...
r
21
...
...
...
...
...
d
n
r
n1
r
n1
...
r
nm
Probabilities
P(S
1
)
P(S
2
)
...
P(S
m
)
r
ij
= the payoff if alternative d
i
is
chosen and state of nature
S
j
occurs
1

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