Mgt Science Chp 3

Front 1

Decision theory is ...

Back 1

an analytic and systematic approach to the
study of decision making.

Front 2

A good decision is based on_____

Back 2

logic

Front 3

Six Steps in Decision Making

Back 3

1. Clearly define the problem at hand.
2. List the possible alternatives.
3. Identify the possible outcomes or states of nature.
4. List the payoff (typically profit) of each combination of alternatives and outcomes.
5. Select one of the mathematical decision theory models.
6. Apply the model and make your decision.

Front 4

In decision theory, those outcomes over which the decision maker has little or no
control are called ...

Back 4

states of nature.

Front 5

In decision
theory, we call such payoffs or __________. Not every decision, of course, can be
based on money alone—any appropriate means of measuring benefit is acceptable.

Back 5

profits conditional values

Front 6

During the fourth step, the
decision maker can ...

Back 6

construct
decision or payoff tables.

Front 7

There are three decision-making environments:


Back 7

Decision making under certainty
 Decision making under uncertainty
 Decision making under risk

Front 8

TYPE 1 : DECISION MAKING UNDER CERTAINTY

Back 8

In the environment of decision making under
certainty, decision makers know with certainty the consequence of every alternative or decision
choice.

Naturally, they will choose the alternative that will maximize their well-being or will
result in the best outcome.

Front 9

TYPE 2: DECISION MAKING UNDER UNCERTAINTY

Back 9

In decision making under uncertainty, there
are several possible outcomes for each alternative, and the decision maker does not know the
probabilities of the various outcomes.

Front 10

TYPE 3: DECISION MAKING UNDER RISK

Back 10

In decision making under risk, there are several pos-
sible outcomes for each alternative, and the decision maker knows the probability of occurrence
of each outcome.

Front 11

Several criteria exist for making decisions under uncertainty these conditions:

Back 11

1. Optimistic (maximax)
2. Pessimistic (maximin)
3. Criterion of realism (Hurwicz)
4. Equally likely (Laplace)
5. Minimax regret

Front 12

Maximax is an _____
approach.

Back 12

optimistic
- the best (maximum) payoff for each alternative is considered
and the alternative with the best (maximum) of these is selected.

Front 13

Maximin is a ______
approach.

Back 13

pessimistic

Front 14

Criterion of realism uses the..

Back 14

weighted average approach.

Front 15

Equally likely criterion uses the

Back 15

average outcome.

Front 16

Minimax regret criterion is based
on

Back 16

opportunity loss.

Front 17

EMV is the

Back 17

weighted sum of
possible payoffs for each
alternative.

Front 18

EVPI places an ______ on
what to pay for information.

Back 18

upper bound

Front 19

EVPI is

Back 19

the expected value with
perfect information minus the
maximum EMV.

EVPI = EVwPI - Best EMV

Front 20

EOL is the

Back 20

cost of not picking
the best solution.

Front 21

EOL will always result in the

Back 21

same decision as the maximum
EMV.

Front 22

Sensitivity analysis investigates

Back 22

how our decision might change
with different input data.

Front 23

Any problem that can be presented in a decision table can also be

Back 23

graphically illustrated in a
decision tree.

Front 24

Five Steps of Decision Tree Analysis

Back 24

1. Define the problem.
2. Structure or draw the decision tree.
3. Assign probabilities to the states of nature.
4. Estimate payoffs for each possible combination of alternatives and states of nature.
5. Solve the problem by computing expected monetary values (EMVs) for each state of
nature node. This is done by working backward, that is, starting at the right of the tree and
working back to decision nodes on the left. Also, at each decision node, the alternative
with the best EMV is selected.

Front 25

When_____________ need to be made, decision trees are much more powerful tools than decision tables.

Back 25

sequential decisions

Front 26

One way of
measuring the value of market information is to compute the __________________ which is the increase in expected value resulting from the sample information.

Back 26

expected value of sample information
(EVSI)