Chapter 3

Question 1

An analytic and systematic approach to the study of decision making

Answer 1

Decision Theory

Question 2

A good decision is based on what?

Answer 2

1. Logic
2. Considers all Available Data
3. Considers all Possible Alternatives
4. Applies the Quantitative Approach

Question 3

A good decision occasionally results in an ______, _______ outcome, but is still a good decision if it is made properly.

Answer 3

Unexpected; Unfavorable

Question 4

A bad decision is NOT based on what?

Answer 4

1. Logic
2. Does not consider all available data
3. Does not consider all possible alternatives
4. Does not apply the quantitative approach

Question 5

What are the six steps in decision making?

Answer 5

1. Clearly define the problem
2. List the possible alternatives
3. Identify the possible outcomes
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 decisions

Question 6

A course of action or a strategy that the decision maker can choose

Answer 6

Alternative

Question 7

What is a common mistake in choosing alternatives in decision making?

Answer 7

leave out possible outcomes

Question 8

What is a common mistake in identifying outcomes or states of nature? Why does it occur?

Answer 8

Forget about some of the outcomes: an optimistic decision maker tends to leave out bad outcomes where pessimistic decision makers may discount a favorable outcome

Question 9

Outcomes over which the decision maker has little or no control

Answer 9

States of Nature

Question 10

A consequence, normally expressed in a monetary value, that occurs as a result of a particular alternative and state of nature

Answer 10

Conditional Value or Payoff

Question 11

A table that lists the alternatives, states of nature, and payoffs in a decision-making situation

Answer 11

Decision or Payoff Table

Question 12

Selecting the model depends on what?

Answer 12

the environment in which you’re operating and the amount of risk and uncertainty involved

Question 13

What are the three decision-making environments?

Answer 13

1. Decision making under certainty
2. Decision making under uncertainty
3. Decision making under risk

Question 14

The decision making environment in which decision makers know with certainty the consequence of every alternative or decision choice

Answer 14

Decision Making Under Certainty

Question 15

The decision making environment in which decision makers do not know the probabilities of the various outcomes

Answer 15

Decision Making Under Uncertainty

Question 16

The decision making environment in which there are several possible outcomes for each alternative, and the decision maker knows the probability of occurrence of each outcome

Answer 16

Decision Making Under Risk

Question 17

When in the decision making under risk environment, what two equivalent criteria do decision makers typically employ?

Answer 17

1. Maximization of expected monetary value

2. Minimization of expected opportunity loss

Question 18

What are the criteria for making decisions under conditions of uncertainty?

Answer 18

1. Optimistic
2. Pessimistic
3. Criterion of realism
4. Equally Likely
5. Minimax regret

Question 19

The criterion for making decision under uncertainty in which the best (maximum) payoff for each alternative is considered and the alternative with the best (maximum) of these is selected.

Answer 19

Optimistic Criterion or Maximax Criterion

Question 20

When looking at which lower payoffs (EG costs) are better, you would look at the best _____ payoff for each alternative and choose the alternative with the best ____ of these.

Answer 20

Minimum

Question 21

A decision making criterion that maximizes the minimum payoff. It selects the alternative with the best of the worst possible payoffs.

Answer 21

Pessimistic Criterion or Maximin Criterion

Question 22

A decision making criterion that uses a weighted average of the best and worst possible payoffs for each alternative.

Answer 22

Criterion of Realism or Weighted Average Criterion

Question 23

A number from 0 to 1. When the coefficient is close to 1, the decision criterion is optimistic. When the coefficient is close to 0, the decision criterion is pessimistic.

Answer 23

Coefficient of Realism (a)

Question 24

In coefficient of realism, when the coefficient is close to 1, the decision criterion is ____.

Answer 24

Optimistic

Question 25

In coefficient of realism, when the coefficient is close to 0, the decision criterion is ____.

Answer 25

Pessimistic

Question 26

What is the advantage of the coefficient of realism approach?

Answer 26

Allows the decision maker to build in personal feelings about relative optimism and pessimism

Question 27

What is the weighted average formula?

Answer 27

Weighted Average = a(best in row) + (1-a)(worst in row)

Question 28

In using the criterion of realism for minimization problems, the best payoff for an alternative would be the ____ in the row and the worst would be the ____ in the row.

Answer 28

Lowest Payoff: Highest Payoff

Question 29

A decision criterion that places an equal weight on all states of nature?

Answer 29

Equally Likely (LaPlace)

Question 30

A decision criterion that involves finding the average payoff for each alternative, and selecting the alternative with the best or highest average.

Answer 30

Equally Likely (LaPlace)

Question 31

The difference between the optimal profit or payoff for a given state of nature and the actual profit or payoff received fro a particular decision for that state of nature

Answer 31

Opportunity Loss or Regret

Question 32

How is opportunity loss calculated?

Answer 32

By subtracting each payoff in the column fro the best payoff in the same column

Question 33

The average value of a decision if it can be repeated may times. This is determined by multiplying the monetary values by their respective probabilities.

Answer 33

Expected Monetary Value (EMV)

Question 34

The long run average value of an EMV decision.

Answer 34

Expected Value or Mean Value

Question 35

E(X) =

Answer 35

Expected Value of X

Question 36

What is the formula for EMV (alternative)?

Answer 36

EMV (alternative) = EXiP(Xi) Where Xi = payoff for the alternative in state of nature i P(Xi) = probability of achieving payoff Xi (i.e. probability of state of nature i) E = summation symbol

Question 37

The expected or average return, in the long run, if we have perfect information before a decision has to be made.

Answer 37

Expected Value With Perfect Information (EVwPI)

Question 38

The average or expected value of information if it were completely accurate. The increase in EMV that results from having perfect information.

Answer 38

Expected value of Perfect Information (EVPI)

Question 39

What is the expected value with perfect information formula?

Answer 39

EVwPI = E(Best payoff in state of nature i)(probability of first state of nature)

Question 40

What is the expected value of perfect information formula?

Answer 40

EVPI = EVwPI – Best EMV

Question 41

The cost of not picking the best solution

Answer 41

Expected Opportunity Loss (EOL)

Question 42

Investigates how a decision might change given different input data

Answer 42

Sensitivity Analysis

Question 43

A graphical representation of a decision making situation

Answer 43

Decision Tree

Question 44

In a decision tree, this is a point where the best of the available alternatives is chosen.

Answer 44

Decision Node (Point)

Question 45

The branches of a decision tree represent the ____.

Answer 45

Alternatives

Question 46

In a decision tree, a point where the EMV is computed.

Answer 46

State of Nature Node (Point)

Question 47

What are the five steps of decision tree analysis?

Answer 47

* Step 1: Define the Problem * Step 2: Structure or draw the decision tree * Step 3: Assign probabilities to the states of nature * Step 4: Estimate payoffs for each possible combination of alternatives and states of nature * Step 5: Solve the problem by computing EMV’s 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.