Deck 19: Decision Analysis

Question 1

A tabular presentation of the expected gain from the various options open to a decision maker is called

A) a payoff table.
B) a decision tree.
C) the expected values table.
D) the branch probabilities table.

Answer 1

a payoff table.

Question 2

A decision criterion which weights the payoff for each decision by its probability of occurrence is the

A) payoff criterion.
B) expected value criterion.
C) decision strategy.
D) expected value of perfect information criterion.

Answer 2

expected value criterion.

Question 3

New information obtained through research or experimentation that enables an updating or revision of the state-of-nature probabilities is _____ information.

A) population
B) prior
C) sample
D) conditional

Answer 3

sample

Question 4

The outcomes of uncontrollable future events that can affect the outcome of a decision are known as

A) alternatives.
B) decision events.
C) payoffs.
D) states of nature.

Question 5

A graphic presentation of the expected gain from the various options open to the decision maker is called

A) a payoff table.
B) a decision tree.
C) the expected values table.
D) the branch-to-node tree.

Question 6

The result obtained when a decision alternative is chosen and a chance event occurs is known as

A) decision event.
B) consequence.
C) state of nature.
D) conditional probability.

Question 7

Nodes indicating points where a decision is made are known as _____ nodes.

A) decision
B) chance
C) unconditional
D) conditional

Question 8

The expected value of information that would tell the decision maker exactly which state of nature is going to occur is the _____ information.

A) expected value of sample
B) expected value of perfect
C) revised state-of-nature
D) updated research

Question 9

An intersection or junction point of a decision tree is called a(n)

A) junction.
B) intersection.
C) branch.
D) node.

Question 10

The probability of both sample information and a particular state of nature occurring simultaneously is _____ probability.

A) posterior
B) joint
C) prior
D) conditional

Question 11

A tabular representation of the payoffs for a decision problem is a

A) decision tree.
B) payoff table.
C) sequential node.
D) problem table.

Question 12

In computing an expected value (EV), the weights are

A) decision alternative probabilities.
B) the payoffs.
C) expected outcomes.
D) the state-of-nature probabilities.

Question 13

A line or arc connecting the nodes of a decision tree is called a(n)

A) junction.
B) intersection.
C) branch.
D) node.

Question 14

The expected opportunity loss of the best decision alternative is the

A) expected monetary value.
B) payoff.
C) expected value of perfect information.
D) None of these alternatives is correct.

Question 15

The probability of a state of nature that results after using Bayes' theorem to adjust the prior probability based on sample information is called _____ probability.

A) joint
B) conditional
C) posterior
D) decision

Question 16

Nodes indicating points where an uncertain event will occur are known as _____ nodes.

A) decision
B) chance
C) unconditional
D) conditional

Question 17

For a decision alternative, the weighted average of the payoffs is known as

A) the expected value of perfect information.
B) the expected value.
C) weighted probability.
D) perfect information.

Question 18

The outcomes of future events that cannot be controlled by the decision maker are called

A) decision outcomes.
B) states of nature.
C) prior events.
D) posterior events.

Question 19

An uncertain future event affecting the consequence, or payoff, associated with a decision is known as

A) decision alternative.
B) payoff node.
C) chance event.
D) uncertain probability.

Question 20

The probability of one event given the known outcome of a (possibly) related event is known as _____ probability.

A) posterior
B) joint
C) prior
D) conditional

Question 21

Prior probabilities are the probabilities of the states of nature _____ information.

A) after obtaining sample
B) prior to obtaining perfect
C) prior to obtaining sample
D) after obtaining perfect

Question 22

Below you are given an income payoff table involving three decision alternatives and two states of nature. ​ The probability of the occurrence of s₁ = .3. The expected value of the best alternative is

A) 12.9.
B) 13.2.
C) 10.2.
D) 28.0.

Question 23

Below you are given a profit payoff table involving three decision alternatives and three states of nature. ​ The probability of occurrence of s₁ is .1 and the probability of occurrence of s₂ is .3.
The expected value of the best alternative is

A) 4.5.
B) 69.5.
C) 7.5.
D) 9.0.

Question 24

The difference between the expected value of an optimal strategy based on sample information and the "best" expected value without any sample information is called the _____ information.

A) optimal
B) expected value of sample
C) expected value of perfect
D) new

Question 25

The process of revising prior probabilities to create posterior probabilities based on sample information requires using

A) decision strategies.
B) a subjective approach.
C) Bayes' theorem.
D) the posterior revision.

Question 26

Below you are given a profit payoff table involving two decision alternatives and three states of nature. ​ The probability that s₁ will occur is .2; the probability that s₂ will occur is .6.
The expected value of perfect information equals

A) 12.
B) 9.
C) 37.
D) 29.

Question 27

Below you are given a profit payoff table involving three decision alternatives and two states of nature. ​ The probability of occurrence of s₁ = .2. The expected value of the best alternative is

A) 8.8.
B) 7.4.
C) 9.6.
D) 11.6.

Question 28

Below you are given an income payoff table involving three decision alternatives and two states of nature. ​ The probability of the occurrence of s₁ = .3. The expected value of perfect information is

A) 1.5.
B) 1.2.
C) 4.2.
D) 4.8.

Question 29

Below you are given a profit payoff table involving three decision alternatives and three states of nature. ​ The probability of occurrence of s₁ is .1 and the probability of occurrence of s₂ is .3.
The recommended decision alternative based on the expected value is

A) A.
B) B.
C) C.
D) Both A and B are optimal.

Question 30

Below you are given a profit payoff table involving three decision alternatives and two states of nature. ​ The probability of occurrence of s₁ = .2. The expected value of alternative A is

A) 7.6.
B) 11.6.
C) 8.8.
D) 13.6.

Question 31

Below you are given a profit payoff table involving three decision alternatives and two states of nature. ​ The probability of occurrence of s₁ = .2. The recommended decision alternative based on the expected value is

A) A.
B) B.
C) C.
D) Both A and C are recommended.

Question 32

Below you are given an income payoff table involving three decision alternatives and two states of nature. ​ The probability of the occurrence of s₁ = .3. The recommended decision alternative based on the expected value is

A) A.
B) B.
C) C.
D) Both A and B are optimal.

Question 33

Below you are given a profit payoff table involving three decision alternatives and two states of nature. ​ The probability of occurrence of s₁ = .2. The expected value of perfect information is

A) 6.2.
B) 2.0.
C) 13.6.
D) 4.8.

Question 34

Below you are given a revenue payoff table involving three decision alternatives and two states of nature. ​ The probability of the occurrence of state of nature s₁ is .4.
The expected value of the best alternative equals

A) 13,000.
B) 14,000.
C) 15,000.
D) 16,000.

Question 35

Below you are given an income payoff table involving three decision alternatives and two states of nature. ​ The probability of the occurrence of s₁ = .3. The expected value of alternative A is

A) 10.9.
B) 13.2.
C) 12.9.
D) 8.1.

Question 36

Below you are given a revenue payoff table involving three decision alternatives and two states of nature. ​ The probability of the occurrence of state of nature s₁ is .4.
The recommended decision based on the expected value criterion is

A) A.
B) B.
C) C.
D) Both B and C are recommended.

Question 37

Below you are given a profit payoff table involving three decision alternatives and three states of nature. ​ The probability of occurrence of s₁ is .1 and the probability of occurrence of s₂ is .3.
The expected value of alternative C is

A) 30.0.
B) 6.5.
C) 3.
D) 5.5.

Question 38

Below you are given a profit payoff table involving two decision alternatives and three states of nature. ​ The probability that s₁ will occur is .2; the probability that s₂ will occur is .6.
The recommended decision based on the expected value criterion is

A) A.
B) B.
C) Both A and B are optimal.
D) A third alternative is required for an optimal solution.

Question 39

Below you are given a profit payoff table involving two decision alternatives and three states of nature. ​ The probability that s₁ will occur is .2; the probability that s₂ will occur is .6.
The expected value of the best alternative equals

A) 29.
B) 105.
C) 12.0.
D) 41.0.

Question 40

Below you are given a revenue payoff table involving three decision alternatives and two states of nature. ​ The probability of the occurrence of state of nature s₁ is .4.
The expected value of perfect information equals

A) 13,000.
B) 14,000.
C) 15,000.
D) 16,000.

Question 41

The approach used to determine the optimal decision strategy involves​

A) ​a forward (left to right) pass through the decision tree.
B) ​a backward (right to left) pass through the decision tree.
C) ​choosing the outcome of a chance event with the greatest probability.
D) ​choosing the outcome of a chance event with the greatest payoff.

Question 42

The _____ leaving the decision node correspond to the decision alternatives.

A) nodes
B) decision trees
C) branches
D) payoff tables

Question 43

Experts in problem solving agree that the first step in solving a complex decision problem is to​

A) ​decompose it into a series of smaller subproblems.
B) ​acquire the best software available for solving it.
C) ​assign several teams to work on it simultaneously.
D) ​recognize your staff's limitations and hire expert consultants.

Question 44

A sequence of decisions and chance outcomes that provide the optimal solution to a decision problem is called​

A) ​a payoff table.
B) ​the expected value approach.
C) ​a decision strategy.
D) an optimal plan.

Question 45

Application of Bayes' theorem enables us to compute​ the

A) prior probability of each state of nature.
B) posterior probability of each sample outcome.
C) conditional probability of the sample outcomes given each state of nature.
D) conditional probability of the states of nature given each sample outcome.

Question 46

When working backward through a decision tree, the analyst should​

A) ​compute the expected value at each chance node.
B) ​select the best chance branch at each chance node.
C) ​select the best chance branch at each decision node.
D) ​compute the expected value at each decision node.

Question 47

Below you are given a profit payoff table involving three decision alternatives and three states of nature. ​ The probability of occurrence of s₁ is .1 and the probability of occurrence of s₂ is .3.
The expected value of perfect information is

A) 18.1.
B) 11.7.
C) 51.
D) 37.

Question 48

A posterior probability associated with sample information is of the form​

A) ​P(a sample outcome | a state of nature).
B) ​P(a state of nature | a sample outcome).
C) ​P(a decision alternative | a sample outcome).
D) ​P(a sample outcome | a decision alternative).