Deck 20: Decision Analysis

Question 1

New information can be used to revise or update the prior probabilities so that the final decision is based on _____.

A) input from a larger group of individuals
B) figures that were voted upon
C) more accurate probabilities for the states of nature
D) the opinion of the CEO

Answer 1

more accurate probabilities for the states of nature

Question 2

The probabilities of states of nature after revising the prior probabilities based on given indicator information are _____.

A) the expected probabilities
B) the posterior probabilities
C) the prior probabilities
D) None of the answers is correct.

Answer 2

the posterior probabilities

Question 3

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

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

Answer 3

branch

Question 4

Experts in problem solving agree that the first step in solving a complex problem is to _____.

A) decompose it into a series of smaller sub-problems
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 5

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

A) decision alternative probabilities
B) in pounds or some unit of weight
C) in dollars or some unit of currency
D) the state-of-nature probabilities

Question 6

A decision criterion that weights the payoff for each decision by its probability of occurrence is known as the _____.

A) payoff criterion
B) expected value criterion
C) probability
D) expected value of perfect information

Question 7

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

A) decision tree
B) payoff table
C) matrix
D) sequential matrix

Question 8

Future events that cannot be controlled by the decision maker are called _____.

A) indicators
B) states of nature
C) prior probabilities
D) posterior probabilities

Question 9

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

A) junction
B) intersection
C) intersection point
D) node

Question 10

The probabilities for the states of nature must be _____.

A) between 0 and 1 and they must add to 1
B) a series of zeros and ones
C) greater than 1 and must sum to 100 or less
D) derived using the classical method of assigning probabilities

Question 11

The expected opportunity loss of the best decision alternative is the _____.

A) expected value
B) payoff
C) expected value of perfect information
D) None of the answers is correct.

Question 12

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

A) expected value of sample information
B) expected value of perfect information
C) maximum information
D) expected value

Question 13

The probability of the states of nature, after use of Bayes' theorem to adjust the prior probabilities based on given indicator information, is called _____.

A) marginal probability
B) conditional probability
C) posterior probability
D) None of the answers is correct.

Question 14

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

A) alternatives
B) decision outcomes
C) payoffs
D) states of nature

Question 15

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) the expected probability
D) perfect information

Question 16

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 opportunity loss
D) the expected value of perfect information

Question 17

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 opportunity loss
D) the expected value of perfect information

Question 18

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) optima
B) expected value of sample
C) expected value of perfect
D) efficiency of

Question 19

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

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

Question 20

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

A) joint
B) unconditional
C) marginal
D) conditional

Question 21

A posterior probability associated with sample information is of the form _____.

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

Question 22

The approach 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 23

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 24

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 25

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

A) population information
B) sampling without replacement
C) sample information
D) conditional information

Question 26

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) a contingency plan

Question 27

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

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

Question 28

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

A) happenstance
B) consequence
C) alternative probability
D) conditional probability

Question 29

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

A) unconditional
B) joint
C) marginal
D) conditional