1.Future events that cannot be controlled by the decision maker are called _.
A) states of nature
2.Exhibit 20-5
Below is a payoff table involving three states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 | S3 |
| A | -20 | 10 | 15 |
| B | 16 | -5 | 8 |
| C | 15 | 25 | -10 |
The probability of occurrence of s1 is .2, and the probability of occurrence of s2 is .3.
Refer to Exhibit 20-5. The recommended decision alternative based on the expected value is _.
ans) A
3.Exhibit 20-1
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 5 | 8 |
| B | 10 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .2.
Refer to Exhibit 20-1. The expected value of alternative A is _.
ans) 7.4
4.Exhibit 20-4
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 15 | 12 |
| B | 16 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .3.
Refer to Exhibit 20-4. The expected value of the best alternative is _.
ans) 13.2
5.The expected opportunity loss of the best decision alternative is the _.
ans) expected value of perfect information
6.New information obtained through research or experimentation that enables an updating or revision of the state-of-nature probabilities is known as _.
ans) sample information
7.Experts in problem solving agree that the first step in solving a complex problem is to _.
ans) decompose it into a series of smaller sub-problems
8.Nodes indicating points where an uncertain event will occur are known as _ nodes.
ans) chance
9.A tabular presentation of the expected gain from the various options open to a decision maker is called _.
ans) a payoff table
10.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.
ans) expected value of sample
11.New information can be used to revise or update the prior probabilities so that the final decision is based on _.
ans) more accurate probabilities for the states of nature
12.The result obtained when a decision alternative is chosen and a chance event occurs is known as the _.
ans) consequence
13.Experts in problem solving agree that the first step in solving a complex problem is to _.
ans) decompose it into a series of smaller sub-problems
14.Exhibit 20-4
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 15 | 12 |
| B | 16 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .3.
Refer to Exhibit 20-4. The expected value of the best alternative is _.
ans) 13.2
15.The approach to determine the optimal decision strategy involves _.
ans) a backward (right to left) pass through the decision tree
16.Nodes indicating points where an uncertain event will occur are known as _ nodes.
ans) chance
17.Exhibit 20-1
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 5 | 8 |
| B | 10 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .2.
Refer to Exhibit 20-1. The recommended decision alternative based on the expected value is _.
ans) B
18.A line or arc connecting the nodes of a decision tree is called a(n) _.
ans) branch
19.Exhibit 20-1
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 5 | 8 |
| B | 10 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .2.
Refer to Exhibit 20-1. The expected value of alternative A is _.
ans) 7.4
20.Exhibit 20-4
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 15 | 12 |
| B | 16 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .3.
Refer to Exhibit 20-4. The recommended decision alternative based on the expected value is _.
ans) B
21.Experts in problem solving agree that the first step in solving a complex problem is to _.
ans) decompose it into a series of smaller sub-problems
22.A decision criterion that weights the payoff for each decision by its probability of occurrence is known as the _.
ans) expected value criterion
23.The probabilities for the states of nature must be _.
A) between 0 and 1 and they must add to 1
24.Exhibit 20-1
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 5 | 8 |
| B | 10 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .2.
Refer to Exhibit 20-1. The recommended decision alternative based on the expected value is _.
ans) B
25.Application of Bayes’ theorem enables us to compute the _.
A) conditional probability of the states of nature given each sample outcome
26.Exhibit 20-4
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 15 | 12 |
| B | 16 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .3.
Refer to Exhibit 20-4. The expected value of alternative C is _.
ans) 10.2
27.Exhibit 20-3
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | $50,000 | –$10,000 |
| B | $10,000 | $15,000 |
| C | $25,000 | $10,000 |
The probability of the occurrence of state of nature s1 is .4.
Refer to Exhibit 20-3. The expected value of perfect information equals _.
ans) $13,000
28.A tabular representation of the payoffs for a decision problem is a _.
ans) payoff table
29.Exhibit 20-3
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | $50,000 | –$10,000 |
| B | $10,000 | $15,000 |
| C | $25,000 | $10,000 |
The probability of the occurrence of state of nature s1 is .4.
Refer to Exhibit 20-3. The expected value of the best alternative equals _.
ans) $16,000
30.The result obtained when a decision alternative is chosen and a chance event occurs is known as the _.
ans) consequence
31.Application of Bayes’ theorem enables us to compute the _.
ans) conditional probability of the states of nature given each sample outcome
32.When working backward through a decision tree, the analyst should _.
ans) compute the expected value at each chance node
33.Prior probabilities are the probabilities of the states of nature _.
ans) prior to obtaining sample information
34.An intersection or junction point of a decision tree is called a(n) _.
ans) node
35.A posterior probability associated with sample information is of the form _.
ans) P(a state of nature | a sample outcome
36.The probability of both sample information and a particular state of nature occurring simultaneously is known as _ probability.
ans) joint
37.Application of Bayes’ theorem enables us to compute the _.
ans) conditional probability of the states of nature given each sample outcom
38.Exhibit 20-1
Below is a payoff table involving two states of nature and three decision alternatives.
| Decision Alternative | S1 | S2 |
| A | 5 | 8 |
| B | 10 | 12 |
| C | 20 | 6 |
The probability of occurrence of s1 = .2.
Refer to Exhibit 20-1. The expected value of perfect information is _.
ans) 2.0
39.The possible outcomes for chance events that can affect the outcome of a decision are known as _.
ans) states of nature
40.The expected value of information that would tell the decision maker exactly which state of nature is going to occur is the _.
ans) expected value of perfect information
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