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to Introduction Management Science, 10e (Taylor)
Chapter 12 Decision Analysis
1) A state of nature is an actual event that may occur in the future.
Diff: 1
Page Ref: 527
Main Heading: Components of Decision Making
Key words: state of nature
2) A payoff table is a means of organizing a decision situation, including the payoffs from
different decisions given the various states of nature.
Diff: 1
Page Ref: 527
Main Heading: Components of Decision Making
Key words: payoff table
3) The maximax criterion results in the maximum of the maximum payoffs.
Diff: 2
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: maximax criterion
4) The maximin approach involves choosing the alternative with the highest payoff.
Diff: 2
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
5) Regret is the difference between the payoff from the best decision and all other decision
payoffs.
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
6) The minimax regret criterion minimizes the maximum regret.
Diff: 2
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
1
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
7) The minimax regret criterion maximizes the maximum regret.
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
8) The Hurwicz criterion is a compromise between the maximax and maximin criteria.
Diff: 2
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
9) The Hurwicz criterion is a compromise between the minimax and minimin criteria.
Diff: 2
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
10) The coefficient of optimism is a measure of the decision maker's optimism.
Diff: 1
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
11) The Hurwicz criterion multiplies the best payoff by the coefficient of optimism.
Diff: 1
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
12) The Hurwicz criterion multiplies the worst payoff by the coefficient of optimism.
Diff: 1
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
13) A dominant decision is one that has better payoff than another decision under each state of
nature.
Diff: 1
Page Ref: 533
Main Heading: Decision Making without Probabilities
Key words: dominant decision
2
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
14) The appropriate criterion is dependent on the risk personality and philosophy of the decision
maker.
Diff: 3
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: decision making criteria
15) The maximax criterion is optimistic.
Diff: 3
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: decision making criteria
16) The maximin criterion maximizes the minimum regret.
Diff: 1
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
17) The minimax criterion minimizes the maximum payoff.
Diff: 1
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax criterion
18) Regret and opportunity loss mean the same thing.
Diff: 2
Page Ref: 537
Main Heading: Decision Making without Probabilities
Key words: expected value of perfect information
19) The equal likelihood criterion assigns a probability of 0.5 to each state of nature.
Diff: 1
Page Ref: 533
Main Heading: Decision Making without Probabilities
Key words: equal likelihood criterion
20) Expected opportunity loss is the expected value of the regret for each decision.
Diff: 2
Page Ref: 536
Main Heading: Decision Making with Probabilities
Key words: expected opportunity loss, minimax regret criterion
3
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
21) When using decision trees, branches with the greatest expected value are selected.
Diff: 1
Page Ref: 541
Main Heading: Decision Making with Probabilities
Key words: decision trees
22) A decision tree is a diagram consisting of circles decision nodes, square probability nodes,
and branches.
Diff: 1
Page Ref: 541
Main Heading: Decision Making with Probabilities
Key words: decision trees
23) When the __________ criterion is used, the maximum of the maximum payoffs is observed.
Answer: maximax
Diff: 1
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: decision making without probabilities maximax criterion
24) When the __________ criterion is used, the maximum of the minimum payoffs is observed
Answer: minimax
Diff: 1
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: decision making without probabilities, minimax criterion
25) __________ is the difference between the payoff from the best decision and all other
decision payoffs.
Answer: Regret
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: regret, minimax regret criterion
26) The __________ is a compromise between the maximax and the maximin criterion.
Answer: Hurwicz criterion
Diff: 2
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
27) The __________ is a measure of the decision makers optimism.
Answer: coefficient of optimism
Diff: 2
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: coefficient of optimism
4
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
28) A(n) __________ decision is one that has a better payoff than another decision under the
state of nature.
Answer: dominant
Diff: 2
Page Ref: 533
Main Heading: Decision Making without Probabilities
Key words: dominant decision
29) A __________ structures decisions with series of nodes.
Answer: decision tree
Diff: 1
Page Ref: 540
Main Heading: Decision Making without Probabilities
Key words: decision trees
30) The __________ of sample information is the ratio of the expected value of sample
information to the expected value of perfect information.
Answer: efficiency
Diff: 1
Page Ref: 556
Main Heading: Decision Making without Probabilities
Key words: expected value of sample information
31) When the __________ criterion is used, the decision maker selects the decision alternative
that minimizes the maximum regret.
Answer: minimax
Diff: 1
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax criterion
32) A ________ decision tree illustrates a situation requiring a services of decisions.
Answer: sequential
Diff: 1
Page Ref: 545
Main Heading: Decision Making with Probabilities
Key words: decision trees
33) ________ is a measure of personal satisfaction derived from money.
Answer: Utility
Diff: 1
Page Ref: 558
Main Heading: Utility
Key words: utility
34) People who forgo a high expected value to avoid a disaster with a low probability are
__________.
Answer: risk averters
Diff: 1
Page Ref: 558
Main Heading: Decision Making with Probabilities
Key words: risk averters, utility
5
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
A group of friends are planning a recreational outing and have constructed the following payoff
table to help them decide which activity to engage in. Assume that the payoffs represent their
level of enjoyment for each activity under the various weather conditions.
Weather
Cold Warm Rainy
S1
S2
S3
Bike: A1 10
8
6
Hike: A2
14
15
2
Fish: A3
7
8
9
35) If the group is optimistic, what decision should they make?
Answer: D2
Diff: 3
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: maximax criterion
36) If the group is conservative, what decision will they make?
Answer: D3
Diff: 3
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
37) If the group chooses to minimize their maximum regret, what activity will they choose?
Answer: 3-way tie
Diff: 3
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
38) If the probabilities of cold weather (S1), warm weather (S2), and rainy weather (S3) are 0.2,
0.4, and 0.4, respectively, then what decision should be made using the expected value criterion?
Answer: Ev(d1) = 7.6
Ev(d2) = 9.6 (best)
Ev(d3) = 8.2
Diff: 3
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: expected value criterion
39) What is the EVPI for this situation?
Answer: EVPI = 12.4 - 9.6 = 2.8
Diff: 3
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: expected value of perfect information
6
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
An investor is consider 4 different opportunities, A, B, C, or D. The payoff for each opportunity
will depend on the economic conditions, represented in the payoff table below.
Poor
Investment (S1)
A
50
B
80
C
-100
D
25
Economic Condition
Average
Good
Excellent
(S2)
(S3)
(S4)
75
20
30
15
40
50
300
-50
10
25
25
25
40) What decision would be made under maximax?
Answer: compare 75, 80, 300 and 25. Choose investment C.
Diff: 3
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: maximax criterion
41) What decision would be made under maximin?
Answer: Compare 20, 15, -100 and 25. Choose investment D.
Diff: 3
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
42) What decision would be made under minimax regret?
Answer: Compare 225, 285, 180 and 275. Select investment C.
Diff: 3
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
43) If the probabilities of each economic condition are 0.5, 0.1, 0.35, and 0.05 respectively, what
investment would be made using the expected value criterion?
Answer: Investment B with an EMV of 58
Diff: 3
Page Ref: 537
Main Heading: Decision Making without Probabilities
Key words: expected value of perfect information
44) What is the expected value of perfect information?
Answer: The EVPI is 28.5.
Diff: 3
Page Ref: 539
Main Heading: Decision Making without Probabilities
Key words: expected value criterion
7
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
A manager has developed a payoff table that indicates the profits associated with a set of
alternatives under 2 possible states of nature.
Alt
1
2
3
S1
10
-2
8
S2
2
8
5
45) If the manager uses maximin as the decision criterion, which of the alternatives should she
choose?
Answer: maximin: Alt 3
Diff: 2
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
46) If the manager uses minimax regret as the decision criterion, which of the alternatives would
she choose?
Answer: Select alternative 3.
Alt
S1
S2
worst
1
0
6
6
2
12
0
12
3
2
3
3 (min regret)
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
47) Use the expected value criterion to select the best alternative. Assume that the probability of
S2 is equal to 0.4.
Answer:
EV (Alt 1) = 0.6(10) + 0.4(2) = 6.8
EV (Alt 2) = 0.6(-2) + 0.4(8) = 2.0
EV (Alt 3) = 0.6(8) + 0.4(5) = 6.8
Select either alternative 1 or 3.
Diff: 2
Page Ref: 537
Main Heading: Decision Making without Probabilities
Key words: expected value criterion
48) Compute the expected value of perfect information assuming that the probability of S2 is
equal to 0.4.
Answer: EVPI = 0.6(10) + 0.4(8) - 6.8 = 2.4
Diff: 2
Page Ref: 539
Main Heading: Decision Making without Probabilities
Key words: expected value of perfect information
8
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
The local operations manager for the IRS must decide whether to hire 1, 2, or 3 temporary
workers. He estimates that net revenues will vary with how well taxpayers comply with the new
tax code.
49) If he uses the maximin criterion, how many new workers will he hire?
Answer: 1
Diff: 2
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
50) If he uses the minimax regret criterion, how many new workers will he hire?
Answer: 2
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
51) If he thinks the chances of low, medium, and high compliance are 20%, 30%, and 50%
respectively, what are the expected net revenues for the number of workers he will decide to
hire?
Answer: $50000
Diff: 2
Page Ref: 537
Main Heading: Decision Making without Probabilities
Key words: expected value criterion
52) If he thinks the chances of low, medium, and high compliance are 20%, 30%, and 50%
respectively, what is the expected value of perfect information?
Answer: $26000
Diff: 2
Page Ref: 539
Main Heading: Decision Making without Probabilities
Key words: expected value of perfect information
9
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
A manufacturer must decide whether to build a small or a large plant at a new location. Demand
at the location can be either small or large, with probabilities estimated to be 0.4 and 0.6
respectively. If a small plant is built, and demand is large, the production manager may choose to
maintain the current size or to expand. The net present value of profits is $223,000 if the firm
chooses not to expand. However, if the firm chooses to expand, there is a 50% chance that the
net present value of the returns will be 330,000 and 50% chance the estimated net present value
of profits will be $210,000. If a small facility is built and demand is small, there is no reason to
expand and the net present value of the profits is $200,000. However, if a large facility is built
and the demand and the demand turns out to be small, the choice is to do nothing with a net
present value of $40,000 or to stimulate demand through local advertising. The response to
advertising can be either modest with a probability of .3 or favorable with a probability of .7. If
the response to advertising is modest the net present value of the profits is $20,000. However, if
the response to advertising is favorable, then the net present value of the profits is$220,000.
Finally, the when large plant is built and the demand happens to be high, the net present value of
the profits $800,000.
53) Draw a decision tree.
Answer:
Diff: 2
Page Ref: 540
Main Heading: Decision Making without Probabilities
Key words: sequential decision tree
10
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
54) Draw a decision tree and determine the payoff for each decision and event node. Which
alternative should the manufacturer choose?
Answer:
EV1 = (.3)(20,000) + (.7)((220,000) = $160,000
EV2 = (.5)(330,000) + (.5)((210,000) = $270,000
EV3 = (.4)(200,000) + (.6)((270,000) = $242,000
EV4 = (.4)(160,000) + (.6)((800,000) = $544,000
Since 544,000 > 242,000 build a large plant
Diff: 3
Page Ref: 540
Main Heading: Decision Making without Probabilities
Key words: sequential decision tree
11
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
55) If a student attends every management science class, the probability of passing the course is
0.80; but if the student only attends randomly, then the probability of passing the course is 0.50.
If a student fails, they can take a makeup exam where the probability of passing is 0.60 if the
student has attended every class. This probability of passing the makeup exam drops to 0.10 if
the student has attended at random.
Passing the course is worth 5 credits. Full time attendance "costs" 3 credits in terms of energy
and time whereas random attendance "costs" only 1 credit.
Use a decision tree to decide which is the best attendance pattern to adopt. Assume that all
failing students take the make up exam and that the payoff for failing is equal to 0.
Answer:
The expected value of attending all classes is 4.6 3 = 1.6.
The expected value of attending randomly is 2.75 1 = 1.75, so the student should attend at
random.
Diff: 2
Page Ref: 540
Main Heading: Decision Making without words: Probabilities
Key decision trees
12
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
The quality control manager for ENTA Inc. must decide whether to accept (a1), further analyze
(a2) or reject (a3) a lot of incoming material. Assume the following payoff table is available.
Historical data indicates that there is 30% chance that the lot is poor quality (s1), 50 % chance
that the lot is fair quality (s2) and 20% chance that the lot is good quality (s3).
56) What action would you choose according to maximax criterion?
Answer: (90 > 80 > 70), accept the lot, a1
Diff: 2
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: maximax criterion
57) What action would you choose according to maximin criterion?
Answer: (10 < 20 < 40), reject the lot , a3
Diff: 2
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
58) Construct the regret table
Answer:
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax criterion, regret table
59) What action would you choose according to minimax regret criterion?
Answer: Regret Table
(80 > 60 >50), therefore reject the lot
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax criterion
13
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
60) What action would you choose according to expected value criterion?
Answer:
EV1 = (.3)(20) + (.5)(30) + (.2)(90) = 39
EV2 = (.3)(60) + (.5)(70) + (.2)(10) = 55
EV3 = (.3)(80) + (.5)(50) + (.2)(40) = 57
Since 57 > 55 > 39, reject the lot
Diff: 2
Page Ref: 537
Main Heading: Decision Making without Probabilities
Key words: expected value criterion
61) What is the maximum amount that you would be willing to pay for perfect information?
Answer: expected payoff with perfect information = (.3)(80) + (.5)(70) + (.2)(90) = 77
EVPI = 77 - max (EV) = 77 -57 = 20
Diff: 3
Page Ref: 539
Main Heading: Decision Making without Probabilities
Key words: expected value of perfect information
62) Lucky Lucy is playing the slots in Reno, Nevada, holding her last silver dollar. There are
three possible payoffs if she wins: one cherry, $1.00; two cherries, $5.00; or three cherries,
$50.00. Anything else on the slot machine loses.
Construct the payoff table for Lucky Lucy
Answer:
Diff: 2
Page Ref: 527
Main Heading: Decision Making without Probabilities
Key words: payoff table
14
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
63) Consider the following decision tree.
What is the expected value at node 4?
Answer: $600
Diff: 1
Page Ref: 540
Main Heading: Decision Making without Probabilities
Key words: expected value, decision trees
15
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
64) Consider the following decision tree.
What is the value associated with node 3?
Answer: $2,500
Diff: 2
Page Ref: 540
Main Heading: Decision Making without Probabilities
Key words: expected value, decision trees
16
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
65) Consider the following decision tree.
Which decision, A or B, is best? What is the expected value of this decision?
expected payoff = $2,100
Diff: 2
Page Ref: 540
Main Heading: Decision Making without Probabilities
Key words: expected value, decision trees
66) The maximax criterion results in the
A) maximum of the minimum payoffs
B) maximum of the maximum payoffs
C) minimum of the maximum payoffs
D) minimum of the minimum payoffs
Diff: 2
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: maximax criterion
67) The maximin criterion results in the
A) minimum of the maximum payoffs
B) maximum of the maximum payoffs
C) maximum of the minimum payoffs
D) minimum of the minimum payoffs
Diff: 2
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
17
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
68) Regret is the difference between the payoff from the
A) best decision and all other decision payoffs
B) worst decision and all other decision payoffs
C) best decision and the worst decision payoffs
D) none of the above
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: regret, minimax regret criterion
69) The __________ minimizes the maximum regret.
A) maximax regret criterion
B) minimax regret criterion
C) minimin regret criterion
D) maximin regret criterion
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
70) The minimax regret criterion
A) maximizes the minimum regret
B) minimizes the minimum regret
C) minimizes the maximum regret
D) maximizes the maximum regret
Diff: 2
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: minimax regret criterion
71) Determining the worst payoff for each alternative and choosing the alternative with the best
worst is called
A) maximin
B) minimin
C) maximax
D) minimax
Diff: 3
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
18
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
72) The maximin approach to decision making refers to
A) minimizing the maximum return
B) maximizing the minimum return
C) maximizing the maximum return
D) minimizing the minimum return
Diff: 3
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
73) The term opportunity loss is most closely related to
A) maximin regret
B) maximax regret
C) minimax regret
D) minimin regret
Diff: 3
Page Ref: 531
Main Heading: Decision Making without Probabilities
Key words: expected opportunity loss, minimax regret criterion
74) The Hurwicz criterion is a compromise
A) for the maximin criterion
B) for the maximax criterion
C) between the maximax and maximin criteria
D) none of the above
Diff: 2
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
75) The Hurwicz criterion multiplies the
A) best payoff by the coefficient of optimism
B) worst payoff by the coefficient of optimism
C) best payoff by the worst payoff
D) none of the above
Diff: 1
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
19
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
76) The basic decision environment categories are
A) certainty
B) risk
C) uncertainty
D) all of the above
Diff: 2
Page Ref: 527
Main Heading: Decision Making without Probabilities
Key words: decision making
77) The basic decision environment categories are
A) certainty and risk
B) risk and uncertainty
C) certainty and uncertainty
D) certainty, uncertainty and risk
Diff: 2
Page Ref: 527
Main Heading: Decision Making without Probabilities
Key words: decision making
78) The Hurwicz criterion
A) multiplies the worst payoff by one minus the coefficient of optimism
B) multiplies the best payoff by the coefficient of optimism
C) is a compromise between the maximax and maximin criteria
D) all of the above
Diff: 1
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: Hurwicz criterion
79) The appropriate criterion is dependent on
A) the risk personality of the decision maker
B) the philosophy of the decision maker
C) all of the above
D) none of the above
Diff: 3
Page Ref: 558
Main Heading: Decision Making without Probabilities
Key words: decision making
20
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
80) The __________ is a measure of the decision maker's optimism.
A) equal likelihood criterion
B) dominant decision
C) coefficient of optimism
D) none of the above
Diff: 2
Page Ref: 532
Main Heading: Decision Making without Probabilities
Key words: coefficient of optimism, Hurwicz criterion
81) The __________ multiplies the decision payoff for each state of nature by an equal weight.
A) dominant decision
B) coefficient of optimism
C) equal likelihood criterion
D) none of the above
Diff: 2
Page Ref: 533
Main Heading: Decision Making without Probabilities
Key words: equal likelihood criterion
82) A __________ is one that has better payoff than another decision under each state of nature.
A) coefficient of optimism
B) equal likelihood criterion
C) dominant decision
D) none of the above
Diff: 2
Page Ref: 533
Main Heading: Decision Making without Probabilities
Key words: dominant decision
21
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
83) A business owner is trying to decide whether to buy, rent, or lease office space and has
constructed the following payoff table based on whether business is brisk or slow.
The maximax strategy is:
A) Buy
B) Rent
C) Lease
D) Brisk
E) Slow
Diff: 1
Page Ref: 529
Main Heading: Decision Making without Probabilities
Key words: maximax criterion
84) A business owner is trying to decide whether to buy, rent, or lease office space and has
constructed the following payoff table based on whether business is brisk or slow.
The maximin strategy is:
A) Buy
B) Rent
C) Lease
D) Brisk.
E) Slow
Diff: 2
Page Ref: 530
Main Heading: Decision Making without Probabilities
Key words: maximin criterion
22
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
85) A business owner is trying to decide whether to buy, rent, or lease office space and has
constructed the following payoff table based on whether business is brisk or slow.
The equal likelihood criterion strategy is:
A) Buy
B) Rent
C) Lease
D) High
E) Low
Diff: 2
Page Ref: 533
Main Heading: Decision Making without Probabilities
Key words: equal likelihood criterion
86) A business owner is trying to decide whether to buy, rent, or lease office space and has
constructed the following payoff table based on whether business is brisk or slow.
If the probability of brisk business is .40 and for slow business is .60, the expected value of
perfect information is:
A) 12
B) 55
C) 57
D) 69
E) 90
Diff: 2
Page Ref: 536
Main Heading: Decision Making without Probabilities
Key words: expected value of perfect information
23
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
87) The __________ is computed by multiplying each decision outcome under each state of
nature by the probability of its occurrence.
A) expected value
B) expected value of perfect information
C) expected opportunity loss
D) none of the above
Diff: 2
Page Ref: 537
Main Heading: Decision Making with Probabilities
Key words: expected value
88) The __________ is the expected value of the regret for each decision.
A) expected value
B) expected opportunity loss
C) expected value of perfect information
D) none of the above
Diff: 2
Page Ref: 537
Main Heading: Decision Making with Probabilities
Key words: expected opportunity loss
89) A tabular presentation that shows the outcome for each decision alternative under the various
possible states of nature is called a
A) decision tree
B) payoff table
C) feasible region
D) payback matrix
Diff: 2
Page Ref: 527
Main Heading: Decision Making with Probabilities
Key words: payoff table
90) The __________ is the maximum amount a decision maker would pay for additional
information.
A) expected opportunity loss
B) expected value
C) expected value of perfect information
D) none of the above
Diff: 2
Page Ref: 539
Main Heading: Decision Making with Probabilities
Key words: expected value of perfect information
24
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
91) A decision tree is a diagram consisting of
A) square decision nodes
B) circle probability nodes
C) branches representing decision alternatives
D) all of the above
Diff: 1
Page Ref: 540
Main Heading: Decision Making with Probabilities
Key words: decision trees
92) In __________ additional information is used to alter the marginal probability of the
occurrence of an event.
A) Bayesian analysis
B) decision analysis
C) probability analysis
D) all of the above
Diff: 2
Page Ref: 550
Main Heading: Decision Analysis with Additional Information
Key words: Bayesian analysis
93) A __________ probability is the probability that an event will occur given that another event
has already occurred.
A) posterior
B) conditional
C) marginal
D) all of the above
Diff: 2
Page Ref: 550
Main Heading: Decision Analysis with Additional Information
Key words: conditional
94) A __________ probability is the altered marginal probability of an event based on additional
information.
A) marginal
B) conditional
C) posterior
D) none of the above
Diff: 2
Page Ref: 552
Main Heading: Decision Analysis with Additional Information
Key words: posterior
25
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
95) The efficiency of sample information is the ratio of the expected value of sample information
to the
A) expected value of perfect information
B) expected value
C) utilization rate
D) coefficient of optimism
E) expected opportunity loss
Diff: 2
Page Ref: 556
Main Heading: Utility
Key words: efficiency of sample information
96) The expected value of sample information
A) is never more than EVPI
B) can be compared to the sample cost to judge whether to sample.
C) is never negative
D) all of the above are true
E) Only A and C are true.
Diff: 2
Page Ref: 556
Main Heading: Utility
Key words: efficiency of sample information
97) People who forgo a high expected value to avoid a disaster with a low probability are
A) risk takers
B) risk averters
C) risk calculators
D) risk predictors
Diff: 1
Page Ref: 558
Main Heading: Utility
Key words: risk averters, utility
98) People who take a chance on a bonanza with a very low probability of occurrence in lieu of a
sure thing are
A) risk takers
B) risk averters
C) risk calculators
D) risk predictors
Diff: 1
Page Ref: 558
Main Heading: Utility
Key words: risk takers, utility
26
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
99) Utiles are units of __________ measures of utility.
A) quantitative
B) objective
C) subjective
D) qualitative
Diff: 3
Page Ref: 558
Main Heading: Utility
Key words: utility
A small entrepreneurial company is trying to decide between developing two different products
that they believe they can sell to two potential companies, one large and one small. If they
develop Product A, they have a 50% chance of selling it to the large company with annual
purchases of about 20,000 units. If the large company won't purchase it, then they think they
have an 80% chance of placing it with a smaller company, with sales of 15,000 units. On the
other hand if they develop Product B, they feel they have a 40% chance of selling it to the large
company, resulting in annual sales of about 17,000 units. If the large company doesn't buy it,
they have a 50% chance of selling it to the small company with sales of 20,000 units.
100) What is the probability that Product Awill being purchased by the smaller company?
A) 0.8
B) 0.5
C) 0.4
D) 0.2
E) 0.1
Diff: 2
Page Ref: 540
Main Heading: Decision Making with Probabilities
Key words: decision trees
101) What is the probability that Product B will being purchased by the smaller company?
A) 0.8
B) 0.5
C) 0.4
D) 0.3
E) 0.1
Diff: 2
Page Ref: 540
Main Heading: Decision Making with Probabilities
Key words: decision trees
27
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall
102) How many units of Product A can they expect to sell?
A) 20,000
B) 17,000
C) 15,500
D) 15,000
E) 13,100
Diff: 2
Page Ref: 540
Main Heading: Decision Making with Probabilities
Key words: decision trees
103) How many units of Product A can they expect to sell?
A) 20,000
B) 17,000
C) 15,500
D) 15,000
E) 13,100
Diff: 2
Page Ref: 540
Main Heading: Decision Making with Probabilities
Key words: decision trees
104) How many units can they expect to sell for the optimum alternative?
A) 20,000
B) 17,000
C) 15,500
D) 15,000
E) 13,100
Diff: 2
Page Ref: 540
Main Heading: Decision Making with Probabilities
Key words: decision trees
28
Copyright 2010 Pearson Education, Inc. Publishing as Prentice Hall

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Strayer - MAT540 - MAT540

Introduction to Management Science, 10e (Taylor)Chapter 14 Simulation1) In computer mathematical simulation, a system is replicated with a mathematical model that isanalyzed with the computer.Answer: TRUEDiff: 1Page Ref: 628Main Heading: The Monte

Strayer - MAT540 - MAT540

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Berkeley - STAT 134 - 134

Chemistry 3ASuggested Problems #1A few notes about the suggested problems. For those from theexambook, you will find the notation X(Y). X refers to the pagenumber at the bottom MIDDLE of the page. The Y refers to theproblem on that page. If there is

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Suggested Problems #2 for Chemistry 3AFor instructions on how to interpret the numbering system below,see Suggested Problems #1.September 7, 2012From the Chemistry 3 ExambookBond-line structures, Resonance, Frontier MO theory, beginningarrow-pushing

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Suggested Problems #3 for Chemistry 3AFor instructions on how to interpret the numbering system below,see Suggested Problems #1.September 13, 2012From the Chemistry 3 ExambookNomenclature:5(a, b: 1st and 2nd ones), 13(c), 42(a: 3rd one; b: 1st one),

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S uggested Problems #5 for Chemistry 3AFor instructions on how to interpret the numbering system below seeSuggested Problems #1.September 25, 2012From the ExambookCyclohexane conformations and cycloalkane ring nomenclature.5(b: 3rd one), 12, 13(a),

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Suggested Problems #7 for Chemistry 3AFor instructions on how to interpret the numbering system below,see Suggested Problems #1.October 11, 2012From the Chemistry 3 ExambookStereochemistry. Part I17(a:3rd one; b:2nd one), 18, 36(not first a; a,b), 5

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Suggested Problems #8 for Chemistry 3AFor instructions on how to interpret the numbering system below,see Suggested Problems #1.October 18, 2012ExambookStereochemistry. Part IIPlease note that the new instructions for all Predict theProducts proble

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Suggested Problems #12 for Chemistry 3AFor instructions on how to interpret the numbering system below,see Suggested Problems #1.November 15, 2012From the Chemistry 3 ExambookReduction of Aldehydes and Ketones and Grignard/alkyl lithiumReagents19(d

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Suggested Problems #13 for Chemistry 3AFor instructions on how to interpret the numbering system below,see Suggested Problems #1.November 20, 2012From the Chemistry 3 ExambookAlkenes Part 1: Nomenclature and hydrogenation.26(a:4th,5th boxes; b), 29(

Berkeley - STAT 134 - 134

Homework 1 ProblemsStatistics 134, Pitman, Fall 20121.1.7 Suppose two dice are rolled. Find the probabilities of the following events.1. the maximum of the two numbers rolled is less than or equal to 2;2. the maximum of the two numbers rolled is less

Berkeley - STAT 134 - 134

Homework 1 Solutions1.1.7Statistics 134, Pitman, Fall 2012a) P (maximum 2) = P (both dice 2) = 4/36 = 1/9b) P (maximum 3) = P (both dice 3) = 9/36 = 1/4c) P (maximum = 3) = P (maximum 3) P (maximum 2) = 5/36d)OutcomeProbability12341/36 3/36 5

Berkeley - STAT 134 - 134

Homework 2 ProblemsStatistics 134, Pitman, Fall 20122.1.2 Suppose that in 4-child families, each child is equally likely to be a boy or a girl,independently of the others. Which would then be more common, 4-child families with2 boys and 2 girls, or 4-

Berkeley - STAT 134 - 134

Homework 2 SolutionsStatistics 134, Pitman, Fall 20122.1.2 P (2 boys and 2 girls) = 4 (1/2)4 = 6/24 = 0.375 < 0.5. So families with dierent2numbers of boys and girls are more likely than those having an equal number of boysand girls, and the relative

Berkeley - STAT 134 - 134

Homework 3 ProblemsStatistics 134, Pitman , Fall 20122.4.4 Repeat the previous problem for the event of getting 30 or more sixes in 100 die rolls,which has probability 0.00068.2.4.6 A box contains 1000 balls, of which 2 are black and the rest are whit

Berkeley - STAT 134 - 134

Homework 3 SolutionsStatistics 134, Pitman , Fall 20122.4.4 Here = 365 0.00068 = 0.2482, anda) 1 e = .219796;b) 1 e e = 0.026150.2.4.6a) The number of black balls seen in a series of 100 draws with replacement hasbinomial (1000, 2/1000) distributio

Berkeley - STAT 134 - 134

Homework 4 Problems3.2.8 Suppose E (X 2 ) = 3,E (Y 2 ) = 4,Statistics 134, Pitman , Fall 2012E (XY ) = 2. Find E [(X + Y )2 ].3.2.14 A building has 10 oors above the basement. If 12 people get into an elevator at thebasement, and each chooses a oor

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Homework 4 SolutionsStatistics 134, Pitman , Fall 20123.2.8 E [(X + Y )2 ] = E (X 2 ) + 2E (XY ) + E (Y 2 ) = 11.3.2.14 We want E (N ), where N is the number of oors at which the elevator makes a stop0to let out one or more of the people. N is a coun

Berkeley - STAT 134 - 134

Homework 5 ProblemsStatistics 134, Pitman , Fall 20123.3.2 Let Y be the number of heads obtained if a fair coin is tossed three times. Find themean and variance of Y 2 .3.3.4 Suppose X1 and X2 are independent. Find a formula for V ar(X1 X2 ) in terms

Berkeley - STAT 134 - 134

Homework 5 SolutionsStatistics 134, Pitman , Fall 20123.3.2 E (Y 2 ) = 3, V ar(Y 2 ) = 15/23.3.4 V ar(X1 X2 ) = E [(X1 X2 )2 ] [E (X1 X2 )]222= E (X1 ) E (X2 ) [E (X1 X2 )]222= (2 + 1 ) (2 + 2 ) (1 2 )2122222= 2 2 + 2 1 + 1 2213.3.6 By s

Berkeley - STAT 134 - 134

Homework 6 ProblemsStatistics 134, Pitman , Fall 20123.4.4 In the game of odd one out three people each toss a fair coin to see if one of theircoins shows a dierent face from the other two.1. After one play, what is the probability of some person bein

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Homework 6 Solutions3.4.4Statistics 134, Pitman , Fall 2012a) The probability of some person being the odd one out is 1 the probability ofhaving the three coins be HHH or TTT. Thus the probability is 1 ( 1 )3 + ( 1 )3 =223.4b) Let the length of

Berkeley - STAT 134 - 134

Homework 7 ProblemsStatistics 134, Pitman , Fall 20124.1.2 Suppose X has density f (x) = c/x4 for x > 1, and f (x) = 0 otherwise, where c is aconstant. Findc;E (X );V ar(X ).4.1.4 Suppose X with values in (0, 1) has density f (x) = cx2 (1 x)2 for 0

Berkeley - STAT 134 - 134

Homework 7 Solutions4.1.2Statistics 134, Pitman , Fall 2012a)1ccdx = 34x3x=1c3and since f (x) is a density function, it must integrate to 1, so c = 3.b)xE (X ) =133dx = 2x42x=1c)E (X 2 ) =x2133dx =x4xThus V ar(X ) = E (

Berkeley - STAT 134 - 134

Homework 8 ProblemsStatistics 134, Pitman , Fall 20124.2.4 Suppose component lifetimes are exponentially distributed with mean 10 hours. Find:1. the probability that a component survives 20 hours;2. the median component lifetime;3. the SD of componen

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Homework 8 SolutionsStatistics 134, Pitman , Fall 20124.2.4 Let W be the lifetime of a component. Then W has exponential distribution withrate = 1/10.a) P (W > 20) = e20 = e2 0.135 .b) The median lifetime m satises1/2 = P (W > m) = em m =(log 2)=

Berkeley - STAT 134 - 134

Homework 9 ProblemsStatistics 134, Pitman , Fall 20124.5.4 Let X be a random variable with c.d.f. F (x). Find the c.d.f. of aX + b rst for a > 0,then for a < 0.4.5.6 Let X be a random variable with c.d.f. F (x) = x3 for 0 x 1. Find:1. P (X 1 );22.

Berkeley - STAT 134 - 134

Homework 9 SolutionsStatistics 134, Pitman , Fall 20124.5.4 If a > 0, thenFaX +b (y ) = P (aX + b y )yb=P Xayb= FXaIf a < 0, thenFaX +b (y ) = P (aX + b y )yb=P Xayb= 1 FXaassuming FX (x) is a continuous function of x.4.5.6a) P (X 1/2)

Berkeley - STAT 134 - 134

Homework 10 ProblemsStatistics 134, Pitman , Fall 20125.2.4 For random variables X and Y with joint density functionf (x, y ) = 6e2x3y(x, y > 0)and f (x, y ) = 0 otherwise, nd:1. P (X x, Y y ); fX (x); fY (y ).2. Are X and Y independent? Give a rea

Berkeley - STAT 134 - 134

Homework 10 Solutions5.2.4Statistics 134, Pitman , Fall 2012a)yx6e2x3y dydxP (X x, Y y ) =00x=0y16e2x ( e3y ) dx30x2e2x dx= (1 e3y )03y= (1 eb))(1 e2x )6e2x3y dy = 2e2xfX (x) =0c)6e2x3y dx = 3e3yfY (y ) =0d) Yes, they are

Berkeley - STAT 134 - 134

Homework 11 ProblemsStatistics 134, Pitman , Fall 20126.1.2 In a particular town 10% of the families have no children, 20% have one child, 40%have two children, 20% have three children, and 10% have four. Let T represent thetotal number of children, a

Berkeley - STAT 134 - 134

Homework 11 SolutionsStatistics 134, Pitman , Fall 20126.1.2 Condition on the value of T :4P (G = g |T = t)P (T = t)P (G = g ) =t=0Now given T = t, G has binomial (t, 1/2) distribution, sot(1/2)t ,gP (G = g |T = t) =g = 0, . . . , t.Conclude:

Berkeley - STAT 134 - 134

Homework 12 ProblemsStatistics 134, Pitman , Fall 20126.4.4 Let (X, Y ) have uniform distribution on the four points (1, 0), (0, 1), (0, 1), (1, 0).Show that X and Y are uncorrelated but not independent.6.4.8 You have N boxes labeled Box1, Box2,. . .

Berkeley - STAT 134 - 134

Intermolecular Forces!Intermolecular forces take place between molecules.!!!!!An understanding of intermolecular forces is crucial !to a chemists ability to successfully carry out reactions !in the organic chemistry laboratory.!!The Forces Betwe

Berkeley - STAT 134 - 134

Terminology of MixingSolution: A homogenous mixture of two or more compounds.Solute: The compound in a solution present in lesser amount.Solvent: The major component of a solution.Miscibility: Two components of a solution are innitely soluble in each

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Melting PointsTypical Phase Changes as a Function of Temperatureat a Constant PressureTemperatureDbp, cpBmp, fpELCGGas(G)LiquidSolidASL(L)(S)Heat AddedBC = melting point(mp)/freezing point(fp): [Psolid = Pliquid]DE = boiling point(b

Berkeley - STAT 134 - 134

Boiling PointsImpurities and Boiling PointsSoluble, Non-Volatile ImpurityPA = vapor pressureof compound A in a solution of A and asoluble impurityPressureRaoults Law:PA = XAPAELiquidSolidPatmDTCGasReduced vaporpressure curvedue to the

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Purifying Solids!!!! Sublimation/Deposition! Chromatography! Recrystallization!Recrystallization!Step 1: Choosing the right equipment!The Glassware! Erlenmeyer ask!Richard Erlenmeyer! Test tube!Constricted opening!Large surface area!Step 1:

Berkeley - STAT 134 - 134

Chromatography!Separation of Different Compounds!!!! Partition! Adsorption!Adsorption Chromatography!Compounds that have Different Interactions with the Mobile Phase!Versus the Stationary Phase can be Separated !ABCABA CC CBBAaddsolventst

Berkeley - STAT 134 - 134

Retention Factor (Rf)!Not a Physical Constant!Rf = !distance to !midpoint!of spot!distance to !solvent front!Rf depends on:!u The stationary phase !u The mobile phase !u The amount of compound!spotted!u The temperature!TLC: Conclusions!Give

Berkeley - STAT 134 - 134

Structure Determination!v NMR Spectroscopy!v Mass Spectrometry!v X-Ray Crystallography!Spectroscopy!Absorption of Electromagnetic Radiation:!Something Changes from a Lower Energy !State to a Higher Energy State!E = h !E: change in energyh : Plan

Berkeley - STAT 134 - 134

Spin-Spin Splitting !(J Coupling)!Coupling of spins provides connectivity information !about neighboring nuclei!1HNMR Spectrum of 1,1,2-trichloroethane!HBPredicted !HAH B!ClHBClClHA!TMS6ppm5ppm4ppm3ppm2ppm1ppm0 ppmObserved! !TMS6p

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Complex Coupling !singlet!doublet!triplet!?!quartet!Successive Application of the N + 1 Rule!HBHAHBClCl ClTMS6ppm5ppm4ppm3ppm1ppm2ppm0 ppmTwo different hydrogen atoms coupling to a third hydrogen atom!HAWhat if:!JAB = 3 Hz!JAC = 8

GWU - BADM - 2201

Indonesia Country AssessmentDavid FetnerAdam WertheimQmarth GhaemiTorrance ShepardsonAlexander LeeINDONESIA2Table of ContentsIntroduction.3Indonesia is an archipelago or a country that is composed of thousands of islands. With approximately 17,00

GWU - BADM - 2201

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GWU - BADM - 2003W

Qmarth GhaemiHow does/can a business balance profits and social responsibility?When a business becomes so consumed in worrying about profit it losses sight of what suroundsthe company. Even when a business is doing well there can be times in which soci

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Qmarth GhaemiAssignment 3In Harold Koontzs article, The Management Theory Jungle Revisited, attempts to explain the new findings with the management jungle and how this is effecting everyone. It goeson to describe how the original management theory jun

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Qmarth GhaemiHow does/can a business balance profits and social responsibility?When a business becomes so consumed in worrying about profit it losses sight of what suroundsthe company. Even when a business is doing well there can be times in which soci

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Please complete this worksheet for your Paper 2 Peer Review Assignment. You may also makecomments on their paper if youd like, but it is not required.Name of Student doing the Peer Review:Qmarth GhaemiName of Student whose paper is being peer reviewed

GWU - BADM - 2003W

The George Washington University BADM.2003W, WID Summer Reading Program,HANNAN, Fall 2012.V2Congratulations on the successful completion of your first year in our University!In keeping with the tradition embodied by The George Washington University of

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Business Ethics-Desire to do whats right-Self-policing-Business practices should add value to society-Should hurt the least amount of people-Obligation to behave legally-Need to add value to business-FairnessManagement Jungle-Connectivity and coh

GWU - BADM - 2003W

Q GhaemiHannan 2003 WPaper 1How is tThis Happening Under Our Own EyesSimple enough, the problem with these modern companies is the fact that they are unable to adjust to the changing climate of each field. Creative Destruction went into detail about w

GWU - BADM - 2003W

Q GhaemiPaper 2A business is defined as something that seeks profit. There are many different things that will inhibit a businesss opportunity to expand its profit. It is the duty of those in charge to make surethat the most profit is brought in by the

GWU - BADM - 2003W

Qmarth Ghaemi2003W; HannanMondaySummer SynthesisOver the years I have discovered that one thing is for certain, that the moment I wrote myfinal summer paper for high school merely two years ago, I truly thought this was the end to allsummer assignme

GWU - BADM - 2003W

IntroductionThe following is a financial analysis of Anheuser-Busch. Included is a deeper look into the current finances, trends in the sector, the merger with InBev, and a brief history of the company inaddition to other topics of discussion.Anheuser-

GWU - BADM - 2003W

Your name: Qmarth GhaemiPeer review colleague: Ryan WinemanEmail: qghaemi@gwu.eduThe primary purpose of this worksheet is to insure that your colleague has developed a clear, completeand convincing recommendation. Imagine, then, that you are a potenti