Decision Analysis: Techniques and Applications in Business

Posted on Aug 12, 2024 in Mathematics

  1. decision analysis supports ol but 1 of d following goals.Which goal is nt supported?
    1. help make gud decisions.
    2. help ensure selection of gud outcomes.
    3. analyze decision problems logically.ab.
    4. incorpor8 problem uncertainty.

Answer


b

  1. although modeling provides valuable insight 2 decision makers,decision making remains a difficult task.Which of d following is nt a primary cause 4 dis difficulty discussed in d decision analysis chapter?
    1. uncertainty regarding d future.
    2. models provide decisions 4 d decision maker.
    3. conflicting values.
    4. conflicting objectives.

answer:  b

  1. a course of action intended 2 solve a problem is called a(n)
    1. altern8ve.
    2. option.
    3. decision.
    4. criteria.

answer:  a

  1. decision analysis techniques provide modeling techniques 2 help decision makers make decisions.Which of d following is nt typically a benefit of decision analysis?
    1. incorpor8ng uncertainty via probabilities.
    2. incorpor8ng risk via utility theory functions.
    3. incorpor8ng uncertainty via exp1ntial distributions.
    4. structuring decision str8gies via decision trees.

answer:  c

  1. which of d following is a goal of decision analysis?
    1. help individuals make gud decisions.
    2. ensure decisions lead 2 gud outcomes.
    3. avoiding decisions leading 2 bad outcomes.
    4. reduce d role of luck in a decision.

answer:  a

  1. din a decision problem represent fac2rs dat
    R important 2 d decision maker.
    1. payoffs
    2. st8s of nature
    3. criteria
    4. altern8ves

answer:  c


  1. dcorrespond 2 future events dat R nt under d control of d decision maker.
    1. payoffs
    2. st8s of nature
    3. criteria
    4. altern8ves

answer:  b

  1. a(n)is a course of action intended 2 solve a problem.
    1. decision
    2. criteria
    3. st8 of nature
    4. altern8ve

answer:  d

  1. a payoff matrix depictsversuswith payoffs 4 each intersection cell.
    1. decision criteria;st8s of nature.
    2. decision altern8ves;potential outcomes.
    3. decision altern8ves;st8s of nature.
    4. decision criteria;potential outcomes.

answer:  c

  1. which of d following summarizes d final outcome 4 each decision altern8ve?
    1. payoff matrix
    2. outcome matrix
    3. yield matrix
    4. per4mance matrix

answer:  a

  1. d decision rule which determines d maximum payoff 4 each altern8ve & then selects d altern8ve associ8d with d largest payoff is d
    1. maximax decision rule.
    2. maximin decision rule.
    3. minimax regret decision rule.
    4. minimin decision rule.

answer:  a

  1. which decision rule optimistically assumes dat nature will always b “on our side” regardless of ? Decision we make?
    1. maximax decision rule.
    2. maximin decision rule.
    3. minimax regret decision rule.
    4. minimin decision rule.

answer:  a


  1. which decision rule pessimistically assumes dat nature will always b “against us” regardless of ? Decision we make?
    1. maximax decision rule.
    2. maximin decision rule.
    3. minimax regret decision rule.
    4. minimin decision rule.

answer:  b

  1. d decision rule which determines d minimum payoff 4 each altern8ve & then selects d altern8ve associ8d with d largest minimum payoff is d
    1. maximax decision rule.
    2. maximin decision rule.
    3. minimax regret decision rule.
    4. minimin decision rule.

answer:  b

  1. evry nonprobabilistic method hs a weakness 4 decision making.Which of d following is incorrect regarding a method & its weakness?
    1. d maximax method ignores potentially large losses.
    2. d maximin method ignores potentially large payoffs.
    3. d minimax regret method can lead 2 inconsistent decisions.
    4. ol of these R correct.

answer:  d

  1. d c8gory of decision rules dat contains d maximax decision rule is d
    1. optimistic c8gory.
    2. non-probabilistic c8gory.
    3. probabilistic c8gory.
    4. optimality c8gory.

answer:  b

  1. d amount of opportunity lost in making a decision is called
    1. loss.
    2. frustr8on.
    3. neg8ve profit.
    4. regret.

answer:  d

  1. d decision rule which selects d altern8ve associ8d with d smallest maximum opportunity loss is d
    1. maximax decision rule.
    2. maximin decision rule.
    3. minimax regret decision rule.
    4. minimin decision rule.

answer:  c


  1. how R st8s of nature assigned probabilities?
    1. use his2rical data.
    2. use best judgements.
    3. use interview results.
    4. ol of these.answer:  d exhibit 14.1

d following questions R based on d in4m8on below.

an inves2r is considering 4 investments,a,b,c & leaving his m1y in d bank.D payoff frm each investment is a function of d economic clim8 over d next 2 years.D economy can expand or decline.D following payoff matrix hs been developed 4 d decision problem.

a

b

c

d

1

payoff matrix

2

3

economy

4

investment

decline

expand

5

a

0

85

6

b

25

65

7

c

40

30

8

bank

10

10

payoffs


Refer


2 exhibit
14.1.? Decision should b made according 2 d maximax decision rule?

  1. a
    1. b
    2. c
    3. bank

answer:  a

  1. refer 2 exhibit 14.1.? Decision should b made according 2 d maximin decision rule?
    1. a
    2. b
    3. c
    4. bank

answer:  c


  1. refer 2 exhibit 14.1.? Decision should b made according 2 d minimax regret decision rule?
    1. a
    2. b
    3. c
    4. bank

answer:  b

  1. refer 2 exhibit 14.1.? 4mula should go in cell d5 2 implement d maximax decision rule?

a.=max(max(b5:c5))

b.=min(b5:c5)

c.=average(b5:c5)

d.=max(b5:c5)

answer:  d

  1. refer 2 exhibit 14.1.? 4mula should go in cell d5 2 implement d maximin decision rule?

a.=max(min(b5:c5))

b.=min(b5:c5)

c.=average(b5:c5)

d.=max(b5:c5)

answer:  b

  1. probabilistic decision rules can b used if d st8s of nature in a decision problem can b assigned probabilities dat represent their likelihood of occurrence.Which of d following is nt tru regarding d probabilities employed?
    1. d probabilities R always obtained frm his2rical data.
    2. d probabilities must always b unbiased.
    3. d probabilities can b assigned subjectively.
    4. subjective probabilities obtained can b accur8 & unbiased.

answer:  a


exhibit 14.2

d following questions R based on d in4m8on below.

an inves2r is considering 4 investments,a,b,c & leaving his m1y in d bank.D payoff frm each investment is a function of d economic clim8 over d next 2 years.D economy can expand or decline.D following payoff matrix hs been developed 4 d decision problem.

a

b

c

d

e

f

g

h

1

payoff matrix

regret matrix

2

3

     economy

     economy

4

investment

decline

expand

investment

decline

expand

5

a

0

85

a

6

b

25

65

b

7

c

40

30

c

8

bank

10

10

      bank

  1. refer 2 exhibit 14.2.? 4mula should go in cell f5 of d regret matrix above 2 compute d regret value?A.=b$5-max(b$5:b$8)

b.  =max(b$5:b$8)-max(b5)

c. =max(b$5:b$8)-min(b$5:b$8) d.=max(b$5:b$8)-b5

answer:  d

  1. refer 2 exhibit 14.2.? 4mula should go in cell h5 & copied 2 h6:h8 of d regret table above 2 implement d minimax regret decision rule?

a.=max(max(f5:g5))

b.=min(f5:g5)

c.=average(f5:g5)

d.=max(f5:g5)

answer:  d

  1. d decision with d smallest expected opportunity loss (eol) will also have d
    1. smallest emv.
    2. largest emv.
    3. smallest regret.
    4. largest regret.

answer:  b


  1. expected regret is also called
    1. emv.
    2. eol.
    3. epa.
    4. eoq.

answer:  b

  1. d minimum eol in a decision problem will always
    1. exceed d evpi.
    2. b less than d evpi.
    3. equal d evpi.
    4. equal d emv.answer:  c


Exhibit 14.3

d following questions R based on d in4m8on below.

an inves2r is considering 4 investments,a,b,c & leaving his m1y in d bank.D payoff frm each investment is a function of d economic clim8 over d next 2 years.D economy can expand or decline.D following payoff matrix hs been developed 4 d decision problem.D inves2r hs estim8d d probability of a declining economy @ 70% & an expanding economy @ 30%.

a

b

c

d

e

f

g

h

1

payoff matrix

regret matrix

2

3

economy

economy

4

investment

decline

expand

emv

investment

decline

eol

5

a

−10

90

a

6

b

20

50

b

7

c

40

45

c

8

bank

15

20

bank

9

10

probability

0.7

0.3

probability

0.7

0.3

  1. refer 2 exhibit 14.3.? Decision should b made according 2 d expected m1tary value decision rule?
    1. a
    2. b
    3. c
    4. bank

answer:  c


  1. refer 2 exhibit 14.3.? Is d expected m1tary value of investment a?A.34.

b.30.

c.20.

d.15.

answer:  c

  1. refer 2 exhibit 14.3.? 4mula should go in cell f5 & copied 2 f6:f8 of d spreadsheet if d expected regret decision rule is 2 b used?

a.=b$5-max(b$5:b$8)

b.  =max(b$5:b$8)-max(b5)

c. =max(b$5:b$8)-min(b$5:b$8) d.=max(b$5:b$8)-b5

answer:  d

  1. refer 2 exhibit 14.3.? Decision should b made according 2 d expected regret decision rule?
    1. a
    2. b
    3. c
    4. bank

answer:  c


exhibit 14.4

d following questions R based on d in4m8on below.

a

b

c

d

e

1

payoff matrix

2

3

economy

4

                 investment

decline

expand

emv

5

a

0

80

6

b

30

70

7

c

50

35

8

bank

20

20

9

10

probability

0.7

0.3

11

12

payoff of decision made with perfect in4m8on:

13

14

evpi:

evpi

  1. refer 2 exhibit 14.4.? Is d expected value of perfect in4m8on 4 d inves2r?A.13.5

b.20 c.45.5

d.59

answer:  a

  1. refer 2 exhibit 14.4.? Is d expected value with perfect in4m8on 4 d inves2r?A.13.5

b.45.5

  1. 59
  2. 80

answer:  c

  1. refer 2 exhibit 14.4.? 4mula should go in cell d14 of d spreadsheet 2 compute d evpi?
    1. max(d5:d8)-d12
    2. d12-min(d5:d8)
    3. sumproduct(b12:c12,b10:c10)-max(d5:d8)
    4. d12-max(d5:d8)

answer:  d


  1. a square node in a decision tree is called a(n)node.
    1. chance
    2. random
    3. decision
    4. event

answer:  c

  1. a circular node in a decision tree is called a(n)node.
    1. chance
    2. random
    3. decision
    4. event

answer:  d

  1. leaves of a decision tree R also callednodes.
    1. end
    2. terminal
    3. decision
    4. payoff

answer:  b



exhibit 14.5

d following questions R based on d in4m8on below.

an inves2r is considering 4 investments,a,b,c,d.D payoff frm each investment is a function of d economic clim8 over d next 2 years.D economy can expand or decline.D following decision tree hs been developed 4 d problem.D inves2r hs estim8d d probability of a declining economy @ 40% & an expanding economy @ 60%.

  1. refer 2 exhibit 14.5.? Is d correct decision 4 dis inves2r based on an expected m1tary value criteria?
    1. a
    2. b
    3. c
    4. d

answer:  d

  1. refer 2 exhibit 14.5.? Is d expected m1tary value 4 d inves2r’s problem?
    1. 32
    2. 36
    3. 38
    4. 42

answer:  c



  1. refer 2 exhibit 14.5.How hi can p(e) go be4 d inves2r’s decision,based on expected m1tary value criteria,changes?

a.0.65

b.0.70

c.0.75

d.0.80

answer:  d

  1. an inves2r is considering 2 investments,a,b,which can b made now.After these investments R made he can pursue choices c,d,e & f depending on whether he chose a or b originally.He hs developed d following decision tree 2 aid in his selection process.? R d correct original & subsequent decisions based on an expected m1tary value criteria?

  1. a,c
    1. a,d
    2. b,e
    3. b,f

answer:  d



  1. a company is planning a plant expansion.Dey can build a large or small plant.D payoffs 4 d plant depend on d level of consumer demand 4 d company’s products.D company believes dat there is an 69% chance dat demand 4 their products will b hi & a 31% chance dat it will b low.D company can pay a market research firm 2 survey consumer attitudes 2wards d company’s products.There is a 63% chance dat d cus2mers will like d products & a 37% chance dat dey 1’t.D payoff matrix & costs of d 2 plants R listed below.D company believes dat if d survey is favorable there is a 92% chance dat demand will b hi 4 d products.If d survey is unfavorable there is only a 30% chance dat d demand will b hi.D following decision tree hs been built 4 dis problem.D company hs computed dat d expected m1tary value of d best decision without sample in4m8on is 154.35 million.? Is d evsi 4 dis problem (in $ million)?

       demand

fac2ry size

hi

low

plant cost ($million)

large

200

85

10

small

100

95

2

a.0.07

b.26.38

c.109.5

d.180.8

answer:  a

  1. d 2tal worth,value or desirability of a decision altern8ve is called its
    1. usefulness.
    2. worthiness.
    3. utility.
    4. risk.

answer:  c


  1. a “risk averse” decision maker assigns drel8ve utility 2 ne payoff but hs a(n)marginal utility 4 increased payoffs.
    1. largest;increasing
    2. largest;diminishing
    3. smallest;diminishing
    4. smallest;increasing

answer:  b



exhibit 14.6

d following questions use d in4m8on below.

a company is planning a plant expansion.Dey can build a large or small plant.D payoffs 4 d plant depend on d level of consumer demand 4 d company’s products.D company believes dat there is an 69% chance dat demand 4 their products will b hi & a 31% chance dat it will b low.D company can pay a market research firm 2 survey consumer attitudes 2wards d company’s products.There is a 63% chance dat d cus2mers will like d products & a 37% chance dat dey 1’t.D payoff matrix & costs of d 2 plants R listed below.D company believes dat if d survey is favorable there is a 92% chance dat demand will b hi 4 d products.If d survey is unfavorable there is only a 30% chance dat d demand will b hi.D following decision tree hs been built 4 dis problem.D company hs computed dat d expected m1tary value of d best decision without sample in4m8on is 154.35 million.D company hs developed d following conditional probability table 4 their decision problem.

a

b

c

d

1

2

joint probabilities

3

hi demand

low demand

2tal

4

favorable  response

0.58

0.05

0.63

5

unfavorable  response

0.11

0.26

0.37

6

2tal

0.69

0.31

1.00

7

8

9

conditional probability

4 a given survey response

10

11

hi demand

low demand

12

favorable  response

0.92

0.08

13

unfavorable  response

0.30

0.70

14

15

conditional probability

4 a given demand level

16

17

hi demand

low demand

18

favorable  response

0.84

0.16

19

unfavorable  response

0.16

0.84

  1. refer 2 exhibit 14.6.? Is p(f∩h),where f = favorable response & h = hi demand?A..58

b..63

c..84

d..92

answer:  a



  1. refer 2 exhibit 14.6.? 4mula should go in cell c13 of d probability table?A.=c5/$d4

b.=c5/c$6 c.=c5/$d5 d.=c4/$d4

answer:  c

exhibit 14.7

d following questions use d in4m8on below.

a decision maker is faced with 2 altern8ves.D decision maker hs determined dat she is indifferent btwn d 2 altern8ves wen p = 0.45.

altern8ve 1:           receive $82,000 with certainty

altern8ve 2:           receive $143,000 with probability p & lose $15,000 with probability (1 − p).

  1. refer 2 exhibit 14.7.? Is d expected value of altern8ve 2 4 dis decision maker?A.$82,000

b.$56,100 c.$64,350 d.$72,600

answer:  b

  1. refer 2 exhibit 14.7.? Is d decision maker’s certainty equivalent
    4 dis problem?A.−$15,000

b.$82,000 c.$56,100 d.$82,000

answer:  d

  1. refer 2 exhibit 14.7.? Is d decision maker’s risk premium
    4 dis problem?A.−$20,000

b.−$25,900 c.$70,000 d.$80,000

answer:  b

  1. ? Is d 4mula 4 d exp1ntial utility function u(x)?
    1. −e−x/r
    2. 1 + e−x/r
    3. 1 − ex/r
    4. 1 − e−x/r

answer:  d


  1. ? Is d 4mula 4 d w8ed average score 4 altern8ve j wen using a multi-criteria scoring model?A.

b.

c.

d.

answer:  a

  1. d scores in a scoring model range frm
    1. 0 2 1
    2. −1 2 +1
    3. 0 2 5
    4. 0 2 10

answer:  a

  1. d scores in a scoring model can b thought of as subjective assessments of
    1. usefulness.
    2. worthiness.
    3. utility.
    4. payoff.

answer:  c

  1. a fast food restaurant is considering opening a new s2re @ 1 of 4 loc8ons.Dey have developed d following multi-criteria scoring model 4 dis problem.? Loc8on should dey choose based on dis in4m8on?

a

b

c

d

e

f

g

h

1

scores

2

site

site

site

site

criterion

3

            criterion

a

b

c

d

w8s

4

sales

0.80

0.75

0.70

0.65

0.4

5

           loc8on

0.70

0.80

0.88

0.95

0.3

6

            security

0.40

0.50

0.60

0.50

0.2

7

growth

0.60

0.60

0.80

0.85

0.1

8

w8ed average score

1

  1. a
    1. b
    2. c
    3. d

answer:  c



  1. based on d radar chart of raw scores provided below,y? Is dis decision complex?

  1. d chart is hard 2 read.
    1. no site wins on ol 4 criteria.
    2. no site achieves a perfect score of 1.0 on a criteria.
    3. no sites have sufficient security.

answer:  b



  1. based on d radar chart of d w8ed scores provided below,which of d following interpret8ons is incorrect?

  1. site a wins on d sales criteria but is last on d loc8on criteria.
    1. site c wins on d security criteria & scores hi on d remaining 3 criteria.
    2. site b scores lowest on each of d 4 criteria.
    3. no site domin8s on each of d 4 criteria.

answer:  c



exhibit 14.8

d following questions use d in4m8on below.

a company needs 2 buy a new insurance policy.Dey have 3 policies 2 choose frm,a,b & c.D policies differ with respect 2 price,coverage & ease of billing.D company hs developed d following ahp tables 4 price & summary.D other tables R nt shown due 2 space limit8ons.

a

b

c

d

e

f

g

1

2

pairwise comparisons

3

a

b

c

4

a

1.000

3.000

5.000

5

b

0.333

1.000

2.000

6

c

0.200

0.500

1.000

7

sum

1.533

4.500

8.000

8

9

price      consistency

normalized comparisons

10

a

b

c

scores

measure

11

a

0.652

0.667

0.625

0.648

3.007

12

b

0.217

0.222

0.250

0.230

3.003

13

c

0.130

0.111

0.125

0.122

3.001

14

15

consistency  r8o:

0.003

price

a

b

c

d

e

f

g

1

2

3

           criterion

a

b

c

4

price

0.648

0.230

0.122

0.123

5

coverage

0.213

0.701

0.085

0.320

6

billing

0.120

0.272

0.608

0.557

7

w8ed avg.Score:

0.215

0.404

0.381

1.000

summary

  1. refer 2 exhibit 14.8.? 4mula should go in cell f11 & get copied 2 f12:f13 of d price worksheet 2 compute d price score?

a.=average(c4:c6)

b.=average(c11:e11)

c.=average(g11:g13)

d.=average(c7:e7)

answer:  b


  1. refer 2 exhibit 14.8.? 4mula should go in cell g11 & get copied 2 g12:g13 of d price worksheet 2 compute d consistency measure?

a. =mmult(c4:e4,$f$11:$f$13)

b. =sumproduct(c4:e4,$f$11:$f$13)/f11 c. =mmult(c4:e4,$f$11:$f$13)/f11

d. =mmult(c7:e7,$f$11:$f$13)/f11

answer:  c

  1. refer 2 exhibit 14.8.? 4mula should go in cell g15 of d price worksheet 2 compute d consistency r8o?

a. =average(g11:g13)-3)/(2*0.58)

b.=average(g11:g13)-3)

c. =average(g11:g13))/(2*0.58) d. =average(g11:g13)-3)/0.58

answer:  a

  1. refer 2 exhibit 14.8.? 4mula should go in cell c7 & get copied 2 d7:e7 of d summary worksheet 2 compute d w8ed average score?

a. =sumproduct(c4:e4,$g$4:$g$6)

b. =sumproduct(c4:c6,$c$5:$c$7)

c. =sumproduct($g$4,$g$6)

d. =sumproduct(c4:c6,$g$4:$g$6)

answer:  d

  1. refer 2 exhibit 14.8.Which policy should d company choose based on d summary worksheet?
    1. a
    2. b
    3. c
    4. n1 of these

answer:  b

  1. refer 2 exhibit 14.8.D consistency r8o indic8s consistency in d pairwise comparison matrix if d r8o is a.≤ 0.05

b.≤ 0.10

c.≤ 0.20

d.≤ 0.30

answer:  b



exhibit 14.9

d following questions R based on d in4m8on below.

an inves2r is considering 4 investments,w,x,y,& z.D payoff frm each investment is a function of d economic clim8 over d next 2 years.D economy can expand or decline.D following payoff matrix hs been developed 4 d investment decision problem.

a

b

c

d

e

1

                   payoff matrix

2

3

                     economy           

4

investment

           decline

expand

choice

5

w

0

80

6

x

30

70

7

y

50

35

8

z

20

20

payoffs

  1. refer 2 exhibit 14.9.? Decision should b made according 2 d maximax decision rule?

answer:  w

  1. refer 2 exhibit 14.9.? Decision should b made according 2 d maximin decision rule?

answer:  y

  1. refer 2 exhibit 14.9.? Decision should b made according 2 d minimax regret decision rule?

answer:  x

  1. refer 2 exhibit 14.9.? 4mula should go in cell d5 & get copied 2 d6:d8 2 implement d maximax decision rule?

answer:  =max(b5:c5)

  1. refer 2 exhibit 14.9.? 4mula should go in cell d5 & get copied 2 d6:d8 2 implement d maximin decision rule?

answer:  =min(b5:c5)

  1. refer 2 exhibit 14.9.Assume d 4mula =max(b5:c5) was entered in cell d5 & copied 2 cells d6:d8.? 4mula should go in cell e5 & get copied 2 cells e6:e8 2 place a ” 2 indic8 d choice according 2 d maximax decision rule?

answer:   =if(d5=max($d$5:$d$8),”

  1. refer 2 exhibit 14.9.Assume d 4mula =min(b5:c5) was entered in cell d5 & copied 2 cells d6:d8.? 4mula should go in cell e5 & get copied 2 cells e6:e8 2 place a ” 2 indic8 d choice according 2 d maximin decision rule?

answer:   =if(d5=max($d$5:$d$8),”


  1. refer 2 exhibit 14.9.D original payoff data is in d worksheet called “payoffs”.? 4mula should go in cell b5 of dis regret matrix 2 compute d regret value?

a

b

c

d

1

regret matrix

2

3

economy

4

investment

           decline

expand

5

w

6

x

7

y

8

z

regret

answer:   =max(payoffs!B$5:b$8)-payoffs!B5

  1. refer 2 exhibit 14.9.? 4mula should go in cell d5 of d following regret table 2 implement d minimax regret decision rule?Assume dat cells b5:c8 contain d regret values 4 d problem.

a

b

c

d

1

regret matrix

2

3

economy

4

investment

          decline

expand

5

w

6

x

7

y

8

z

regret

answer:  =max(b5:c5)



exhibit 14.10

d following questions R based on d in4m8on below.

an inves2r is considering 4 investments,w,x,y,& z.D payoff frm each investment is a function of d economic clim8 over d next 2 years.D economy can expand or decline.D following payoff matrix hs been developed 4 d decision problem.D inves2r hs estim8d d probability of a declining economy @ 80% &  an expanding economy @ 20%.

a

b

c

d

1

payoff matrix

2

3

economy

4

investment

            decline

expand

emv

5

w

10

60

6

x

20

80

7

y

40

30

8

z

35

25

9

10

probability

0.8

0.2

payoffs

  1. refer 2 exhibit 14.10.Complete d table using d expected m1tary value decision rule & indic8 which decision should b made according 2 dat rule.

answer:

a

b

c

d

1

payoff matrix

2

3

            economy

4

investment

decline

expand

emv

5

w

10

60

20

6

x

20

80

32

7

y

40

30

38

8

z

35

25

33

9

10

probability

0.8

0.2

payoffs



  1. refer 2 exhibit 14.10.D original payoff data is in d worksheet above called “payoffs”.? 4mula should go in cell b5 of d spreadsheet if d expected regret decision rule is 2 b used?

a

b

c

d

1

regret matrix

2

3

economy

4

investment

decline

expand

eol

5

w

6

x

7

y

8

z

9

10

probability

0.8

0.2

regret

answer:   =max(payoffs!B$5:b$8)-payoffs!B5

  1. refer 2 exhibit 14.10.Complete d regret table according 2 d expected regret decision rule.

answer:

a

b

c

d

1

regret matrix

2

3

economy

4

investment

decline

expand

eol

5

w

30

20

30

6

x

20

16

7

y

50

10

8

z

5

55

15

9

   10

probability

0.8

0.2

regret



  1. refer 2 exhibit 14.10.Complete d following table 2 determine d expected value of perfect in4m8on 4 d inves2r.

a

b

c

d

e

1

payoff matrix

2

3

             economy

4

               investment

decline

expand

emv

5

w

10

60

6

x

20

80

7

y

40

30

8

z

35

25

9

   10

                   probability

0.8

0.2

   11

   12

payoff of decision made with perfect in4m8on:

   13

   14

evpi:

evpi

answer:

a

b

c

d

e

1

payoff matrix

2

3

economy

4

                 investment

decline

expand

emv

5

w

10

60

20

6

x

20

80

32

7

y

40

30

38

8

z

35

25

33

9

    10

                probability

0.8

0.2

    11

    12

payoff of decision made with perfect in4m8on:

40

80

48

     13

     14

evpi:

10

evpi



  1. refer 2 exhibit 14.10.? 4mulas should go in cell d5:d14 & b12:c12 of d spreadsheet 2 compute d evpi?

a

b

c

d

e

1

payoff matrix

2

3

            economy

4

              investment

decline

expand

emv

5

a

10

60

6

b

20

80

7

c

40

30

8

bank

35

25

9

10

               probability

0.8

0.2

11

12

payoff of decision made with perfect in4m8on:

13

14

evpi:

evpi

answer:  cell                         4mula                                                                                   copied 2

d5                   =sumproduct(b5:c5,$b$10:$c$10)                                 d6:d8,d12

b5                    =max(b5:b8)                                                                         c5

d14                 =d12-max(d5:d8)



  1. an inves2r is considering 4 investments,a,b,c,d.D payoff frm each investment is a function of d economic clim8 over d next 2 years.D economy can expand or decline.D following decision tree hs been developed 4 d problem.D inves2r hs estim8d d probability of a declining economy @ 25% & an expanding economy @ 75%.? Is d correct decision 4 dis inves2r based on an expected m1tary value criteria?Draw d decision tree 4 dis problem.

   answer:


c,emv = 45



  1. an inves2r is considering 4 investments,a,b,c,d.D payoff frm each investment is a function of d economic clim8 over d next 2 years.D economy can b weak or strong.D inves2r hs estim8d d probability of a declining economy @ 30% & an expanding economy @ 70%.Draw d decision tree 4 dis problem & determine d correct decision 4 dis inves2r based on d expected m1tary value criteria.

payoff matrix economy

investment

weak

strong

a

−30

120

b

20

60

c

30

35

d

15

30

answer:



correct decision,a with emv = 75.



  1. an inves2r is considering 2 investments,a,b,which can b purchased now 4 $10.There is a 40% chance dat investment a will grow rapidly in value & a 60% chance dat it will grow slowly.If a grows rapidly d inves2r can cash it in 4 $80 or trade it 4 investment c which hs a 25% chance of growing 2 $100 & a 75% chance of reaching $80.If a grows slowly it is sold 4 $50.There is a 70% chance dat investment b will grow rapidly in value & a 30% chance dat it will grow slowly.If b grows rapidly d inves2r can cash it in 4 $100 or trade it 4 investment d which hs a 20% chance of growing 2 $95 & an 80% chance of reaching $80.If b grows slowly it is sold 4 $45.Draw d decision tree 4 dis problem.

answer:

  1. an inves2r is considering 2 investments,a,b,which can b purchased now 4 $10.There is a 40% chance dat investment a will grow rapidly in value & a 60% chance dat it will grow slowly.If a grows rapidly d inves2r can cash it in 4 $80 or trade it 4 investment c which hs a 25% chance of growing 2 $100 & a 75% chance of reaching $80.If a grows slowly it is sold 4 $50.There is a 70% chance dat investment b will grow rapidly in value & a 30% chance dat it will grow slowly.If b grows rapidly d inves2r can cash it in 4 $100 or trade it 4 investment d which hs a 20% chance of growing 2 $95 & an 80% chance of reaching $80.If b grows slowly it is sold 4 $45.? Is d multistage decision 4 dis inves2r & ? Is d emv 4 dis decision?

answer:  pick b,sell b,emv = 83.5.



  1. a company is planning a plant expansion.Dey can build a large or small plant.D payoffs 4 d plant depend on d level of consumer demand 4 d company’s products.D company believes dat there is a 72% chance dat demand 4 their products will b hi & a 28% chance dat it will b low.D company can pay a market research firm 2 survey consumer attitudes 2wards d company’s products.There is a 76% chance dat d cus2mers will like d products & a 24% chance dat dey 1’t.D payoff matrix & costs of d 2 plants R listed below.D company believes dat if d survey is favorable there is an 87% chance dat demand will b hi 4 d products.If d survey is unfavorable there is only a 25% chance dat d demand will b hi.Draw d decision tree 4 d problem wen d survey is per4med be4 d plant size decision is made.

demand

fac2ry size

hi

low

plant cost ($million)

large

90

40

5

small

55

20

1

answer: 



exhibit 14.11

d following questions use d in4m8on below.

a company is planning a plant expansion.Dey can build a large or small plant.D payoffs 4 d plant depend on d level of consumer demand 4 d company’s products.D company believes dat there is an 72% chance dat demand 4 their products will b hi & a 28% chance dat it will b low.D company can pay a market research firm 2 survey consumer attitudes 2wards d company’s products.There is a 76% chance dat d cus2mers will like d products & a 24% chance dat dey 1’t.D payoff matrix & costs of d 2 plants R listed below.D company believes dat if d survey is favorable there is an 87% chance dat demand will b hi 4 d products.If d survey is unfavorable there is only a 25% chance dat d demand will b hi.

demand

fac2ry size

hi

low

plant cost ($million)

large

90

40

5

small

55

20

1

d company hs developed d following conditional probability table 4 their decision problem.

a

b

c

d

1

2

joint probabilities

3

hi demand

low demand

2tal

4

favorable  response

0.66

0.10

0.76

5

unfavorable  response

0.06

0.18

0.24

6

2tal

0.72

0.28

1.00

7

8

9

conditional probability

4 a given survey response

10

11

hi demand

low demand

12

favorable  response

0.87

0.13

13

unfavorable  response

0.25

0.75

14

15

conditional probability

4 a given demand level

16

17

hi demand

low demand

18

favorable  response

0.92

0.36

19

unfavorable  response

0.08

0.64

refer 2 exhibit 14.11.? Is p(f∩h),where f = favorable response & h = hi demand?

answer:  0.66


  1. refer 2 exhibit 14.11.? 4mula should go in cell c13 of d probability table?

answer:  c5/$d5


exhibit 14.12

d following questions use d in4m8on below.A decision maker is faced with 2 altern8ves.

altern8ve 1:        receive $40,000 with certainty

altern8ve 2:        receive $80,000 with probability p & lose $5,000 with probability (1 − p).

d decision maker hs determined dat she is indifferent btwn d 2 altern8ves wen p = 0.7.

  1. refer 2 exhibit 14.12.? Is d expected value of altern8ve 2 4 dis decision maker?

answer:  = 80,000 * .7 − 5,000 * .3 = 54,500

  1. refer 2 exhibit 14.12.? Is d decision maker’s certainty equivalent 4 dis problem?

answer:  $40,000

  1. refer 2 exhibit 14.12.? Is d decision maker’s risk premium 4 dis problem?

answer:  $14,500

  1. a convenience s2re chain is considering opening a new s2re @ 1 of 4 loc8ons.Dey have developed d following multi-criteria scoring model 4 dis problem.

a

b

c

d

e

f

g

h

1

scores

2

site

site

site

site

criterion

3

criterion

a

b

c

d

w8s

4

sales

0.65

0.75

0.70

0.80

0.50

5

loc8on

0.95

0.80

0.88

0.70

0.20

6

security

0.50

0.50

0.60

0.40

0.25

7

growth

0.85

0.60

0.80

0.60

0.05

8

w8ed average score

1

? 4mula should b entered in2 cell c8-f8 2 compute d w8ed average scores?

answer:



  1. a convenience s2re chain is considering opening a new s2re @ 1 of 4 loc8ons.Dey have developed d following multi-criteria scoring model 4 dis problem.Complete d table 4 dis problem.? Loc8on should dey choose based on dis in4m8on?

a

b

c

d

e

f

g

h

1

scores

2

site

site

site

site

criterion

3

criterion

a

b

c

d

w8s

4

sales

0.65

0.75

0.70

0.80

0.50

5

                loc8on

0.95

0.80

0.88

0.70

0.20

6

security

0.50

0.50

0.60

0.40

0.25

7

                 growth

0.85

0.60

0.80

0.60

0.05

8

w8ed average score

1

answer:

a

b

c

d

e

f

g

h

1

scores

2

site

site

site

site

criterion

3

              criterion

a

b

c

d

w8s

4

sales

0.65

0.75

0.70

0.80

0.50

5

loc8on

0.95

0.80

0.88

0.70

0.20

6

security

0.50

0.50

0.60

0.40

0.25

7

growth

0.85

0.60

0.80

0.60

0.05

8

w8ed average score

0.6825

0.69

0.716

0.67

1

site c should b selected.



  1. a convenience s2re chain is considering opening a new s2re @ 1 of 4 loc8ons.Dey have developed d following multi-criteria scoring model 4 dis problem.? 4mulas must b placed in cells c13:f16 2 compute d w8ed scores 4 use in gener8ng a w8ed score radar chart?

a

b

c

d

e

f

g

h

1

scores

2

site

site

site

site

criterion

3

               criterion

a

b

c

d

w8s

4

sales

0.65

0.75

0.70

0.80

0.50

5

               loc8on

0.95

0.80

0.88

0.70

0.20

6

security

0.50

0.50

0.60

0.40

0.25

7

                  growth

0.85

0.60

0.80

0.60

0.05

8

w8ed average score

0.6825

0.69

0.716

0.67

1

9

   10

scores

   11

site

site

site

site

criterion

   12

              criterion

a

b

c

d

w8s

   13

sales



0.50

   14

               loc8on



0.20

   15

               security



0.25

   16

               growth



0.05

   17

1

answer:  cell                         4mula                                                                       copied 2:

c13                  =c4*$h13                                                                   d13:f13,c14:f16



  1. a convenience s2re chain is considering opening a new s2re @ 1 of 4 loc8ons.Dey have developed d following multi-criteria scoring model 4 dis problem.Complete d follow table 2 prepare d spreadsheet 4 use in gener8ng a w8ed score radar chart?

a

b

c

d

e

f

g

h

1

scores

2

site

site

site

site

criterion

3

                criterion

a

b

c

d

w8s

4

sales

0.65

0.75

0.70

0.80

0.50

5

              loc8on

0.95

0.80

0.88

0.70

0.20

6

security

0.50

0.50

0.60

0.40

0.25

7

                 growth

0.85

0.60

0.80

0.60

0.05

8

w8ed average score

0.6825

0.69

0.716

0.67

1

9

10

scores

11

site

site

site

site

criterion

12

                criterion

a

b

c

d

w8s

13

sales



0.50

14

              loc8on



0.20

15

security



0.25

16

                growth



0.05

17

1

answer:

a

b

c

d

e

f

g

h

10

scores

11

site

site

site

site

criterion

12

             criterion

a

b

c

d

w8s

13

sales

0.3250

0.375

0.350

0.40

0.50

14

loc8on

0.1900

0.160

0.176

0.14

0.20

15

security

0.1250

0.125

0.150

0.10

0.25

16

growth

0.0425

0.030

0.040

0.03

0.05

17

1



exhibit 14.13

d following questions use d in4m8on below.

a student wants 2 buy a new car.She hs 3 cars 2 choose frm,a,b & c.D cars differ with respect 2 price,per4mance & looks.D student hs developed d following ahp tables 4 price & summary.D other tables R nt shown due 2 space limit8ons.

a

b

c

d

e

f

g

1

2

pairwise comparisons

3

a

b

c

4

a

1.000

0.999

0.250

5

b

1.001

1.000

0.200

6

c

4.000

5.000

1.000

7

sum

6.001

6.999

1.450

8

9

normalized comparisons

price

consistency

10

a

b

c

scores

measure

11

a

0.167

0.143

0.172

0.161

3.003

12

b

0.167

0.143

0.138

0.149

3.003

13

c

0.667

0.714

0.690

0.690

3.012

14

15

consistency  r8o:

0.005

         price

a

b

c

d

e

f

g

1

2

3

            criterion

a

b

c

4

price

0.557

0.320

0.123

0.123

5

per4mance

0.161

0.149

0.690

0.320

6

looks

0.115

0.182

0.703

0.557

7

w8ed avg.Score:

0.184

0.188

0.628

1.000

summary

  1. refer 2 exhibit 14.13.? 4mula should go in cell f11 & copied 2 cells f12:f13 of d price worksheet 2 compute d price score?

answer:   =average(c11:e11)


  1. refer 2 exhibit 14.13.? 4mula should go in cell g11 & copied 2 cells g12:g13 of d price worksheet 2 compute d consistency measure?

answer:   =mmult(c4:e4,$f$11:$f$13)/f11


  1. refer 2 exhibit 14.13.? 4mula should go in cell g15 of d price worksheet 2 compute d consistency r8o?

answer:   =average(g11:g13)-3)/(2*0.58)

  1. refer 2 exhibit 14.13.? 4mula should go in cell c7 & copied 2 cells d7:e7 of d summary worksheet 2 compute d w8ed average score?

answer:   =sumproduct(c4:c6,$g$4:$g$6)

  1. refer 2 exhibit 14.13.Which car should d student choose based on d summary worksheet?

answer:  car c

exhibit 14.14

d following questions use d decision tree model & str8gy table in4m8on below.

a

b

c

d

e

f

g

h

i

j

k

1

           str8gy table

2

p(g|b)

3

sell b

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

4

0

trade a 4 c

sell b

sell b

sell b

sell b

sell b

sell b

sell b

sell b

5

0.1

trade a 4 c

trade a 4 c

sell b

sell b

sell b

sell b

sell b

sell b

sell b

6

0.2

trade a 4 c

trade a 4 c

trade a 4 c

sell b

sell b

sell b

sell b

sell b

sell b

7

p(g|a)

0.3

trade a

4 c

trade a

4 c

trade a

4 c

sell b

sell b

sell b

sell b

sell b

sell b

8

0.4

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

sell b

sell b

sell b

sell b

sell b

9

0.5

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

sell b

sell b

sell b

sell b

10

0.6

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

sell b

sell b

sell b

sell b

11

0.7

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

sell b

sell b

sell b

12

0.8

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

sell b

sell b

13

0.9

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

sell b

sell b

14

1

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

trade a 4 c

sell b


  1. refer 2 exhibit 14.14.U want 2 conduct a risk analysis on p(g|a) & p(g|b).? Decision tree model changes must U make 2 b able 2 use a str8gy table?

answer:  change cell h17 2 =(1-h7) & change cell h21 2 =(1-h32)

  1. refer 2 exhibit 14.14.? 4mula is placed in cell b3 of d str8gy table 2 complete d table as provided?

answer:    =if(b20=1,choose(j9,l4,l12),choose(j34,l29,l37))

or =if(b20=1,choose(j9,”trade a 4 c”,”sell a”),choose(j34,”trade b 4 d”,”sell b”))

  1. refer 2 exhibit 14.14.Y? Does d str8gy table,examining d risk associ8d with p(g|a) & p(g|b) never show “sell a” or “trade b 4 d” as selected options?

answer:  d expected value of trade a 4 c will always exceed d certain value of sell a & d certain value of sell b will always exceed d expected value of trade b 4 d.

  1. project 14.1 − d pre-paid gas tank decision

yur company hs sent U on business 2 d los angeles (la) metropolitan area.Upon yur arrival @ lax,U make yur way 2 d klunker car rental counter.As usual,d line @ d counter is long,so U enter & begin yur wait.While waiting U notice dat klunker is offering a special deal on gas.Dey R selling gas 4

$1.579 per gallon.However,U must purchase a full tank wen U rent d car.Klunker also says dat d average price per gallon of gas in d la area is $1.60.UR uncertain of several necessary pieces of in4m8on 2 determine whether U should take advantage of dis deal.These R:

  • d 2tal miles U will drive on d trip;

rental car gas mileage;

how much gas d rental car’s tank holds;

d tru cost of gas in d la area.

1st,U expect 2 drive btwn 150 & 250 miles on dis trip.U believe there is an equal chance dat U will drive either of these extreme amounts.However,U may have 2 make a side trip 2 edwards afb dat will increase d 2tal miles 2 500.U believe there is a 1 in 5 chance dat dis will happen.Normally,klunker rents U a mid-size car.U believe most cars in dis class have either a 15 gallon gas tank with 60% confidence or a 18 gallon gas tank with 40% confidence.U’ve heard dat cars in dis class get as much as 25 mpg on d highway but may get as little as 18 mpg city driving.U decide there is an 70% chance most of yur driving will


b on d freeways & d rest in d city.Finally,U don’t believe klunker’s posted average price of $1.60 per gallon in d la area.U guess dat there is 40% chance dat d gas will b $1.259,20% chance it will b $1.479 & a 40% chance it will b $1.659.Assume U must decide whether 2 pre-purchase d tank of gas prior 2 talking 2 a klunker clerk.

  1. draw d decision tree 4 dis problem using decision tree in excel.
  1. ? Is d optimal decision?

now suppose U can delay yur decision til U speak 2 a clerk & find out exactly how

  1. much gas yur rental car holds.D clerk says d car U will rent holds 18 gallons of gas.? Is yur optimal decision now?? Is d value of dis additional in4m8on?


answer:

a.

d decision tree is a fully symmetric decision tree.D tree starts with d decision whether or nt 2 purchase d full tank of gas.After d decision node R 4 event nodes 4 miles drive,miles per gallon realized,size of d fuel tank on d rental car,& d cost of gas in d la area.

d following tables summarize d outcomes 4 each of d possible st8s of nature.

purchase d tank

miles driven

1.579

mgp

tank

price

150

250

500

18

15

1.259

$23.69

$23.69

$39.77

18

15

1.479

$23.69

$23.69

$42.58

18

15

1.659

$23.69

$23.69

$44.88

18

18

1.259

$28.42

$28.42

$40.73

18

18

1.479

$28.42

$28.42

$42.88

18

18

1.659

$28.42

$28.42

$44.64

25

15

1.259

$23.69

$23.69

$29.98

25

15

1.479

$23.69

$23.69

$31.08

25

15

1.659

$23.69

$23.69

$31.98

25

18

1.259

$28.42

$28.42

$30.94

25

18

1.479

$28.42

$28.42

$31.38

25

18

1.659

$28.42

$28.42

$31.74

purchase jst d gas

miles driven

mgp

tank

price

150

250

500

18

15

1.259

$10.49

$17.49

$34.97

18

15

1.479

$12.33

$20.54

$41.08

18

15

1.659

$13.83

$23.04

$46.08

18

18

1.259

$10.49

$17.49

$34.97

18

18

1.479

$12.33

$20.54

$41.08

18

18

1.659

$13.83

$23.04

$46.08

25

15

1.259

$  7.55

$12.59

$25.18

25

15

1.479

$  8.87

$14.79

$29.58

25

15

1.659

$  9.95

$16.59

$33.18

25

18

1.259

$  7.55

$12.59

$25.18

25

18

1.479

$  8.87

$14.79

$29.58

25

18

1.659

$  9.95

$16.59

$33.18

b.

based on d decision tree with d above outcomes included,d optimal decision is 2 purchase d tank of gas with an expected m1tary value of $26.30.

c.

if d decision is delayed til d clerk confirms there is an 18 gallon tank on d rental car,d decision remains d same.D expected m1tary value increases 2 $29.6886 but since d decision hs nt changed dis in4m8on hs no value.


  1. project 14.2 − on-orbit moni2ring

altern8ve ways R being evalu8d 2 per4m spacecraft on-orbit moni2ring.Currently d af per4ms d function with junior officers.D enlisted 4ce altern8ve involves d replacement of half d officers with enlisted personnel.D au2m8d altern8ve involves reducing d crew 4ce by increasing d reliance on expert systems.Both altern8ves involve increased contracted technical support.D officer/enlisted altern8ve involves a hardware & software upgrade.D expert systems altern8ve involves d development of d expert systems software.D following constant year cost data is provided: (assume a time horizon of 10 years & an interest  r8 of 5%.)

  • d current officer costs R $5m/year.

d officer/enlisted costs would b $4m/year.However,upgrades 2 data & hardware would cost $2m 4 d 1st 3 years.

d expert systems costs would b $3m/year.However,d expert system development will cost $3m 4 d 1st 4 years.

use decision tree 2 calcul8 d cost of each altern8ve & 2 determine d preferred altern8ve.

  1. suppose each variable on our problem can vary as follows:
  • time horizon: 8 2 12 years

interest r8: 3 2 8%

officer/enlisted hardware & software upgrades: $1 2 3 m/year

officer/enlisted hardware & software upgrades development period: 2 2 4 yrs

expert system development costs: $2 2 4m/year

expert system development period: 3 2 5 yrs

examine d impact of each variable on d problem.4 those variables whose change produces a change in d optimal decision,@ ? Value of dat variable does d decision change?

ans: 

a.

d following tree depicts d basic decision.D pv function within excel is used 2 calcul8 d costs as follows:

annual_cost:

junior officer

=pv(5,0.05,10)

mixed crew

=pv(4,0.05,10)

au2m8d

=pv(3,0.05,10)

investment_cost:

junior officer

=pv(2,0.05,3)

mixed crew

=pv(3,0.05,4)

au2m8d

au2m8d

based on dis model,d decision preferred according 2 d expected m1tary value decision rule is d expert system choice.

b.

2 examine each variable in dis problem d pertinent data is placed in a table & referred 2 by d present value functions.Dis approach enables 1 2 employ d sensitivity analysis table feature in excel or 2 simple change d variables 1 @ a time.D variables changed & their range of change R:


time horizon: 8 2 12 years


interest r8: 3 2 8%


officer/enlisted hardware & software upgrades: $1 2 3 m/year


officer/enlisted hardware & software upgrades development period: 2 2 4 yrs


expert system development costs: $2 2 4m/year


expert system development period: 3 2 5 yrs


d results R summarized in d following table.Ol results R in terms of expected costs of d program.

variable*

lower bound

upper bound

notes:

time horizon

30.0275

37.2276

no change

interest r8

36.7419

30.0666

no change

mixed crew costs

33.6102

(mixed crew)

33.8031

(expert system)

@ $1.078m,change back 2 expert systems

mixed crew dev.Time

33.8031

33.8031

no change

expert system costs

30.2571

(expert system)

36.3334

(mixed crew)

@ $3.714,change 2 mixed crew option

expert system dev.Time

31.3349

36.1536

no change

* optimal choices R expert system unless otherwise noted.

* optimal choices R expert system unless otherwise noted.

d point @ which d decision changes is easily found using d risk solver plat4m (rsp).Set d objective cell & variable cell 2 d variable cell 4 which UR trying 2 find d break point.Add a constraint keeping d decision tree decision @ its current value & hit solve.


in decision analysis,gud decisions

  1. always result in gud outcomes
    1. always result in bad outcomes
    2. guarantee gud outcomes
    3. may b reached wen d model accounts 4 un4seeable circumstances

answer:  d

  1. in decision-making,luck
    1. often plays a role in determining whether gud or bad outcomes occur
    2. can b quantified
    3. cannot b quantified
    4. can b ignored

answer:  a

  1. an altern8ve
    1. is a course of action intended 2 solve a problem
    2. is always feasible
    3. is never feasible
    4. is realistic

answer:  a

  1. a st8 of nature
    1. is observed
    2. is under control of a decision maker
    3. is known with certainty
    4. is estim8d using a decision model of choice

answer:  a

  1. decision models R applicable wen
    1. there R multiple altern8ves
    2. there R multiple st8s of nature
    3. there is only 1 altern8ve
    4. there is only 1 st8 of nature

answer:  a

  1. business decision models can b c8gorized as
    1. decision-making under uncertainty
    2. decision-making under risk
    3. decision making under certainty
    4. (a) & (b) only

answer:  d


  1. whichRcharacteristicsofdecision-makingunderuncertainty?

    1. d probability of possible future events is unknown
    2. decision-makers must rely on probabilities in evalu8ng outcomes
    3. ol process parameters have known values
    4. some process parameters have known values

answer:  a

  1. dmaximinapproach2decision-making

    1. maximizes d minimum return
    2. maximizes d maximum return
    3. maximizes d minimum regret
    4. minimizes d minimum regret

answer:  a

  1. which1oftheseisntusedindecision-makingunderrisk?

    1. minimax regret
    2. evpi
    3. emv
    4. decision trees

answer:  a

  1. dexpectedm1taryvaluecriterion(emv)isddecision-makingapproachused

    1. in decision-making under risk
    2. in decision-making under uncertainty
    3. in decision-making under certainty
    4. ol of d above

answer:  a

  1. ddifferencebtwnexpectedpayoffundercertainty&expectedpayoffunderriskis

    1. evpi
    2. emv
    3. expected regret value
    4. n1 of d above

answer:  a

  1. suppose dat evpi=0.Dis means dat
    1. d decision problem involves no risk
    2. d decision problem is certain
    3. d payoff under risk iz zero
    4. d decision problem is incorrectly 4mul8d

answer:  a


  1. sensitivityanalysisismostusefulin

    1. decision-making under risk
    2. decision-making under uncertainty
    3. decision-making under certainty
    4. ol of d above

answer:  a

  1. suppose dat d payoffs 4 an altern8ve with 3 st8s of nature R: 10,20,& 30.D probabilities of these st8s of nature R 0.2,0.3,& 0.5,respectively.D expected payoff 4 d altern8ve is equal 2
    1. 23
    2. 30
    3. 60
    4. 20

answer:  a

  1. suppose dat d regrets 4 an altern8ve with 3 st8s of nature R: 20,10,& 0.D probabilities of these st8s of nature R 0.2,0.3,& 0.5,respectively.D expected regret 4 d altern8ve is equal 2
    1. 7
    2. 20
    3. 10
    4. 30

answer:  a

  1. in a graphical represent8on of decision trees d decision nodes
    R represented by
    1. squares
    2. circles
    3. solid dots
    4. ovals

answer:  a

  1. in a graphical represent8on of decision trees d event nodes R represented by
    1. squares
    2. circles
    3. solid dots
    4. ovals

answer:  b