Quantitative Methods

fr O^tg Q"^zS'lr*n 3* ll

Thc EVSI a. is lbund by subtracting thc EMV without samplc inli:r-

mation liom the EMV with sample inl'ormation. b. is always equal to the expected value of peri'ect

intbrmation. c. equals the EMV with sample intbrmation assumiug nt-r

cost fbr the information minus the EMV without sample information.

d. is usually negative. The cl.licicncy ol sample inl'orrnatior.r a. is thc tiVSI/(maxirnum IIMV rvithout SI) cxprcsscd as

a percentage.

tr. is the EVPI/EVSI expressed as a percentagL'. c. w'ould be 1007c ilthe sample information were

perfect.

d. is con.rputed using only the EVPI and the maximum EN4V.

On a decision tree. once the tree has been drawn and the payol{.s and probabilities have been placod on thc trcc.

Discussion Questions and Problems

DtscussroN QUESTToNS AND PROBLEMS 101

the analysis (computing EMVs and sclecting the berst altcrnalivc) a. working hackward (starting on the ilght and moving to

the lefi). b. w'orking tbrward (starting on the left and moving to the

right). c. starting at the top o1'the tree and movin_s down. d. starting at the bottom of the tree and moving up. In assessing utility values, a. the wotsl outcome is given a utility ot' - 1. b. the best outcolllc is -civen a utility ol0. c. the worst outcome is given a utility of 0. d. the best outcome is given a value of - 1. lf a rational person selects an alternative that does not maximize the EMV, we u,ould expect that this alternatire a. minimizes the EMV. b, maximizes the expected utility. c. minimizes the expected utility. d. has zcro utility associatcd rvith cach possible payol)'.

12.

13.

11.

15.

16.

3-l Civer an examplc of a good decision that you made that resulted in a bad outcorne. Also give an example of a bad decision that you made that had a good out- come. Why was each decision gor."ld or bad'?

3-2 Describe what is involved in the decision process. 3-3 What is an alternative? What is a state of nature'l 3-4 Discuss thc dilltrcnces arnong dccision making un-

der certainty, decision making under risk, and deci- sion miiking under unceilainty.

3-6

What techniques arc used to solve dccision-making prohlerns under uncertainty? Which technique re- sults in an optimistic clecision? Which technique re- sults in a pcssirnistic decision'.)

Delrne opportunity loss. What decision-n.rakin-e cri- leria are used with an opporlunity loss table? What inlbrmation should he placed on a decision tree'l

Describe horv you would determinc thc hcst dccision using the EMV criterion with a decision trec.

3-9 What is the clil'l'erence between prior and p()stcriur probabilities?

3- l0 What is the purpose of Bayesian analvsis'l Describe how you rvould usc Baycsian irnalysis in the decision-rnaking process.

3- I I What is the EVSI'I Flor,r, is this computed? 3- l2 How is the elficiency of sample information computed'7 3- l3 What is the overall purpose of utitity theory'l

3-14 Briefly discuss how a utiiity lunction can be as- sessed. What is a slandard gamble, and how rs it used in deterrnining utilitl, values'?

-l- I 5 How is tr utility curve used in selecling the best deci- sion lbr a pa(icular problem?

-l-16 What is a risk seeker? Whal is a risk avoider? How does the utility curve ibr thcse types of dccision makers differ?

( - -l- i 7 -.Kcnneth Brown is the principal owner of Brown Oil,'*--/ Inc. .\lter quitting his university teaching job, Ken has been able to increase his annual salary by a 1ac- tor of over 100. At the present time, Ken is lbrced to consider purchasing some more equiprnent tbr Brown Oil because ol'competition. His alternalives arc shown in thc followine tablc:

FAVORABLE T]NFAVORABLE MARKET MARKET

EQTTTPMENT ($) ($)

3--5

1-6

Sub 100

Oiler J

Texan

300,Ofi)

250,000

75,000

-200,000

- 100"000 - r 8,000

For example, if Ken purchases a Sub 100 and if there is a favorable market, he will realize a profit of $300,000. On the other hand, if the market is

;;E *"r * O-*rn *u, be solved v/ith QM for Windows; -Y means the problem may be solved with Excel QM; and $ *"*, the prohlem may be solved with QM for Windows and/or Excel QM.

Quantitative Analysis for ManagemenL Tweifth Edition, by Barry Render, Ralph M. Stair, Michael E. Hanna, and Trevor S. Hale. Published by Prentice Hall Copyright O 201 5 by Pearson Education, lnc.