Module 6 Modeling Uncertainty
Ch 7 Probability Basics
I assume that you all have a basic understanding of Chapter 7
Probability Basics. Mostly, I would need you to refresh yourself
about general meanings of discrete and continuous probability
distributio
YORK UNIVERSITY
Toronto, Ontario
ADMS3300 3.0
Decision Analysis
Fall 2008
Assignment # 1
Submitted to
Dr. Mustafa Karakul
Date Submitted: _
Personal/Group Work Statement
We/I, the undersigned:
warrant that the work submitted herein is our/my work and not
Ch 13 Risk Attitudes
The risk and return trade-offs?
How to model a decision makers preferences?
Using Utilities to Model Risk Attitudes
Risk Averse, Risk Lover, Risk Neutral
Expected Utility, Certainty Equivalents and Risk Premiums
Utility Function Asses
1
AP/ADMS 3300 M
Decision Analysis Winter 2010
ASSIGNMENT # 1
Rules:
1.
2.
3.
4.
All calculations are to be completed to the 4 decimal place, unless told
otherwise. Show your Work.
Must use provided cover page. (page 2 of this document). All group
members
AP/ADMS 3300 A and B
Decision Analysis Fall 2009
ASSIGNMENT # 2
Rules:
1.
2.
3.
All calculations are to be completed to the 4 decimal place, unless told
otherwise. Show your Work.
Must use provided cover page. (page 2 of this document). All group
members
Solutions to Suggested Problems from Chapter 16
16.6. a. The assessments indicate that kX = 0.48 and kY = 0.67. The two-attribute utility
function is U(x, y) = 0.48UX(x) + 0.67UY(y) - 0.15UX(x)UY(y).
b. The two attributes would appear to be substitutes. T
AP/ADMS 3300 A and B Decision Analysis Winter 2011 ASSIGNMENT # 2 Rules:
1. 2. 3. All calculations are to be completed as specified in each question. Show your Work. Must use provided cover page. (page 2 of this document). All group members must sign the
Solutions to Suggested Problems from Ch 16
16.6. a. The assessments indicate that kX = 0.48 and kY = 0.67. The two-attribute utility function is U(x, y)
= 0.48UX(x) + 0.67UY(y) - 0.15UX(x)UY(y).
b. The two attributes would appear to be substitutes. That i
AP/ADMS 3330
Fall 2010
Assignment #1
Section D Due 4:00 pm on Tuesday, 23 November 2010
Section E Due 4:00 pm on Wednesday, 24 November 2010
You may only submit in your own section.
Assignment Instructions (please read carefully)
1. While we encourage stu
AP/ADMS 3300 A and B
Decision Analysis Fall 2009
ASSIGNMENT # 1
Rules:
1.
2.
3.
4.
5.
6.
All calculations are to be completed to the 4 decimal place, unless told
otherwise. Show your Work.
Must use provided cover page. (page 2 of this document). All group
Solutions to Suggested Problems (and a few extra solutions to some questions) from
Chapter 3
(please compare your solutions with theses and feel free to ask the questions you may have!)
3.4. It is reasonable in this situation to assume that the banks obje
Solutions to Suggested Problems from Chapter 2
( Please compare your solutions with these, and feel free to ask me any questions you may have, )
2.1. a.
Some objectives might be to minimize cost, maximize safety, maximize comfort, maximize reliability,
ma
Who am I?
Dr. Mustafa Karakul, Associate Professor of Management Science
AK/ADMS 3300 Decision Analysis
PhD in Operations Management, UofT, Rotman School of Management
BSc and MSc in Industrial Engineering, Bilkent University, Ankara, TR
Teaching at Atkin
Solutions to Suggested Problems from Ch 16
16.6. a. The assessments indicate that kX = 0.48 and kY = 0.67. The two-attribute utility function is U(x, y)
= 0.48UX(x) + 0.67UY(y) - 0.15UX(x)UY(y).
b. The two attributes would appear to be substitutes. That i
Solutions to Suggested Problems and More Ch 8
(Please do these questions and ask me the questions you may have!)
8.6. Your assessments may vary considerably. However, you should be reasonable and indicate in some
way that some effort went into the assessm
Solution to Home Work 5 Remaining problems
12.6. a. Of course, different people will have different feelings on this one. Personally, I would prefer that
the doctor wait to inform me until after the other tests have been performed. (This may not be possib
Question 1
Let
Evil Stats
1 = San Diego
2 = Houston
3 = Tulsa
4 = St. Louis
5 = Portland
6 = Seattle
7 = Denver
8 = Kansas City
Let
Pij = the number of panels shipped from source i to destination j
Bi = 1 if plant i is built, = 0 otherwise (i = 3, 4, 5)
M
Formula sheet (you might not need all formulas to solve this midterm)
P( A B) = P( A) + P( B) P( AB)
P( A) = P( AB) + P( AB )
P( A | B) =
P( AB)
P(B)
P( A | B) = 1 P( A | B)
EVPI =| EMV(Info) EMV( NoInfo |
)
Bayes Theorem:
P(B | A) =
P( A B)P(B)
P( A B)P(
AP/ADMS 3300 M
Decision Analysis Winter 2010
ASSIGNMENT # 2
Rules:
1.
2.
3.
All calculations are to be completed as specified in each question. Show
your Work.
Must use provided cover page. (page 2 of this document). All group
members must sign the cover
Probability: A Subjective Interpretation
Module 5 - Ch 8 Subjective Probability - Outline
Subjective Probability. What is it? Why do we need it?
Assessing Subjective Probabilities
n
n
q
Assessing Discrete Probabilities
n
n
n
q
n
q
q
n
q
q
Using Continuous
QUESTION #1
PART A:
(a)
EMV (launch) =0.2385+0.5473+0.23 (-41) =$49.54M
EMV (not launch) =$29.5M
Since the EMV of launch the product is larger than the EMV of not launch it, therefore
the product should be launched.
(b)
EVwIF=0.2385+0.5473+0.2329.5=$65.75
Solutions to Suggested Problems (and then some) from Chapter 4
4.3. A variety of reasonable answers exist. For example, it could be argued that the least Liedtke should
accept is $4.63 billion, the expected value of his Counteroffer $5 billion alternative
Week 1 - Review
What is Decision Analysis?
Decision Analysis Process
Elements of Decision Problems
Values and Objectives
Decisions to Make
Uncertain Events
Consequences
Time Value of Money A special kind of trade-off
1
What you were supposed to do!
Before
Question I, (20 marks.)
Given the. linear program
Min 3X 4V
ST -.\+-z'
_ g E»
X+2Y :12
2C+\ _r 16
PLY : O
(a) \Vritc the problem in standard form.
(b) Solve. the problem using the graphical solution procedure.
(a) (C) Find the dual prices
IJJ (d) What ar
Chapter 12
Making Hard Decisions
R. T. Clemen, T. Reilly
Value of Information
Draft: Version 1
Making Hard Decisions
R. T. Clemen, T. Reilly
Chapter 12 Value of Information
Lecture Notes by: J.R. van Dorp and T.A. Mazzuchi http:/www.seas.gwu.edu/~dorpjr/
Problem 2.10- Excel Solution
Making Hard Decisions with DecisionTools by Robert T. Clemen & Terence Reilly
NPV=
$2,003.90
IRR=
19.2%
InterestRate
12%
CashFlows:
Year1 ($12,000.00)
Year2
$5,000.00
Year3
$5,000.00
Year4 ($2,000.00)
Year5
$6,000.00
Year6
$6,
Problem 2.9- Excel Solution
Making Hard Decisions with DecisionTools by Robert T. Clemen & Terence Reilly
$158.78
Clickhere
toviewthe
equations.
InterestRate
13%
CashFlows:
Year0
#
Year1 $1,500.00
Year2 $1,700.00
Clickhere
toreturnto
thevalues.
NPV=
ence
Problem 2.11- Excel Solution
Making Hard Decisions with DecisionTools by Robert T. Clemen & Terence Reilly
NPVat0.83%
$23.71
NPV for annual interest rate
of 10%.
NPVat1.67%
($28.44)
NPV for annual interest rate
of 20%.
IRR=
1.20%
InterestRate(yearly)
Cash
YORK UNIVERSITY
School of Administrative Studies
Fall 2015, AP/ADMS 3300 3.0, Decision Analysis
Section A, Mondays 4:00 - 7:00pm, ACE 009
Section B, Mondays 7:00 - 10:00pm, ACE 009
Course Director: Dr. Mustafa Karakul
Office: Atkinson Bldg. 2nd Fl. 260A
E
PracticeProblem#1
PracticeProblem#2
SampleMCQs
Suppose your utility function is exponential U(x) = 1 e-x/1210 and you face the following
gamble:
Win $1540.30 with probability 0.5
Win $888.12 with probability 0.3
Lose $1279.93 with probability 0.2
1) The e