SYST
573/OR 681
Decision
and Risk Analysis
Spring
2008
Instructor: Dr. Andrew Loerch
Office: Science and Tech II, Room 119
Phone: (703)
993-1657 (O)
E-mail:
aloerch@gmu.edu
Office
Hours: Before or after class, or by appointment
Text: Making Hard Decisions with DecisionTools,
by Clemen and Reilly
Software: Logical
Decisions for Windows, plus the software that comes with the text
Description: The intent of this course is to provide a modern perspective on analytical methodologies to support decision making. Decision analysis offers a set of structured procedures that assist decision-makers in structuring decision problems and developing creative decision options, quantifying their uncertainty (this includes combining available statistics with expert judgments, and their own beliefs to arrive at estimates of the probabilities of various outcomes), quantifying their preferences (this includes structuring their value tradeoffs and examining their attitude towards risk), combining their uncertainty and preferences to arrive at “good” decisions. This course provides an introductory treatment of decision analysis. The intended participants are students who want to learn more about decision making under uncertainty and tools that can be used to support it. Other information.
Topic Reading
Assignment*
Introduction Read
Chapt.1
Review of Probability Read
Chapt. 7 pg 282, # 7.8, 7.9, 7.15, 7.16,
7.19 Prob
HW
Value
Focused Thinking Read
Handout and Chapt. 6 Keeney
Article Affinity Diagram
Value
Functions and Weight Elicitation AHP Read Chapt. 4 pg 142-143,
614-621 (Assessing Weights) Single Dim
VF HW
Hierarchical Value function HW
Decisions
Under Uncertainty Read
Chapt. 3 Decision tree HW
Influence
Diagrams Read
Chapt. 3
Utility
Functions Multiattribute
Utilility Read
Chapt. 15, 16 Utility
HW1
Sensitivity
Analysis Read
Chapt. 5 Utility and Sensitivity
* Homework sets will be assigned on a
weekly basis from appropriate problems in the textbook and on handouts.
Grading: Midterm 30%
Final Exam 30%
Project 30%
Class & Homework 10%
100%