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(The following description was used when this course was taught during the Fall 2006 Semester. There will likely be differences in the instructor, textbook, and/or outline the next time the course is taught.)
Instructor: Dr. J. Eric Bickel
Text:
- Instructor notes
- Ron Howard’s Manuscript in Progress
- A Collection of Readings
- Making Hard Decisions, Robert Clemen and Terence Reilly (optional)
Description: Principles and application of techniques in analysis of decision processes involving engineering systems under uncertainty. Areas of utility and information theory as related to quantification of information for decision-making.
Everyone makes decisions, but few people think about how they do it. Yet, psychological research shows that we are prone to many different errors of thought that degrade our decision making ability. In this course we will discuss the principles and fundamental concepts for the normative theory of decision making under uncertainty. We will develop a language, set of theories, and tools to transform complex decisions into ones where the course of action is clear.
This course is intended to provide students with the ability to:
• Bring engineering principals to bear on decision making
• Appreciate the challenges we face when making decisions, particularly decisions that must be made in the face of uncertainty
• Make better decisions in their personal and professional lives
• Play an active role in helping their employers and society make better decisions
• Communicate their choices and recommendations clearly
• Decide on possible career in decision analysis (industry or academia)Prerequisites: ISEN 420 and STAT 601.
Course Topics
- Please note: We may not cover all these topics and the order may be slightly different. We will adjust based on class performance and interest.
- Probability
- Probability as a measure of belief
- Bayes theorem
- Probabilistic relevance
- Axioms of choice under uncertainty
- Utility theory
- Risk preference
- Normative vs descriptive theories of decision making
- Certain equivalents
- Value of perfect information
- Value of imperfect information
- Value of control
- Probabilistic assessment
- Decision diagrams
- Decision trees
- Options
- Probabilistic sensitivity analysis
- Experimentation
- Heuristics and biases in decision making
- Risk Sharing/Scaling
- Life and Death Decision Making
