Economic Decisions in Engineering
Classical decision theory, deterministic decision rules, decision trees, influence diagrams, single/multiple stage analysis, sensitivity analysis; subjective probability, heuristics and biases, Bayesian methods, conjugate belief forms, inference, belief assessment methods, value of information, risk analysis; utility theory, risk aversion, conflicting objectives, multi-attribute decision theory, analytic hierarchy process.
IE54600
Credit Hours:
3Learning Objective:
We will learn decision making and rationality, including decision analysis; decision making under uncertainty; various descriptive and prescriptive models from operations research, economics, and business. Applications are drawn from engineering decision-making, public policy, and personal decision-making. Attention is also paid to designing aids to improve decision-making. Use of risk analysis software is optional (not required).Description:
Classical decision theory, deterministic decision rules, decision trees, influence diagrams, single/multiple stage analysis, sensitivity analysis; subjective probability, heuristics and biases, Bayesian methods, conjugate belief forms, inference, belief assessment methods, value of information, risk analysis; utility theory, risk aversion, conflicting objectives, multi-attribute decision theory, analytic hierarchy process.
Topics Covered:
Classical decision theory, deterministic decision rules, decision trees, influence diagrams, single/multiple stage analysis, sensitivity analysis; subjective probability, heuristics and biases, Bayesian methods, conjugate belief forms, inference, belief assessment methods, value of information, legal reasoning, risk analysis; utility theory, risk aversion, conflicting objectives, multi-attribute decision theory, analytic hierarchy process.Prerequisites:
Background in probability theory and familiar with general economics concepts.Applied / Theory:
50 / 50Web Address:
https://mycourses.purdue.edu/Web Content:
Syllabus, grades, lecture notes, homework assignments, solutions.Homework:
Seven to eight homeworks.Projects:
None.Exams:
Two midterms and one final examTextbooks:
Required:
Robert T. Clemen. Making Hard Decisions: An Introduction to Decision Analysis, 2nd edition, Duxbury Press
Reference (not required):
- Ronald A. Howard and Ali E. Abbas. Foundations of Decision Analysis. Pearson Higher Ed, 2015
- Hammond, John S., Ralph L. Keeney, and Howard Raiffa. Smart Choices: A Practical Guide to Making Better Decisions. Harvard Business Review Press, 2015.
- Reference book on probability - Sheldon Ross. First Course in Probability. (Does not matter which edition you use.)