Course Details

Course Number: 95-760

Decision Making Under Uncertainty

Units: 6

This course provides an introduction to modeling and computational methods used
by policy-makers, managers and analysts to support decision-making. The first half
of the course focuses on deterministic optimization, and covers linear programming,
network optimization and integer programming. The second half of this course
introduces risk and uncertainty, and includes methods to characterize uncertainty
and methods to optimize decisions under uncertainty. Examples are drawn from a
variety of domains where these decision-making methods can provide value for
business and policy, such as transportation, energy, health care, manufacturing,
supply chain management, etc.

The readings, lectures, homework assignments and exams will help you develop
modeling skills, computational skills and analytical skills. Modeling skills involve
translating a problem into a well-defined mathematical framework, using little more
than pen and paper. Computational skills involve solving your model on a computer
program. In this course, all applications will be done in Excel. Analytical skills
involve critically interpreting a model and translating results into insights for

decision-making. All three are important!

Learning Objectives:

1. Become familiar with advanced Excel functions. This helps you get a job.
2. Survey optimization and decision science methods. This helps you hire
consultants intelligently, should you need to.
3. Learn some analytical methods. This helps you solve smaller problems
yourself and develop intuition for more complex problems.
4. Learn how to develop a mathematical model. This helps you think clearly and

precisely, and will give you an edge on the marketplace.


95-796 Statistics for IT Managers 6 Credits

David Choi
Riaz Esmailzadeh
Alexandre Jacquillat
Stephen F. Roehrig
Donald P Taylor