Decision Analysis for Civil and Environmental Engineers
Fee may apply
Current challenges in selecting an appropriate construction or development site, alternate designs, or retrofit strategies based on economic, environmental, and social factors can be best addressed through applications of decision science. Fundamentals of decision theory, including development of decision trees with discrete and continuous random variables, modeling the uncertainty of various components of the decision tree through probability models, expected value decision making, utility theory, expected utility decision making, value of information, and elementary multi-attribute decision making will be covered in the class. Examples will cover many areas of civil and environmental engineering problems. Class final project is based on student’s personal area of interest.
What you will learn
- What are the components of simple and complex decision-making
- How to model the uncertainties in potential future outcomes of specific decisions
- How to develop utility functions
- The fundamentals of single and multi-utility decision making
Students taking this course must have taken a course in probability theory, such as CEE203 or equivalent.
- Probability modeling of states of nature
- Basics of decision theory, including decision trees
- Bayesian analysis
- Multi-attribute decisions
|Dates:||April 1 - June 5, 2019|
|Times:||9:30 am - 11:20 am|
Provides Stanford University credit that may later be applied towards a graduate degree or certificate. Includes access to online course materials and videos for the duration of the academic quarter. Starting Autumn 2016 there is a $100 fee per course for courses dropped before the drop deadline. Click here for more information about our Registration Policies.
*Note: All amounts shown are in USD
NotesEnrollment Dates: February 10 to March 18, 2019
This course may not currently be available to learners in some states and territories.