DECISION ANALYSIS

Prerequisites & course information

Requisites: STAT/MATH 309 , 409, 431 , STAT 311 , or MATH 331 , graduate/professional standing, member of Engineering Guest Students, or declared in Capstone Certificate in Artificial Intelligence for Engineering Data Analytics Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Summer 2026 Learning Outcomes: 1. Recognize the types of problems that decision analysis can and cannot solve Audience: Both Grad & Undergrad 2. Structure decision problems by identifying the relevant values, objectives, attributes, decisions, uncertainties, consequences, and trade-offs Audience: Both Grad & Undergrad 3. Represent aspects of a decision problem graphically or mathematically Audience: Both Grad & Undergrad 4. Determine the optimal decision, using mathematical techniques as appropriate Audience: Both Grad & Undergrad 5. Identify which parameters have the most impact on the result Audience: Both Grad & Undergrad 6. Explain the results of a decision analysis to managers and other non-specialists Audience: Both Grad & Undergrad 7. Articulate mathematical foundations of decision problems Audience: Graduate Learning Outcomes: 1. Recognize the types of problems that decision analysis can and cannot solve Audience: Both Grad & Undergrad 2. Structure decision problems by identifying the relevant values, objectives, attributes, decisions, uncertainties, consequences, and trade-offs Audience: Both Grad & Undergrad 3. Represent aspects of a decision problem graphically or mathematically Audience: Both Grad & Undergrad 4. Determine the optimal decision, using mathematical techniques as appropriate Audience: Both Grad & Undergrad 5. Identify which parameters have the most impact on the result Audience: Both Grad & Undergrad 6. Explain the results of a decision analysis to managers and other non-specialists Audience: Both Grad & Undergrad 7. Articulate mathematical foundations of decision problems Audience: Graduate