Decision Analysis
Decision Analysis covers modeling techniques including multiattribute utility models, decision trees, and Bayesian models, with emphasis on practical model building.
Summary
Recent recorded grades — Fall 2022: 3.80 GPA, 90.0% A/AB (n=30 letter grades); Spring 2025: 3.62 GPA, 90.0% A/AB (n=40 letter grades); Fall 2025: 3.82 GPA, 94.1% A/AB (n=17 letter grades).
What you’ll be able to do
Recognize the types of problems that decision analysis can and cannot solve
Structure decision problems by identifying the relevant values, objectives, attributes, decisions, uncertainties, consequences, and trade-offs
Represent aspects of a decision problem graphically or mathematically
Determine the optimal decision, using mathematical techniques as appropriate
Identify which parameters have the most impact on the result
Explain the results of a decision analysis to managers and other non-specialists
Articulate mathematical foundations of decision problems
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapSTAT/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
- take one
- graduate/professional standing
- member of Engineering Guest Students
- declared in Capstone Certificate in Artificial Intelligence for Engineering Data Analytics
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Any of
- Any of
- graduate/professional standing
- member of Engineering Guest Students
- declared in Capstone Certificate in Artificial Intelligence for Engineering Data Analytics
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Spring 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
Student experience
the class
Recent recorded grades — Fall 2022: 3.80 GPA, 90.0% A/AB (n=30 letter grades); Spring 2025: 3.62 GPA, 90.0% A/AB (n=40 letter grades); Fall 2025: 3.82 GPA, 94.1% A/AB (n=17 letter grades).
difficulty & workload
No workload feedback recorded.
Topics
- Multiattribute utility models, decision trees, and Bayesian models
- Psychological components of decision making
- Real-world model building applications
Skills
- Model building and elicitation techniques for decision problems
- Communicating decision analysis results to non-specialists
Grades
Latest available · Fall 2025— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Fall 2025
More grade details Grade mix, volume & source data
Not enough comparable courses for Spring 2027 in UW–Madison.
Sources & history
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
Observations at scan time; dates do not imply when a catalog change took effect.
Selected offering source records
No offering records for the selected term.
Raw records
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Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
No records available.
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "Qwen/Qwen3.8-27B",
"model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
"task_version": "17",
"output_id": "c2ac815a4f4e0f786a161660ae32481d2bc88572bdba87bea8e9c3a1d50fc9f6",
"requirements_status": "needs_review",
"dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
"observed_at": "2026-10-14 17:50:09.728220+00:00"
}