Recent recorded grades — Fall 2018: 3.49 GPA, 62.2% A/AB (n=45 letter grades); Fall 2025: 3.59 GPA, 79.3% A/AB (n=29 letter grades).
Theory of Probability I
Theory of Probability I introduces measure theoretic probability and stochastic processes.
Summary
Historical reviews of Hao Shen, Jun Yin: Jun Yin's materials were hard with a weird curve, while Hao Shen was very test-heavy and did not provide proper preparation for exams.
Grade history
↗letter grades
All recorded terms · compare terms & instructors
Prerequisites
Course mapGraduate/professional standing or member of the Pre-Masters Mathematics (Visiting International) Program
- Graduate/professional standing or member of the Pre-Masters Mathematics (Visiting International) Program
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Graduate/professional standing or member of the Pre-Masters Mathematics (Visiting International) Program
Professors
Fall 2026Historical instructors & teaching patterns
Historical reviews for Timo Seppalainen describe him as an exceptional lecturer with clear explanations and proofs. Reviewers rated his teaching highly, noting his clarity in explaining concepts and providing proofs. These positive experiences suggest he is a strong instructor for this course.
DAVID ANDERSON is recorded teaching in Fall 2018, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.
HAO SHEN is recorded teaching in Fall 2023. Recorded history may be incomplete and does not establish a future schedule.
JUN YIN is recorded teaching in Fall 2014. Recorded history may be incomplete and does not establish a future schedule.
PHILIP WOOD is recorded teaching in Fall 2015. Recorded history may be incomplete and does not establish a future schedule.
SEBASTIEN ROCH is recorded teaching in Fall 2013. Recorded history may be incomplete and does not establish a future schedule.
TIMO SEPPALAINEN is recorded teaching in Fall 2014, Fall 2017, Fall 2024. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 44 / 54 | 0 |
| LEC 001 | Classroom Instruction | 4 / 54 | 0 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Meeting source records
Student experience
the class
Historical reviews for Timo Seppalainen describe him as one of the best instructors in the department, noting his super clear explanations of concepts and proofs.
Recent recorded grades — Fall 2023: 3.39 GPA, 65.2% A/AB (n=46 letter grades); Fall 2024: 3.45 GPA, 58.1% A/AB (n=43 letter grades); Fall 2025: 3.59 GPA, 79.3% A/AB (n=29 letter grades).
difficulty & workload
Historical reviews of Hao Shen, Jun Yin: Jun Yin's materials were hard with a weird curve, while Hao Shen was very test-heavy and did not provide proper preparation for exams.
Historical reviews of Philip Wood: Philip Wood set a doable pace for the measure theory intro and chose interesting homework problems, particularly doing a great job with martingales.
Topics
Skills
Grades
Latest available · Fall 2025— not enough history to project Fall 2026.
Grade distribution · % of letter grades
Grades over time
Through Fall 2025
More grade details Grade mix, volume & source data
Not enough comparable courses for Fall 2026 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
Theory of Probability I
Recorded 2026-09-07Theory of Probability I
Recorded 2026-09-07Raw records
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},
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}
]Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesModel outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
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"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
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"output_id": "fab89b5d6fdf0330840008d27c456ed4bc7c0c7ad65b52abab420d0277487495",
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}