MATH 3181 — Advanced Probability and Statistics
4 semester hoursUndergraduateLectureusually offered: falltypical days: M/WBostonTraditional
Focuses on probability theory needed to prepare students for research and advanced coursework in the physical and data sciences. Examples and homework problems come from physics, chemistry, biology, computer science, data science, and electrical engineering. Topics include sample spaces; conditional probability and independence; discrete and continuous probability distributions for one and for several random variables; expectation; variance; special distributions including binomial, Poisson, and normal distributions; law of large numbers; and the central limit theorem. Introduces basic statistical theory including estimation of parameters, confidence intervals, and hypothesis testing. This course is proof-based and emphasizes developing students' abilities in mathematical proof writing.
Prerequisites
- MATH 2321 (min D-)
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Fall 2023 | 1 | 8 | 19 | 42% | 11.0 |
| Fall 2024 | 1 | 17 | 19 | 89% | 2.0 |
| Fall 2025 | 1 | 25 | 25 | 100% | 0.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 100% · T 0% · W 66% · Th 0% · F 0%
Common patterns: MW (66% of sections), M (34% of sections) — in patterns, R means Thursday
Professors
Fall
- John Lindhe (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Unlocks
MATH 4581, MATH 4681, MATH 4682
Courses that list MATH 3181 in their prerequisites.
Links
Official catalog (MATH course descriptions) · Student reviews on RateMyHusky · All MATH courses · Plan it at numap.app