MATH 7338 — Probability and Measure

4 semester hoursGraduateLectureusually offered: springtypical days: M/WBostonTraditional

Focuses on measure-theoretic probability theory, with an emphasis on proofs. Introduces measure spaces and the different notions of convergence that are relevant for random variables. Studies the classical limit theorems about sums of independent, identically distributed random variables. Proves both the law of large numbers and central limit theorem under optimal assumptions. Covers the theory of martingales, with applications toward random walks, Markov chains, and continuous time diffusion processes.

Prerequisites

Offering history

TermSectionsEnrolledCapacityFullOpen seats/section
Spring 20241112348%12.0
Spring 2025162326%17.0

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 65% · T 35% · W 65% · Th 35% · F 0%

Common patterns: MW (65% of sections), TR (35% of sections) — in patterns, R means Thursday

Professors

Spring

Percentages are each professor's average share of the season's enrolled students in recent terms.

Links

Official catalog (MATH course descriptions) · Student reviews on RateMyHusky · All MATH courses · Plan it at numap.app