Statistical Computing II
Statistics · 3 hrs Lecture
Offered: Fall Or Winter, Every Second Year
Hard to catch. Runs only every second year, and the calendar doesn't say which, confirm the next offering with the department before counting on it.
STAT-3904 prerequisites
23 courses appear in this chain, up to 6 levels deep. 3 are needed whichever route you take: MATH-1201 → MATH-2105 → MATH-2106
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Where STAT-3904 counts
Counts toward 3 more as one option among several, not as a course you must take:
Read from the departments' own calendar pages, where 50 of 208 programs are only partly machine-readable, so treat these as a minimum rather than the full list. Confirm with an academic advisor.
Description
This course introduces modern techniques of statistical computing for practical analysis of data using the statistical software R. Topics include random number generation, an introduction to resampling methods, classical and Bayesian inference and Monte Carlo methods, methods of finding roots, numerical integration methods, expectation-maximization, and Markov chain Monte Carlo. All statistical principles are illustrated using simulated and real-life data sets.
Requisite courses
STAT-2903 or STAT-3103 [prerequisite(s)]; STAT-3612 or MATH-3612 (must be taken previously or at the same time as this course).
From the 2026-27 undergraduate calendar. Always verify details on WebAdvisor or with an academic advisor before registering.