University of Toronto Mississauga
STA380H5
Computational Statistics
What was the average?
Not reported
No student has contributed a result for this offering yet.
How is it graded?
5 components
From the 2024 syllabus. 5 graded components.
How confident is this?
Unknown
A small number of terms, so read it as a range.
From the calendar
Official source · University of Toronto MississaugaComputational methods play a central role in modern statistics and machine learning. This course aims to give an overview of some of the computational techniques that are useful in statistics. Topics include methods of generating random variables, Monte Carlo integration and variance reduction, Monte Carlo methods in inference, bootstrap and jackknife, resampling application, permutation tests, probability density estimation, and optimization.
- Exclusions
- STA312H5STA410H1
- Contact hours
- 36 lecture · 12 tutorial
- Total scheduled hours for the course, not per week.
Where the marks come from
2024 syllabusExtracted from a published 2024 syllabus by deterministic parser. Components that could not be labelled are shown unresolved rather than folded into a neighbouring category.
How well we know this course
2022–2024Pyko’s archive holds 2 documents for STA380H5, across 2 years between 2022 and 2024.
- 1
- Final exams
- 1
- Syllabi
Counts, not a library. Pyko does not host or distribute course files, and this page is not an offer to supply one — the archive is what lets these pages describe how a course is assessed.
What we don’t have yet
Source ledger
Report an error →| Claim | Source | Captured | Status |
|---|---|---|---|
| Course description, prerequisites, exclusions, contact hours | University of Toronto Mississauga | 2026-07-25 | public fact |
| Assessment weighting | Course syllabus, 2024 | 2026-07-25 | summary permitted |
| 2 archived documents, 2022-2024 | Pyko archive | 2026-07-25 | index only |
Page last verified 2026-07-25. A claim whose source moves is withdrawn before it goes stale.
Around this course
Everything above is history. Yours isn’t written yet.
Add STA380H5 and the 2024 weighting loads with it — Pyko tracks what you've earned and solves for what the final has to be.
Pyko is an independent student platform. It is not affiliated with, endorsed by, or operated by the University of Toronto. Course names and codes are used descriptively to identify courses.