University of Toronto Mississauga
STA314H5
Introduction to Statistical Learning
What was the average?
Not reported
No student has contributed a result for this offering yet.
How is it graded?
50% final
From the Fall 2026 syllabus. 19 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 MississaugaThis course provides an introduction to supervised statistical learning, covering regression and classification methods including linear regression, regularization, non-parametric methods, and tree-based models with an emphasis on R implementation.
- Exclusions
- STA314H1
- Contact hours
- 36 lecture · 12 tutorial
- Total scheduled hours for the course, not per week.
Where the marks come from
Fall 2026 syllabus50% of the grade is decided in the final alone. Steady coursework cannot carry this course on its own.
Extracted from a published Fall 2026 syllabus — verified against the university's own document. Components that could not be labelled are shown unresolved rather than folded into a neighbouring category.
- lowest 1 quiz(s) dropped
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 |
| Grading structure, description and credit weight from the official Fall 2026 syllabus (instructor: S. Volgushev) | Official Fall 2026 course syllabus (University of Toronto Mississauga) | 2026-09-05 | official syllabus |
Page last verified 2026-09-05. A claim whose source moves is withdrawn before it goes stale.
What this opens up
2 courses list STA314H5 as a prerequisiteThe other 1 have no page yet. Listing a course here means it names STA314H5 among its prerequisites — often as one of several ways to satisfy the same requirement, so this is what STA314H5 makes available, not what it alone guarantees.
Around this course
Everything above is history. Yours isn’t written yet.
Add STA314H5 and the Fall 2026 weighting loads with it — Pyko tracks what you've earned and solves for what the final has to be.
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