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Linear Models in Applied Statistics STAT 350 (3)
Theory and application of linear regression. Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model diagnostics. Introduction to weighted least squares and generalized linear models. Prerequisite: STAT 260, STAT 285, MATH 251, and one of MATH 232 or MATH 240, all with a minimum grade of C-. Quantitative.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
| D100 |
Faculty , |
Sep 4 – Oct 11, 2024: Tue, 10:30 a.m.–12:20 p.m.
Oct 16 – Dec 3, 2024: Tue, 10:30 a.m.–12:20 p.m. Sep 4 – Dec 3, 2024: Fri, 10:30–11:20 a.m. |
Burnaby Burnaby Burnaby |
| D101 |
Rachel Altman |
Sep 4 – Oct 11, 2024: Tue, 9:30–10:20 a.m.
Oct 16 – Dec 3, 2024: Tue, 9:30–10:20 a.m. |
Burnaby Burnaby |
| D102 |
Rachel Altman |
Sep 4 – Dec 3, 2024: Fri, 11:30 a.m.–12:20 p.m.
|
Burnaby |