Instructor: Yi Yang
Lectures: 3 hours/week, Tu, Thu 8:35am-9:55am on Zoom. Live lectures offered on Zoom at official scheduled time (and recorded, the zoom link is on Mycourses)
Office hours: Tu, Thu 10:00am-11:00am using the same Zoom link.
TA: Yi Lian yi.lian@mail.mcgill.ca
TA office hour: Fri 1:30pm-2:30pm (the zoom link is on Mycourses)
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Introduction to Linear Regression Analysis
5th edition, 2012, D. C. Montgomery, E. A. Peck, and G. G. Vining.
Date | Topics | Notes | Reading Assignments |
Lecture 1 | Optimal prediction | Part I | Ch 1 |
Lecture 2 | Regression function | Part I | Ch 2.1 2.2 |
Lecture 3 | KNN | Part I | - |
Lecture 4 | Optimal linear prediction | Part I | - |
Lecture 5 | Plug-in estimation | Part I | - |
Lecture 6 | SLR assumptions | Part I | - |
Lecture 7 | SLR simulation | Part I | - |
Lecture 8 | Least squares estimator | Part I | - |
Lecture 9 | Statistical properties of LS | Part I | - |
Lecture 10 | Estimation of sigma | Part I | - |
Lecture 11 | Confidence intervals for beta | Part I | Ch 2.4 |
Lecture 12 | Confidence intervals simulation | Part I | Ch 2.4 |
Lecture 13 | Hypothesis test and CI | Part I | Ch 2.3 |
Lecture 14 | t-test | Part I | Ch 2.3 |
Lecture 15 | Permutation test and R squared | Part I | Ch 2.6 |
Lecture 16 | Permutation test | Part I | - |
Lecture 17 | F test | Part I | - |
Lecture 18 | Predictive inference | Part I | Ch 2.5 |
Lecture 19 | Multiple linear regression | Part II | Ch 3.1 |
Lecture 20 | Estimation of the model parameters | Part II | Ch 3.2 |
Lecture 21 | MLR t-test | Part II | Ch 3.3 |
Lecture 22 | MLR F-test | Part II | Ch 3.3 |
Lecture 23 | MLR confidence intervals | Part II | Ch 3.4-3.5 |
Lecture 24 | Diagnostics | Part II | Ch 4 |
Lecture 25 | Model selection | Part II | Ch 10 |