504 homepage | Syllabus | Course timeline | Homework | Discussion sections | GoPost | Resources | Projects | Lecture notes
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Note: Suggested reading is given for Weisberg (2005). The order of topics, time spent on each topic, suggested reading and topics themselves may change depending on the pace of the class. The updates will be posted on this page. Please check the page regularly. |
| Week | Day | Date | In class | Topic (reading) | Due |
|---|---|---|---|---|---|
| 1 | M | Jan 7 | Lecture 1 | Introduction (Ch.1) | |
| W | Jan 9 | Lecture 2 | Basic ideas of regression (p.19-26) | ||
| Th | Jan 10 | Lecture 3 | Simple linear regression (p.26-7) | E-mail project ideas | |
| F | Jan 11 | Discussion session | Introduction to R, group project work | Homework 1 | |
| 2 | M | Jan 14 | Lecture 4 | Tests and confidence intervals (p.28-32) | |
| W | Jan 16 | Lecture 5 | Predictions, fitted values, residuals (p.34-7) | ||
| Th | Jan 17 | Lecture 6 | Simple linear regression: Interpretation (Ch.4.2-4.4) | ||
| F | Jan 18 | Discussion session | Hw 2 review, group project work | Homework 2 | |
| 3 | M | Jan 21 | Holiday | ||
| W | Jan 23 | Lecture 7 | Multiple linear regression: Basics (p.47-59) | ||
| Th | Jan 24 | Lecture 8 | Multiple linear regression: Estimation (p.54-60) | Approval of project topic | |
| F | Jan 25 | Discussion session | Group project work | ||
| 4 | M | Jan 28 | Lecture 9 | Multiple linear regression: Testing (p.61-65) | 9am: Project statement |
| W | Jan 30 | Lecture 10 | Multiple linear regression: Interpretation (p.69-91) | ||
| Th | Jan 31 | Lecture 11 | Independent variables and causality. | ||
| F | Feb 1 | Discussion section | Homework 3 review | Homework 3 | |
| 5 | M | Feb 4 | Lecture 12 | Bootstrap | |
| W | Feb 6 | Lecture 13 | Weighted least squares (p.96-110) | ||
| Th | Feb 7 | Lecture 14 | Categorical independent variables (p.122-133),
pairwise comparisons
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| F | Feb 8 | Discussion session | Homework 4 review | Homework 4 | |
| 6 | M | Feb 11 | Midterm exam | ||
| W | Feb 13 | Lecture 15 | Interaction terms | ||
| Th | Feb 14 | Lecture 16 | Violations of assumptions (p.171-177); Nonlinearity: Detection; Non-constant variance (p.177-191) | ||
| F | Feb 15 | Discussion section | Review midterm exam | ||
| 7 | M | Feb 18 | Holiday | ||
| W | Feb 20 | Lecture 17 | Transformations (p.115-120, 147-161) | ||
| Th | Feb 21 | Lecture 18 | Transformations. Diagnostics (data points) | ||
| F | Feb 22 | Discussion section | Homework 5 review | Homework 5 | |
| 8 | M | Feb 25 | Lecture 19 | Leverage points, outliers and Influential cases (p.194-197, p.198-206) | |
| W | Feb 27 | Short project presentation 1 | |||
| Th | Feb 28 | Short project presentation 2 | |||
| F | Feb 29 | Discussion session | Case studies | ||
| 9 | M | Mar 3 | Lecture 20 | Robust regression | |
| W | Mar 5 | Lecture 21 | Model selection I: AIC, BIC, Mallows' Cp (p.211-230) | ||
| Th | Mar 6 | Lecture 22 | Model selection II: Cross-validation (p.221-230) | ||
| F | Mar 7 | Discussion session | Homework discussion; brainstorming | Homework 6 | |
| 10 | M | Mar 10 | Project presentations 1 | ||
| W | Mar 12 | Project presentations 2 | |||
| Th | Mar 13 | Project presentations 3 | |||
| F | Mar 14 | Lecture 23 | Bayesian Model Averaging | ||
| 11 | M | Mar 17 | No in-class exam | 3pm: Project report |