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Under construction
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| Semester | Spring 2026 |
|---|---|
| Time & Days | MW 10:30AM - 11:45AM |
| Location | E2-2 1120 |
| Instructor | Kihyuk Hong (E2-2 #3104) |
| Office Hours | TBD |
| [email protected] | |
| TAs | TBD |
| Lecture Note | To be provided |
| Midterm | TBD |
| Final | TBD |
This course reviews general theories of linear regression models with applications to industrial engineering problems. Topics include: Principles of least squares method; multivariate normal distribution and quadratic forms; estimation and hypothesis testing; residual analysis; polynomial regression and ridge regression; regression model building; response surface methodology, etc. Computational aspects of regression analysis are also emphasized.
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This course is proof-based. If you lack mathematical maturity, you may have hard time following it.
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| Components | Note | % |
|---|---|---|
| Participation | Participation | 10% |
| Homework | Proof-based problems and some coding-based problems. | 15% |
| Data Project | Implement regression methods learned in lecture and submit solutions in kaggle environments | 15% |
| Midterm Exam | In-class | 30% |
| Final Exam | In-class | 30% |
There are no required textbooks for this course. Some useful resources:
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Subject to change.
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| No. | Date | Lectures | 📹 | Reading | Homework |
|---|---|---|---|---|---|
| 01 | Mar 04 | Introduction – Course Overview, Statistical Decision Theory | Ch 1 | ||
| 02 | Mar 09 | Linear Regression 1 – Least Squares Method. Projection Perspective. | |||
| 03 | Mar 11 | Linear Regression 2 – SVD perspective. | |||
| 04 | Mar 16 | Linear Regression 3 – Gauss-Markov Theorem. | |||
| 05 | Mar 18 | Linear Regression 4 – | |||
| 06 | Mar 23 | Distributional Properties 1 – | |||
| 07 | Mar 25 | Distributional Properties 2 – | |||
| 08 | Mar 30 | Distributional Properties 3 – | |||
| 09 | Apr 01 | ANOVA 1 – | |||
| 10 | Apr 06 | ANOVA 2 – | |||
| 11 | Apr 08 | Model Selection 1 – Bias Variance Tradeoff | |||
| 12 | Apr 13 | Model Selection 2 – Best Subset Selection, Ridge, Lasso | |||
| 13 | Apr 15 | Review | |||
| Midterm exam | |||||
| 14 | Apr 27 | GLM 1 | |||
| 15 | Apr 29 | GLM 2 | |||
| 16 | May 4 | ||||
| 17 | May 6 | ||||
| 18 | May 11 | ||||
| 19 | May 13 | ||||
| 20 | May 18 | ||||
| 21 | May 20 | ||||
| 22 | May 27 | ||||
| 23 | Jun 1 | ||||
| 24 | Jun 3 | ||||
| 25 | Jun 8 | ||||
| 26 | Jun 10 | Review | |||
| Final exam |