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Preliminary Course Outline |
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Linear
regression
(chapters from KNNL) |
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Week |
Mon Date |
Topic |
Readings |
|
1 |
Jan 5 |
Course
Overview and Simple Linear Regression |
1.1-1.7 |
|
2 |
Jan 12 |
Normal
Linear Regression;
Method of Maximum Likelihood; |
1.8;
2.1 - 2.6; |
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3 |
Jan 19 |
Parameter
Estimation; Prediction;
|
2.4-2.6;
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|
4 |
Jan 26 |
Diagnostics
and Remedies; Simultaneous
Inferences; |
3.1-3.10;
4.1 - 4.3; |
|
5 |
Feb 2 |
Matrix
Regression; Multiple Regression; |
5.8
- 5.13;
6.1 - 6.7 |
|
6 |
Feb 9 |
Polynomial
Regression;
Qualitative Predictors |
8.1
– 8.5 |
|
7 |
Feb
16 |
Review
and Exam I |
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Time
Series
(chapters from BD) |
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|
Week |
Mon
Date |
Topic |
Readings |
|
1 |
Feb
23 |
Introduction |
1.1-1.6 |
|
2 |
Mar 2 |
Stationary processes |
2.1-2.5 |
|
3 |
Mar
16 |
ARMA |
3.1-3.3 |
|
4 |
Mar
23 |
Estimation |
5.1-5.2 |
|
5 |
Mar 30 |
Forecasting, Model selection |
5.3-5.5 |
|
6 |
Apr 6 |
Spectral methods |
4.1-4.4 |
|
7 |
Apr
13 |
Exam II and Review |
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|
8 |
Apr 20 |
Final
week |
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