Due dates of the exams will not move, however the timeline of topics and smaller assignments might be updated throughout the semester.
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Lesson |
Reading |
Slides |
Video |
Lab |
AE |
Assessment |
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Week 01 |
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| Thurs, Aug 27 |
Introduction |
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Navigating Canvas |
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Welcome to Linear Models |
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Navigating the website |
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Week 02 |
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| Tues, Sep 1 |
Meet the toolkit |
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Lab 01: Welcome to R + LaTeX! |
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| Thurs, Sep 3 |
Before You Fit A Model |
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History of Linear Models |
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Matrix Form Linear Models |
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Least Squares (Geometric Interpretation) |
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Deriving the Hat Matrix |
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Week 03 |
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| Tues, Sep 8 |
Matrix Review |
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The hat matrix: Geometric proof |
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Simple equation: The intercept only model |
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| Thur, Sep 10 |
Properties of Random Matrices |
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Law of Iterated Expectation |
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Gauss-Markov Theorem (Part 1) |
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Week 04 |
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| Tues, Sep 15 |
Calculating a conditional expected value |
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What is constant? What is random? |
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Calculating the variance of the least squares estimator |
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Gauss-Markov Theorem, Part 2 |
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| Thurs, Sep 17 |
Lab 02: Least Squares |
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Week 05 |
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| Tues, Sep 22 |
RSS |
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Goodness of Fit |
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Hypothesis testing |
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| Thurs, Sep 24 |
Finding an Unbiased Linear Estimator [Appex 05 solution] |
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More on BLUE [Appex 05 solution] |
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More about the Hat Matrix |
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F-tests in R |
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Interpretations |
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Week 06 |
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| Tues, Sep 29 |
F-tests in R Walk through |
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Confidence Intervals for Regression Coefficients |
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Confidence Interval Application |
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| Thurs, Oct 1 |
Bootstrap Confidence Intervals (Part 1) |
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Bootstrap Confidence Intervals (Part 2) |
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Bootstrap Confidence Intervals (Part 3) |
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Bootstrap Confidence Intervals (Part 4) |
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Week 07 |
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| Tues, Oct 6 |
Content Assessments Update |
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Calculating Confidence Intervals Walk Through |
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Bootstrap Confidence Intervals Walk Through |
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Putting it all together |
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| Thurs, Oct 8 |
Lab 03: Multiple Linear Regression Inference |
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Week 08 |
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| Tues, Oct 13 |
More on Confidence Intervals |
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Confidence Interval Simulation |
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| Thurs, Oct 15 |
Indicator Variables |
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Predictions |
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Confidence Intervals for Mean Response |
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Prediction Intervals (Part 1) |
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Prediction Intervals (Part 2) |
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Week 09 |
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| Tues, Oct 20 |
Expectation of Prediction |
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Variance of Prediction |
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What can go wrong with prediction? |
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Comparing Prediction Models |
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| Thurs, Oct 22 |
The Mathematical Model to Quantify Contact Tracing Efficacy |
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R Package and Shiny Application Overview |
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Shiny Application Demo |
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Thinking about Schools Reopening From a Causal Perspective with Emily Oster |
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Week 10 |
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| Tues, Oct 27 |
Calculating Prediction Intervals |
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Calculating Prediction Intervals by Hand |
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Mallow's Cp Calculation |
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Checking Assumptions (Constant Variance) |
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| Thurs, Oct 29 |
Non-constant variance examples |
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Checking Assumptions (Normality) |
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Checking Assumptions (Correlated Errors) |
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Checking Assumptions (Linearity) |
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Week 11 |
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| Tues, Nov 3 |
Q-Q plots and Polynomial Regression |
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Leverage |
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Outliers |
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Studentized Residuals |
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Influential Points |
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| Thurs, Nov 5 |
Unusual observations walk through |
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Lab 04 |
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Week 12 |
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| Tues, Nov 9 |
Generalized Least Squares (Part 1) |
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Generalized Least Squares (Part 2) |
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Generalized Least Squares (Part 3) |
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Generalized Least Squares (Part 4) |
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| Thurs, Nov 11 |
Generalized Least Squares Derivation |
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Weighted Least Squares |
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Week 13 |
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| Tues, Nov 17 |
GLS Walk Through |
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Robust Regression |
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| Thurs, Nov 19 |
Robust Regression Walk Through |
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Week 14 |
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| Tues, Nov 24 |
Creating Reports in RMarkdown (Part 1) |
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Creating Reports in RMarkdown (Part 2) |
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Creating Reports in RMarkdown (Part 3) |
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Creating Reports in RMarkdown (Part 4) |
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Week 15 |
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| Tues, Dec 1 |
Visualizing Linear Models |
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| Thurs, Dec 3 |
Wrap-up |
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