| Week | Mon | Wed | Module | Friday discussion | Due | Notes |
|---|---|---|---|---|---|---|
| Week 0 | Sep 23 | Intro: why statistics? | Sep 25: Intro to R crash course, part 1 (for those new to R) | — | First class Wed Sep 23; R crash course begins Friday Sep 25 | |
| Week 1 | Sep 28 | Sep 30 | Statistics Fundamentals | Oct 2: Intro to R crash course, part 2 (continued, incl. loops & apply functions) | PS 1: Statistics Fundamentals (Oct 5) | One deck across Mon + Wed, a rapid-fire review of intro statistics: describing data and uncertainty, then the toolkit of tests and effect sizes. |
| Week 2 | Oct 5 | Oct 7 | Linear Regression | Oct 9: How to: data wrangling (data.table) | PS 2: Linear Regression (Oct 12) | |
| Week 3 | Oct 12 | Oct 14 | Generalized Linear Models | Oct 16: How to: data wrangling (tidyverse) | PS 3: GLMs (Oct 19) | |
| Week 4 | Oct 19 | Oct 21 | Non-linear Regression & GAMs | Oct 23: How to: write functions | PS 4: Non-linear & GAMs (Oct 26) | |
| Week 5 | Oct 26 | Oct 28 | Model Selection | Oct 30: No class (instructor travel) | PS 5: Model Selection (Nov 2) | |
| Week 6 | Nov 2 | Nov 4 | Regularization & Cross-Validation | Nov 6: Making publication-ready figures | PS 6: Regularization (Nov 9) | |
| Week 7 | Nov 9 | Nov 11 | PCA & Dimension Reduction | Nov 13: Make your own R package | PS 7: PCA (Nov 16) | No class Wed Nov 11 (Veterans Day) |
| Week 8 | Nov 16 | Nov 18 | Clustering | Nov 20: How to: parallelize / big data in R | PS 8: Clustering (Nov 23) | |
| Week 9 | Nov 23 | Nov 25 | Random Forests & Neural Nets + MANOVA & Transformations | Nov 27: No class (Thanksgiving) | PS 9: Random Forests (Nov 30) | No class Wed Nov 25 or Fri Nov 27 (Thanksgiving) |
| Week 10 | Nov 30 | Dec 2 | SEM & Redundancy Analysis | Dec 4: Bonus: mixed effect models | Final: Micro Paper (Dec 11) | Final due Fri Dec 11, 11:59 PM (end of finals week) |
Schedule
Click a topic to open that module’s page: slides, R code, data, and the problem set, all in one place. Materials for each module post on the Monday it starts.