Spring 2017 Class Materials
All materials listed here are licensed for reuse under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Lecture Notes
by Elizabeth Purdom and Adityanand Guntuboyina
| # | Title | Chapter (pdf) | Code (html) | Code(Rmd) |
|---|---|---|---|---|
| 01 | Review of probability | html | Rmd | |
| 02 | Comparing Groups and Hypothesis Testing | html | Rmd | |
| 03 | Fitting curves to data | html | Rmd | |
| 04 | Visualizing Multivariate Data | html | Rmd | |
| 05 | Multiple Regression | html | Rmd | |
| 06 | Logistic Regression | html | Rmd | |
| 07 | Regression and Classification Trees | html | Rmd |
Labs
by Boying Gong
| # | Title | Jupyter Link |
|---|---|---|
| 01 | Intro to R | link |
| 02 | Intro to RStudio | link |
| 03 | Density curves, violin plots | link |
| 04 | Permutation tests, t-tests, Bonferonni correction | link |
| 05 | Bootstrap and parametric Confidence Intervals, Linear regression | link |
| 06 | Linear models, plotting, polynomial models | link |
| 07 | Loess and Pairs plots | link |
| 08 | Heatmaps, PCA, brief intro to ggplot | link |
| 09 | More PCA | link |
| 10 | Multiple linear regression models | link |
| 11 | Prediction with linear regression | link |
| 12 | Regression diagnostics and logistic regression | link |
| 13 | Regression and classification trees | link |