statslab
The “How” of Statistics
Introduction
Content covering statistics, data analysis, and computer programming. Sections are listed on the left.
Instructor
Christian Luhmann
Teaching Assistant
Tracy Radsvick
Schedule
Subject to change, particularly topics scheduled for later in the semester.
| Week | Date | Lecture | Activity |
|---|---|---|---|
| 1 | 09-01 | R & Rstudio, Basic Programming | |
| 2 | 09-08 | Adv. Programming and Handling Data in R | |
| 3 | 09-15 | The Tidyverse, Tibbles | |
| 4 | 09-22 | Christian Out of Town | Review of material to date |
| 5 | 09-29 | Data Wrangling with dplyr | |
| 6 | 10-06 | Sampling | |
| 7 | 10-13 | Plotting with ggplot2 | |
| 8 | 10-20 | rep_sample_n() from scratch |
|
| 9 | 10-27 | Simulating the PRE sampling distribution | |
| 10 | 11-03 | Basic Regression 1/2 | |
| 11 | 11-10 | Basic Regression 2/2 | Generate random data & regress! |
| 12 | 11-17 | Regression Diagnostics | Tests of normality |
| 13 | 11-24 | No Class – Thanksgiving Break | |
| 14 | 12-01 | Class aborted | |
| 15 | 12-08 | Multiple Regression 1/N | |
| Winter Break | |||
| 16 | 1-26 | Refresh | |
| 17 | 2-2 | End-to-end Analysis | |
| 18 | 2-9 | Sampling: p-values ala Lakens | |
| 19 | 2-16 | Interactions | |
| 20 | 2-23 | Linear Mixed Models | |
| 21 | 3-1 | Categorical Variables | |
| 22 | 3-8 | Missingness | |
| 23 | 3-15 | Model comparison | |
| 24 | 3-22 | GLM | |
| 25 | 3-29 | Machine Learning | |
| 26 | 4-5 | Machine Learning | |
| 27 | 4-12 | Bayesian Stuff | |
| 28 | 4-19 | Bayesian Stuff | |
| 29 | 4-26 | Python | |
| 30 | 5-3 | Julia |