Class schedules
This is the working schedule for the course. It is subject to change.
Abbreviation key: OI = OpenIntro Stats textbook, CC = coding challenge, MDSR = Modern Data Science with R
| Month | Day | Topic | Notes | HW Due | Reading | |
|---|---|---|---|---|---|---|
| Sep | Tu, 4 | Intro, motivation | Lec 1 | Kaplan 1 | ||
| Th, 6 | Syllabus | |||||
| Tu, 11 | What is data? | Lec 2 | Kaplan 2, post | |||
| Wed, 12 | Lab 1 - Group Write-Up | |||||
| Th, 13 | discussion | Lab 1 | gaydar critique, orig. paper | |||
| Fri, 14 | Lab 1 - Ind Write-Up | |||||
| Tu, 18 | Data visualization and summary | Lec 3 | Data viz reading list, Kaplan 3 | |||
| Th, 20 | Lab 2 topic | |||||
| Fr, 21 | CC1 | |||||
| Tu, 25 | Language of Models | Lec 4 | Kaplan 6, 7 | |||
| Th, 27 | Linear Regression | Lec 4 w/markup | ||||
| Fri, 28 | Lab 2 | |||||
| Oct | Tu, 2 | Linear Regression | Lec 5 | Kaplan 8-9, OI 7, OI Videos | ||
| Th, 4 | Linear Regression | Lec 6 | OI Videos | |||
| Fri, 5 | Lab 3 | |||||
| Tu, 9 | No Class | |||||
| Th, 11 | Logistic regression | Lec 7 | Kaplan 16, OI 8, OI Video | |||
| Fri, 12 | Lab 4 | |||||
| Tu, 16 | Project | |||||
| Th, 18 | Project | |||||
| Fri, 19 | ||||||
| Tu, 23 | Project | |||||
| Th, 25 | Project | |||||
| Fri, 26 | CC2 | |||||
| Tu, 30 | Project | CC3 | ||||
| Nov | Th, 1 | Project | ||||
| Fri, 2 | ||||||
| Tu, 6 | Project | |||||
| Th, 8 | ||||||
| Fri, 9 | CC4 | |||||
| Mo, 12 | Projects due | |||||
| Tu, 13 | Understanding Uncertainty | Lec 8 | Kaplan 11-13 | |||
| Th, 15 | Understanding Uncertainty | Suppl | ||||
| Fri, 16 | ||||||
| Tu, 20 | Thanksgiving | |||||
| Th, 22 | Thanksgiving | |||||
| Tu, 27 | Understanding Uncertainty | Lec 9, Suppl | Kaplan 14-15 | |||
| Th, 29 | Understanding Uncertainty | Kaplan 14-15 | ||||
| Fri, 30 | Lab 5 | |||||
| Dec | Tu, 4 | Professional Ethics | MDSR 6 | |||
| Th, 6 | Final exam review | |||||
| Fri, 7 | Lab 6 | |||||
| Tu, 11 | Final Exam | |||||
| Fri, 14 |