CSS 211 Schedule

This is a tentative schedule of which topics I plan to cover. Note that while all lectures will have an interactive component, Fridays are reserved for more hands-on labs—typically involving a CSS-relevant dataset—with active participation encouraged.

Readings are option; “ISLR” refers to “Introduction to Statistical Learning in R” (James et al.), which can be downloaded here.

Week	Day	Date	Topic(s)	Assignments Due	Suggested readings
0	F	09-26	Course Introduction
1	M	09-30	Philosophy of Science in CSS		Introduction to R for Data Science
1	W	10-01	Introduction to R and RStudio
1	F	10-03	R basics [HANDS-ON]	Lab 1
2	M	10-06	Data wrangling		Tidy data (Wickham, 2011)
2	W	10-08	Data wrangling
2	F	10-10	Hands-on data cleaning [HANDS-ON]	Concept quiz
3	M	10-13	Data visualization (principles)		Introduction to Data Visualization in R
3	W	10-15	Data visualization (ggplot)
3	F	10-17	Exploratory data analysis [HANDS-ON]	Lab 2
4	M	10-20	Linear regression		ISLR, 3.1
4	W	10-22	Linear regression
4	F	10-24	Hands-on regression [HANDS-ON]	Concept quiz
5	M	10-27	Multiple regression		ISLR, 3.2
5	W	10-29	Regression: issues
5	F	10-31	Building complex models [HANDS-ON]	Lab 3
6	M	11-03	Logistic regression		ISLR, 4.3
6	W	11-05	Logistic regression		ISLR, 6.2
6	F	11-07	Interpreting logistic models [HANDS-ON]	Concept quiz
7	M	11-10	Midterm review
7	W	11-12	Mixed effects models (Pre-recorded lecture)
7	F	11-14	In-class midterm	Midterm!
8	M	11-17	Final project check-in		Winter, 2013
8	W	11-19	Mixed effects models
8	F	11-21	Mixed effects models	Lab 4
9	M	11-24	Model selection [HANDS-ON]	Concept quiz
9	W	11-26	HOLIDAY (Thanksgiving)
9	F	11-28	HOLIDAY (Thanksgiving)
10	M	12-01	Resampling, best practices, wrap-up
10	W	12-03	Final project presentations (pt. 1)
10	F	12-05	Final project presentations (pt. 2)
11	M	12-08		Final report due