Note: Due dates of the exams will not move, however the timeline of topics and smaller assignments might be updated throughout the semester.

Date	Lesson	Reading	Slides	Video	Lab	AE	Assessment
	Week 01
Thurs, Aug 27	Introduction
	Navigating Canvas
	Welcome to Statistical Learning
	Navigating the website
	Week 02
Tues, Sep 1	Meet the toolkit
	Lab 01: Welcome to R!
Thurs, Sep 3	Trade-offs: Accuracy and interpretability, bias and variance (Regression)
	Trade-offs: Accuracy and interpretability, bias and variance (Classification)
	Week 03
Tues, Sep 8	Data visualization (Part 1)
	Data visualization (Part 2)
	Tidy Data
Thur, Sep 10	Cross-validation
	Star Wars Application Exercise Solutions
	NC Bike Data Application Exercise Solutions
	Week 04
Tues, Sep 15	Introduction to tidymodels (Part 1)
	Tidymodels (Part 2)
	Tidymodels (Part 3)
	Tidymodels (Part 4)
Thurs, Sep 17	Lab 02: Cross-validation
	Week 05
Tues, Sep 22	Introduction to Linear Regression
	Taking a derivative with respect to a vector
	Deriving the Least Squares Solution
	Multiple Regression
Thurs, Sep 24	Linear Regression in R
	P-values
	Confidence Intervals
	Week 06
Tues, Sep 29	Linear Regression Application Exercise Walk through
	Logistic Regression
	What are the Odds? (Part 1)
	What are the Odds? (Part 2)
	Confidence Interval Application
Thurs, Oct 1	Lab 03: Logistic Regression
	Week 07
Tues, Oct 6
	Odds Ratios and Logistic Regression Walk Through
	Ridge Regression (Part 1)
	Ridge Regression (Part 2)
	Ridge Regression (Part 3)
	Ridge Regression (Part 4)
Thurs, Oct 8	Ridge Regression Derivation
	Lasso & Elastic Net
	Week 08
Tues, Oct 13	More on Confidence Intervals
	Confidence Interval Coding Simulation
Thurs, Oct 15	tidymodels for Ridge, Lasso, and Elastic Net
	Lab 04: Ridge, Lasso, and Elastic Net
	Week 09
Tues, Oct 20	Polynomial Regression and Splines (Part 1)
	Polynomial Regression and Splines (Part 2)
Thurs, Oct 22	The Mathematical Model to Quantify Contact Tracing Efficacy
	R Package and Shiny Application Overview
	Shiny Application Demo
	Thinking about Schools Reopening From a Causal Perspective with Emily Oster
	Week 10
Tues, Oct 27	Thinking more about Ridge and Lasso
	Calculating Effects of Polynomial Models
	Non-linear Models in R
Thurs, Oct 29	Lab 05: Non-linear models
	Week 11
Tues, Nov 3	Decision Trees - Regression Trees
	Building Decision Trees
	Pruning Decision Trees
	Regression Trees Example
Thurs, Nov 5	Decision Tree Walk Through
	Plotting Decision Trees
	Decision Trees - Classification Trees
	Week 12
Tues, Nov 10	Bagging Decision Trees
	Random Forests
	Random Forests in R
Thurs, Nov 12	Boosted Decision Trees (the Algorithm)
	Boosted Decision Trees (Tuning)
	Boosted Decision Trees in R
	Variable Importance
	Week 13
Tues, Nov 17	Lab 06: Ensemble Models
Thurs, Nov 19	Introduction to Communicating Complex Statistics
	Communicating Complex Statistics
	Week 14
Tues, Nov 24	Statistical Communication Leaders
	Week 15
Tues, Dec 1	Honesty in Statistics and Trust in Experts
Thurs, Dec 3	Lab 07: Final Lab