**Click on the text like “Week 1: Sep 02 – Sep 06” to expand or collapse the items we covered in that week.**

I will fill in more detail and provide links to lecture notes and labs as we go along. Items for future dates are tentative and subject to change.

**In class**, we will work on:- Overview of course (slides): pdf
- Warmup activity in groups: pdf
- Brief reminder of commands for simple linear regression in R: pdf
- Matrix notation for multiple regression (See Chapter 1 of ISLR and https://en.wikipedia.org/wiki/Linear_regression#Introduction)
- Get set up with GitHub:
- Video overview: https://www.youtube.com/watch?v=YxZ8J2rqhEM
- pdf with detailed instructions: pdf
- On step 1, please enter your name and GitHub user name in this form: https://forms.gle/tmv25zoB4EPipa7f8

**After class**, please:- Sign up for our class on Piazza: https://piazza.com/mtholyoke/fall2019/stat340
- Fill out this poll about when my office hours should be held: http://whenisgood.net/8jeinxd
- Finish getting RStudio set up with GitHub if you didn’t get there in class - ask if you have any questions!
- Review the handout about simple linear regression
- Start reading Chapter 1, and Sections 2.1, 2.2.1, 2.2.2, 3.1, 3.2, and 3.3 of ISLR. This material should be mostly familiar, but we will discuss this material over the first two weeks or so of class.
- Ask any questions on piazza!

**In class**, we will work on:**After class**, please:- Continue reading Chapter 1, and Sections 2.1, 2.2.1, 2.2.2, 3.1, 3.2, and 3.3 of ISLR.
- Start on Homework 1, due Friday Sep 13; assigned on GitHub.

**In class**, we will work on:**After class**, please:- Continue reading Chapter 1, and Sections 2.1, 2.2.1, 2.2.2, 3.1, 3.2, and 3.3 of ISLR.

**In class**, we will work on:**After class**, please:- Work on HW1, due Friday Sep 13

**In class**, we will work on:**After class**, please:- Do HW2, due Friday Sep 20, to be assigned on GitHub some time Saturday

**In class**, we will work on:**After class**, please:- Read Sections 5.1.1 through 5.1.4 of ISLR
- Work on HW2, due Friday Sep 20

**In class**, we will work on:- For loops in R: pdf
- Cross-validation: pdf
- Time for Lab 1 (individual GitHub repositories) and Lab 2 (https://github.com/mhc-stat340-f2019-sec01/Lab02)

**After class**, please:- Work on HW2, due Friday Sep 20

**In class**, we will work on:- Pairs Plots: pdf
- Work on labs

**After class**, please:

**In class**, we will work on:**After class**, please:- Finish Lab 2
- Study for quiz on Wed

**In class**, we will work on:- Quiz
- Review Lab 2. My answers are posted at https://github.com/mhc-stat340-f2019-sec01/Lab02
- QQ Plots: pdf

**After class**, please:

**In class**, we will work on:- Transformations: pdf

**After class**, please:

**In class**, we will work on:- Quiz
- Review Lab 3. My solutions are at https://github.com/mhc-stat340-f2019-sec01/Lab03-solutions
- KNN for classification:

**After class**, please:

**In class**, we will work on:- Measuring error rates and cross-validation for classification (continuing lecture notes from last class)
- Start handout from last class

**After class**, please:

**In class**, we will work on:- Finish handout posted Wed Oct 2
- Lab on KNN for classification: https://github.com/mhc-stat340-f2019-sec01/Lab04

**After class**, please:

**In class**, we will work on:- Midterm

**After class**, please:

**In class**, we will work on:- Answer to problem 2 (a) and (b) on HW

**After class**, please:

**In class**, we will work on:- Finish handout on logistic regression with multiple explanatory variables from last class.
- Estimation for logistic regression: pdf

**After class**, please:

**In class**, we will work on:- Measures of classification skill: pdf
- Work on Lab 5

**After class**, please:- Lab 5 due Fri Oct 25
- HW 5 due Wed Oct 30

**In class**, we will work on:- Penalized estimation
- hand out: pdf
- we also defined the LASSO regression estimator as minimizing RSS + \(\lambda \sum_{j = 1}^p \vert\beta_j\vert\), and ridge regression as minimizing RSS + \(\lambda \sum_{j=1}^p \beta_j^2\)

- Penalized estimation
**After class**, please:- Work on HW due Wed Oct 30

**In class**, we will work on:**After class**, please:

**In class**, we will work on:- Quiz
- Overview of where we’ve been and where we’re going: pdf

**After class**, please

**In class**, we will work on:**After class**, please:

**In class**, we will work on:**After class**, please:- Prepare for quiz on Friday

**In class**, we will work on:- Finish bagging, feature subsets, and random forests

**After class**, please:

**In class**, we will work on:**After class**, please:

**In class**, we will work on:**After class**, please:

**In class**, we will work on:**After class**, please:

**In class**, we will work on:**After class**, please:

**In class**, we will work on:**After class**, please:

**In class**, we will work on:**After class**, please:

**No Class**: Thanksgiving Break. Safe travels!

**No Class**: Thanksgiving Break. Safe travels!

**In class**, we will work on:**After class**, please:

**In class**, we will work on:**Evan is away at a conference.**- Time to work on your projects in groups.

**After class**, please:

**In class**, we will work on:**Evan is away at a conference.**- Time to work on your projects in groups.

**After class**, please:

**In class**, we will work on:**After class**, please:

We will not have a final exam in this class.