Schedule

Topics

Course Logistics
How old am I?
- Class data Groups 1 - 6 were student groups, Group 7 estimates came from how-old.net and Group 8 are my estimates based on public data

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Review the syllabus

Due

Complete Slack Introduction:
1. Sign-in to our Slack workspace
2. Navigate to the #general-discussion channel using the menu on the left side of the screen and post a message with your name and three numeric values that describe yourself, two of which are true and one of which is false (don’t say which is which).
3. Find another person’s post, hover over it, and click the chat bubble icon to start a thread. Then guess which of that person’s three statements is false.
4. Finally, find my name (Nate Wells) under Direct Messages on the left side of the screen, and send me a private message answering the following questions:
  1. What is your preferred name? (and what are your pronouns, if you’d like to share?)
  2. Do you have experience using R and Rstudio?
  3. What do you hope to take away from this course?
  4. What concerns do you have about this course, or about academics in general this term?
  5. What is one image that best describes you? (feel free to upload it)

Wednesday 9-2

Topics

RStudio
GitHub
- Working Solo
GitHub Classroom

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Chapter 1 and Section 2.1 (p 1-29) in Introduction to Statistical Learning
Chapter 1 and Chapter 4 in Happy Git and GitHub for the useR

Due

Friday 9-4

Topics

Estimating \(f\), the relationship between predictor and response variables
Assessing error in the guess my age activity

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Review Section 2.1 (p 15-29) in Introduction to Statistical Learning

Due

Homework 0. (Use the link in the #announcments channel to create your repo and view the assignment. Make sure you push any commits you make before 1:35pm on Friday.)

Week 2

Monday 9-7

No class; Labor Day

Wednesday 9-9

Topics

Decomposing the Mean Squared Error
- Wednesday 9-9 Demo
The Bias-Variance Trade-off

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 2.2 (p 29-41) in Introduction to Statistical Learning

Assigned

Homework 1 (Due Wednesday, 9/16 by the start of class)

Friday 9-11

Topics

Review Simple Linear Regression
Introduction to Multiple Linear Regression

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 3.1 (p 59-72) in Introduction to Statistical Learning

Week 3

Monday 9-14

Topics

Introduction to Multiple Linear Regression
- Regression plane for MLR (.Rmd)
Assessing Accuracy of Linear Models
Linear Models in R

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 3.2 (p 71-82) in Introduction to Statistical Learning

Wednesday 9-16

Topics

Extensions of the Linear Model

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 3.3 (p 82-92) in Introduction to Statistical Learning

Due

Homework 1

Assigned

Homework 2, To be posted by Wed. evening (Due Wednesday, 9/23 by the start of class)

Friday 9-18

Topics

Extensions of the Linear Model
- Code from today’s class

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 3.3 (p 92-102) in Introduction to Statistical Learning

Week 4

Monday 9-21

Lecture Video (requires Reed Kerberus credentials to watch)

Topics

Troubleshooting linear models

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 3.6 (p 109-119) in Introduction to Statistical Learning

Wednesday 9-23

Lecture Video (requires Reed Kerberus credentials to watch)

Topics

Transformations

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 3.5 (p 104-109) in Introduction to Statistical Learning

Due

Homework 2

Assigned

No homework assigned.

Friday 9-25

Topics

Review
- Midterm Practice

Reading Assignment

Note that the listed reading assignments should be completed prior to class

None

Week 5

Monday 9-28

Topics

KNN and Bayes Classifier
- Classification Activity

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Review Section 2.2.3 (p 37-42) and Section 3.5 (p 104-109) in Introduction to Statistical Learning

Wednesday 9-30

Topics

Logistic Regression
- 3d Plot of Logistic function

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 4.1 - 4.3 (p 127-137) and Section 4.6.2 (p 156 - 160) in Introduction to Statistical Learning

Due

None

Assigned

HW 3 assigned (Due Wednesday 10/7 by 1:35pm)

Friday 9-25

Topics

More Logistic Regression
Titanic
mushrooms

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 12.1 - 12.2 (p 275 - 287) in Applied Predictive Modeling

Week 6

Monday 10-5

Topics

KNN in R
Assessing model performance for classification
- Iris demo from end of class (.Rmd)
Mushroom Hunting

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Sections 4.6.1, 4.6.2, 4.6.5 and 4.6.6 (p 154-161, 163 - 167) in Introduction to Statistical Learning

Wednesday 10-7

Topics

Linear Discriminant Analysis

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 4.4 (p 138 - 150) in Introduction to Statistical Learning

The following reading is suggested for those interested in the mathematics behind LDA and who are familiar with linear algebra

Section 12.3 (p 287 - 297) in Applied Predictive Modeling

Due

HW 3

Assigned

HW 4 assigned (Due Wednesday 10/14 by 1:35pm)

Friday 10-9

Topics

QDA
Comparison of Classification Methods

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Read Sections 4.5, 4.6.3, 4.6.4 (p 151 - 154, 161 - 163) in Introduction to Statistical Learning

The following reading is suggested for those interested in the mathematics behind QDA and who are familiar with linear algebra

Section 13.1 (p 329 - 332) in Applied Predictive Modeling

Week 7

Monday 10-12

Topics

Cross validation
- Penguin Model Google Sheet
LOOCV
k-fold CV

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Sections 5.1 and 5.3.1 - 5.3.3 (p 175 - 186, 191 - 193) in Introduction to Statistical Learning

Wednesday 10-14

Topics

Cross validation
- Penguin Model Google Sheet
- Penguin Group Analysis .Rmd
LOOCV
k-fold CV
Bias-Variance Tradeoff Penguins

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Sections 5.2 and 5.3.4 (p 187 - 190, 194 - 197) in Introduction to Statistical Learning

Due

HW 4

Assigned

HW 5 assigned (Due Wednesday 10/21 by 1:35pm)

Friday 10-16

Topics

Bias-Variance Tradeoff
- Live Code .Rmd
The bootstrap
Summary of data splitting methods

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 4.3, 4.4, 4.7, 4.8 (p 67 - 73, 77 - 80) in Applied Predictive Modeling

Week 8

Monday 10-19

Topics

Subset Selection

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Sections 6.1 and 6.5.1 - 6.5.3 (p 203 - 214, 244 - 250) in Introduction to Statistical Learning

Wednesday 10-21

Topics

Penalized Regression

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Sections 6.2 and 5.3.4 (p 214 - 228, 251 - 255) in Introduction to Statistical Learning

Due

HW 5

Assigned

None

Friday 10-23

Topics

Midterm 2 Review

Reading Assignment

None

Week 9

Monday 10-26

No class.

Wednesday 10-28

Topics

Ridge Regression
Group projects

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Reread Sections 6.2 and 5.3.4 (p 214 - 228, 251 - 255) in Introduction to Statistical Learning

Due

None

Assigned

Revisions to Midterm 1 model (due Wednesday 11/4 by 1:35 pm); details forthcoming

Friday 10-30

Topics

LASSO
Group Projects

Reading Assignment

Section 6.4 (p 124 - 128) in Applied Predictive Modeling

Week 10

Monday 11-2

Topics

Regression Trees
- Mtcars regression tree

Reading Assignment

Note that the listed reading assignments should be completed prior to class

Section 8.1 (p 301 - 316) in Introduction to Statistical Learning

Wednesday 11-4