STA 295 Spring 2025

Welcome to the Spring 2025 section of STA 295: Introduction to Statistical Learning

Syllabus

The syllabus can be found here

R Downloads

• R
• RStudio
• RTools44

Textbook

An Introduction to Statistical Learning, 2nd Edition (2021) by James, Witten, Hastie, and Tibshirani. (A
.pdf copy of the text is available free of charge on the author’s website). Make sure you download ISL-R not ISL-Python

Labs

Sta-295 will use a modified workshop style class format. This means that much of our class time will be devoted towards collaboratively working through guided lab activities. You should consult the syllabus for a more detailed description of lab procedures and expectations. The majority of these labs were modified from labs by Professor Ryan Miller, Professor Nate Wells, or from the textbook.

• Spring break is between weeks 7 and 8
• Introduction:
  • Lab 1: R basics
  • Lab 2: ggplot
  • Lab 3: Practice
  • Lab 4: Tradeoffs
• Linear Regression:
  • Lab 5: Linear Regression
  • Lab 6: Multiple Linear Regression
• Selection and Regularization
  • Lab 7: Model Selection
  • Lab 8: Polynomial Regression
• Resampling Methods
  • Lab 9: Cross Validation
  • Lab 10: Bootstrap
• Classification part 1:
  • Lab 11: Logistic Regression
  • Lab 12: Naive Bayes
• Classification part 2: Unsupervised
  • Lab 13: KNN
  • Lab 14: Hierarchical Clustering
• Tree Based Methods:
  • Lab 15: Trees 1
  • Lab 16: Trees 2
• Ensemble Models:
  • Lab 17: Ensemble Models
  • Lab 18: Forests
• Support Vector Machines
  • Lab 19: SVM1
  • Lab 20: SVM2

Homework Assignments

• Homework 0: Course basics. Due week 1. Gradescope only
• Homework 1: R basics. Due week 2
• Homework 2: Foundations. 2.4: 1, 2, 4, 8, 9. Due week 3
• Homework 3: Linear Regression. 3.7: 1, 3, 5, 8, 13. Due week 4
• Homework 4: Model Selection. 6.6: 1, 2, 8, 10. Due week 5
• Homework 5: Resampling. 5.4: 1, 2, 3, 8, 9. Due week 7
• Homework 6: Classification. 4.8: 1, 6, 7, 13a-d,h, 15. Due week 8
• Homework 7: Clustering. 12.6: 2, 3, 5, 9, 13. Due week 9
• Homework 8: Trees and Forests. 8.4: 3, 5, 6, 8. Due week 11
  • Update: don’t do part 8f, problem 10 removed
  • Update: Due week 12 (April 25th)
• Homework 9: SVM. 9.7: 3, 4, 5. Due week 12
  • Update: Due week 13 (May 2nd)

Projects

• Project 1: Released Week 4, Due Week 6.
  • Assigned Groups
• Project 2: Released Week 9, Due Week 10.
  • Pseudo Random Group Assignment
• Project 3: Due Week 14
  • Choice of Group
    • Group proposed Week 7 (2-3)
    • I will assign groups as needed
  • Proposal Due Week 9
  • Data Exploration Due and Rough Draft Due Week 12
  • Presentation Week 14
  • Final submission due Week 14 5pm

Recommended Readings