Week 2: Sep 2 – Sep 6
Weekly Objectives
- Be able to fit linear regression using R
- Understand the optimization problem involved in a linear
regression
- Specify higher-order terms, categorical variables and
interactions
- Use a linear model to predict future testing samples
- First try for understanding the bias-variance trade-off in
prediction
- Use simulation to demonstrate properties of a model
- Be able to use model selection criteria and algorithms
Lecture Notes and R Examples
Data
Additional Readings
Homework