Week 10: Linear Regression
Learning Objectives
By the end of this week, students will be able to:
- Formulate a regression problem and fit a linear model
- Interpret coefficients, residuals, and R² in context
- Apply regularization (Ridge, Lasso) and explain its effect on coefficients
- Diagnose model fit with residual plots and identify violations of assumptions
Perspectival Reading
Reading: TBD
Reflection Questions
- Linear regression assumes a particular relationship between variables. What gets hidden when the world doesn’t conform to this assumption?
- What does it mean for a coefficient to be “significant”? Significant to whom, and for what purpose?
- How might the choice to use a linear model reflect or reinforce existing patterns in society?
Slides
Notebook Demo
Open in Google Colab (link TBD)
Lab Assignment
Week 10 Lab — GitHub Classroom (link TBD)