10.29: Logistic Regression Estimation & Interpretation
Upcoming deadlines
- Statistics Reflection 4: Sunday, Nov 3 11:59 PM
- HW 4: Sunday, Nov 10 11:59 PM
Learning Objectives
By the end of the class, students should be able to:
Describe the estimation procedure for a logistic regression model
Interpret coefficients, confidence intervals, and p-values in logistic regression
Generate predictions from a logistic regression model
Class prep
Watch this video:
Logistic Regression estimation and interpretation
Note that this video introduces maximum likelihood estimation, but you have seen maximum likelihood estimation earlier this semester. Here, we apply maximum likelihood estimation to the regression context.
Supplementary videos:
Maximum likelihood vs least squares estimation
Logistic regression: the basics
Logistic regression: maximum likelihood
Slides: Logistic Regression Estimation
Optional/supplementary textbook reading: ISLR 4.3.2-4.3.4