DATA88B.3 - Linear Regression
About this course (Part 3 of 3): 88B concludes with linear regression, multiple regression, non-linearity, logistic regression, and interaction. Part 3 ties together modeling and regression for data-driven decisions.
Topics¶
Part 3 (sometimes listed as 88.3X on edX) includes 4 modules:
Module 11: Linear Regression - Fitting and interpreting simple linear regression; R², residuals, prediction, and inference.
Module 12: Non-linearity - Multiple regression, non-linear patterns, and interpreting coefficients.
Module 13: Discontinuity, Trend, & Seasonality - Discontinuity, trend, seasonality; logistic regression for binary outcomes.
Module 14: Interaction - Interaction terms in regression, interpretation and visualization; introduction to clustering.
Each module includes lecture content and Jupyter lab assignments.
Structure and assignments¶
Modules: 4 content modules (plus “Succeeding in This Course” where applicable)
Labs: 4 Jupyter lab assignments
Quizzes: 4 quizzes