Overview
Explore linear regression from a Bayesian perspective in this comprehensive lecture from the Statistical Rethinking 2022 series. Delve into topics such as the rationale behind using normal distributions, generative and statistical linear models, validation techniques, and posterior predictions. Learn the language for modeling and gain insights into the statistical rethinking approach. Access accompanying slides and course materials on GitHub for a deeper understanding of the concepts presented. Navigate through various sections including an introduction, intermission, and summary, with musical interludes enhancing the learning experience.
Syllabus
Introduction
Why normal?
Flow
Language for modeling
Linear models, generative
Intermission
Linear models, statistical
Validation and analysis
Posterior predictions
Summary
Taught by
Richard McElreath