Lecture

Regression: Linear Models

Description

This lecture covers linear regression, focusing on least squares regression, residuals, confidence intervals for coefficients and variance, and regression diagnostics. It explains the setup of linear regression models, polynomial regression examples, and assumptions like normal theory assumptions. The lecture also delves into the Gauss-Markov Theorem, maximum likelihood approach, and regression diagnostics through residual analysis and distribution plots.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.