Lecture

Basics of linear regression model

Description

This lecture introduces the Ordinary Least Squares (OLS) method as an algebraic tool for linear regression. It covers the derivation of the OLS estimator, the Frisch-Waugh-Lovell theorem, predicted values, residuals, matrix notation, and the properties of OLS under Gauss-Markov assumptions. The lecture also explains the concept of goodness-of-fit using the coefficient of determination (R-squared) and discusses hypothesis testing, confidence intervals, and error types in statistical inference.

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.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.