Linear Regression Essentials

This lecture covers the essentials of linear regression, focusing on using multiple quantitative explanatory variables to predict a quantitative outcome. The instructor explains how to build a linear regression model, estimate parameters, interpret coefficients, and check model assumptions. The lecture also demonstrates how to apply linear regression in practice using a dataset about cars, discussing model fit, hypothesis testing, and model comparison. Additionally, it explores the concept of ANOVA and ANCOVA in the context of regression analysis.