Linear Regression Testing

This lecture covers the concept of least squares in linear regression, focusing on testing in the linear regression setting. Topics include non-central chi-squared distribution, orthogonal matrices, idempotent matrices, hypothesis testing, and diagnostics for linear regression models. The lecture also delves into outliers, influential observations, and the assumptions underlying Gaussian linear regression models.