Linear Regression: Basics and Applications

This lecture covers the fundamentals of linear regression, focusing on the method of least squares to approximate a line that best fits a set of data points. The instructor explains how to determine the parameters a and b in the equation y = ax + b, illustrating the process with examples and discussing the concept of residuals. The lecture also delves into the normal equation form and the importance of regression analysis in statistical modeling.