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This lecture covers the estimation and inference aspects of linear regression models, focusing on the least squares method, estimation of parameters, linearity assumptions, model comparison, and statistical tests. The instructor explains how to estimate the parameters of a simple linear model, interpret the least squares estimators, and perform hypothesis testing on the regression coefficients.