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This lecture covers the linear regression model and the least squares method, focusing on finding the parameters a and b that minimize the loss function L(a,b) = Σ (Z - atm - b)². The instructor explains the process step by step, emphasizing the importance of minimizing the loss function to obtain the best fit. Various examples and mathematical derivations are provided to illustrate the concepts and practical applications of linear regression. The lecture concludes with a discussion on the significance of the least squares method in statistical modeling and data analysis.