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This lecture covers linear regression topics such as confidence intervals for coefficients and variance, regression diagnostics, distribution plots, and the maximum likelihood approach. It explains the assumptions and calculations involved in least squares estimation, weighted least squares, and hypothesis testing in the least squares set-up.