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This lecture covers the problem of estimation in a general framework, focusing on point estimation using estimators to determine the true value of a parameter. It discusses criteria for comparing estimators, such as mean and variance, and introduces the concept of mean squared error. The lecture also delves into the Cramér-Rao bound and consistency of estimators, highlighting the challenges in achieving optimal estimators. Various mathematical expressions and theorems related to estimation and error analysis are presented, providing a comprehensive overview of statistical estimation.