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This lecture covers the concept of confidence intervals in statistics, focusing on providing an idea of the uncertainty of a parameter estimation. It explains how to construct confidence intervals, interpret them, and use them for estimation. The lecture also discusses approximate confidence intervals, based on estimators and the need to estimate variances. It delves into the central limit theorem for constructing approximate confidence intervals and determining the confidence level. Examples and the implications of constructing confidence intervals using the central limit theorem are also presented.