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This lecture covers the estimation of sample mean consistency, ergodicity, and stationarity in time series. It delves into the concepts of sampling, aliasing, and spectral representation, emphasizing the properties of linear time invariant filters. The lecture also explores the transfer function, frequency response function, and the spectral representation of stationary processes.