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This lecture covers structural modeling, state space models, and the Kalman filter in the context of time series analysis. Topics include local level and linear trend models, prediction errors, and the minimum mean square estimator. The instructor discusses the clever solution to prediction, the variance of prediction errors, and the estimation of unobserved state vectors.