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This lecture covers the Decision Theory Framework in Statistical Theory, where statistics is viewed as a random game with Nature and a statistician playing. It discusses point estimation, interval estimation, and hypothesis testing within this framework, exploring concepts like admissibility, inadmissibility, minimax rules, Bayes rules, and randomized rules.