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This lecture covers statistical inference topics related to exponential families, likelihood functions, and model regularity conditions. It discusses the challenges of non-regular models, composite likelihoods, and empirical likelihoods. The instructor explains the importance of likelihood-based approaches, their strengths, weaknesses, and practical applications in various statistical scenarios.