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This lecture covers mixture models, including their definition and examples, such as discrete and continuous mixtures. It explores the concept of mixtures of logit models and the simulation-based estimation of parameters. The instructor discusses the motivation behind using mixture models to capture the complexity of heterogeneous populations and taste heterogeneity.