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This lecture covers topics such as iterative weighted least squares, model checking, generalized linear models, mixed models, Poisson regression, contingency tables, and smoothing. The instructor discusses the inference process, matrix inversion formulae, and the use of REML estimation to reduce bias in parameter estimates.