This lecture covers topics such as iterative weighted least squares, model checking, generalized linear models, Poisson regression, contingency tables, ordinal responses, mixed models, and smoothing. It also discusses fitting multinomial models using Poisson errors and the importance of including appropriate baseline terms in the linear predictor.