Week 1: Generalized linear models: what they are and what they are good for

Week 2: Public hodilay: no lecture

Week 3: Asymptotic statistics, maximum likelihood and quasi-likelihood

Week 4: Asymptotic statistics, maximum likelihood and quasi-likelihood

Week 5: Elements of a generalized linear model

Week 6: Estimation for generalized linear models

Week 7: Inference, deviance, residuals and extensions

Week 8: Bonus midterm exam

Week 9: Generalized linear models for binary/binomial data

Week 10: Logistic regression and its generalizations

Week 11: Generalized linear models for count data

Week 12: Contingency tables