Content
- Continuous distributions: multiple integration, conditional distributions, transformations
- Bayesian analysis: prior- and posterior distributions
- Asymptotic theory: plim, Slutsky's lemma
- Likelihood methods: maximum likelihood estimation, likelihood ratio testing, sufficiency, optimality
- Generalized linear models: logistic and Poisson regression
- Simulation-based inference: parametric and non-parametric bootstrapping
- Statistical programming (a little bit)
Literature
John Rice, Mathematical statistics and data analysis, Duxburry Press 1995, 2nd edition ISBN 0-534-20934-3