The course will use combination of presentations and hands-on experience using R.
The learning will be evaluated using continuous evaluation throughout the course and possibly with a course work at the end of the course.
The course is meant for master's degree students (in their second year) and for doctoral students. The participants are expected to have knowledge of the basic concepts of statistics and statistical inference as well the R language. The course will follow the book "Computer age statistical inference"(Efron and Hastie, Cambridge University Press). Selected chapters from the book will be covered. The concepts of frequentist and Bayesian paradigms will be reviewed, and excerpts from parts II and III of the book will be discussed, including generalised linear models, regression trees, EM algorithm, MCMC, false detection rates, Lasso and random forests. The course includes introductory lectures, discussions, group work, homework and R exercises.