Course goals and objectives

Through hands-on experience with real problems, students will learn computing skills essential in applied statistics and in research in methodological and theoretical statistics. Topics include the Linux operating system; R and SAS (statistical computing environments); L^ATEX (mathematical document preparation language); reproducible research; database management; WinBUGS (software for fitting Bayesian models); simulation methods (Monte Carlo studies, bootstrap, MCMC); statistical computing algorithms (Newton's method, EM algorithm); interfacing to cyberinfrastructure resources.