MATH 4335 Computational Statistics and Its Applications
In this course, students will learn the basics of R programming and the application, at an introductory level, of methods for the asymptotic evaluation of estimators, the generation of observations of random variables, testing hypothesis, and generating confidence intervals using jack knife and bootstrap techniques, finding estimators using the expectation-Maximization algorithm, as well as the application of Markov Chain Monte Carlo (MCMC) simulations and its use in Bayesian methods.