Introduction to Mathematical Statistics

3 credits · Graduate

Formal introduction to basic theory and methods of probability and statistics: probability and sample spaces, independence, conditional probability, and Bayes' theorem; random variables, distributions, moments, and transformations. Parametric families of distributions and central limit theorem. Sampling distributions, traditional methods of estimation, and hypothesis testing. Elements of likelihood and Bayesian inference. Basic discrete and continuous statistical models. Not open to students who have credit for or are taking Statistical Science 230, 231, 240, 250, or 432. Not open to undergraduate students. Does not count towards the MS in Statistical Science degree.