CS 503 - Statistical Methods

Prerequisite, MATH 210, or equivalent. This course will provide a lower graduate level introduction to classical statistical theory. Main concepts such as probability functions, univariate, multivariate, marginal and conditional distributions of random variables, transformations of random variables as well as classical asymptotic results such as the Law of Large Numbers, the Central Limit Theorem, sampling distributions, likelihood, confidence intervals, hypothesis testing, categorical data and linear regression will be emphasized from a more mathematically solid viewpoint. Examples, data, and programming code will be provided to ascertain clarity of all concepts and underline connections with related topics and current research. Examples will be provided to clarify the concepts and underline connections with related topics and current research. Data analyses will be performed via the statistical software package R (http://www.r-project.org). (Offered as needed.) 3 credits