Theory of Statistics II

Catalog description

Point estimation, properties of estimators, sufficiency and completeness, single parameter interval estimation, hypothesis testing, most powerful and UMP tests, likelihood ratio tests, maximum likelihood estimation (mle) and computational approaches to determine mle’s. The multivariate normal distribution, random vectors and covariance matrices; linear and quadratic forms. The general linear model, Cochran-Fisher theorem. Hypothesis testing and confidence regions for a vector of parameters. Prerequisite(s): Graduate level STT 6610 Minimum Grade of C