STAT 5304. Introduction to Statistical Models. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

An introduction to statistical models, including ANOVA, linear regression, and covariate models. Topics include parameter estimation, confidence intervals, and model comparison, using hypothesis testing, p-values, and Bayes factors. Prerequisite: MATH 5302.

STAT 5305. Statistical Models. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Basics of experimental design, mathematical theory for linear and logistic regression models in the multivariate case, and diagnostics and remedial measures for these models. Other topics will be selected from ridge/lasso regression, principle components, canonical correlations, factor analysis, and discriminant analysis. Students may not receive credit for both MATH 5305 and STAT 5305. Prerequisites: The equivalent of an undergraduate course in probability and statistics or STAT 5304.

STAT 5310. Advanced Statistical Methods. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Non-parametric statistics, time series analysis, Bayesian inference, and other topics in advanced statistical analysis. Prerequisite: STAT 5305 or MATH 5305.

STAT 6304. Introduction to Statistical Models. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

An introduction to statistical models, including ANOVA, linear regression, and covariate models. Topics include parameter estimation, confidence intervals, and model comparison, using hypothesis testing, p-values, and Bayes factors. Credit will not be awarded for both STAT 5304 and STAT 6304. Prerequisites: Graduate standing.

STAT 6305. Statisitcal Models. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Basics of experimental design, mathematical theory for linear and logistic regression models in the multivariate case, and diagnostics and remedial measures for these models. Other topics will be selected from ridge/lasso regression, principle components, canonical correlations, factor analysis, and discriminant analysis. Students may only receive credit for one of these courses: MATH 5305, STAT 5305, and STAT 6305. Prerequisites: The equivalent of an undergraduate course in probability and statistics, STAT 5304, or STAT 6304.

STAT 6310. Advanced Statistical Methods. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Non-parametric statistics, time series analysis, Bayesian inference, and other topics in advanced statistical analysis. Credit will not be awarded for both STAT 5310 and STAT 6310. Prerequisite: MATH 5305, STAT 5305, or STAT 6305.

STAT 6315. Mathematical Statistics I. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

Modern statistical inference, starting with probability spaces, multivariate distributions, sampling distributions, confidence intervals, order statistics, hypothesis testing, and bootstrap procedures. Additional topics include consistency, limiting distributions, maximum likelihood methods, the Rao-Cramer lower bound, asymptotic relative efficiency, and the EM-algorithm. Prerequisite: MATH 5320 or approved graduate coursework in real analysis.

STAT 6316. Mathematical Statistics II. 3 Credit Hours (Lecture: 3 Hours, Lab: 0 Hours).

A second course in statistical inference, with topics selected from sufficient statistics, completeness, exponential families, minimal sufficiency, likelihood ratio tests, uniformly most powerful tests, normal linear models, nonparametric statistics, and Bayesian statistics. Prerequisite: STAT 6315.