*STA 511 SOFTWARE FOR STATISTICAL SCIENCES. Topics include MINITAB, SAS, Maple and Scientific Workplace (or equivalents). This one-hour course is available for graduate students in all disciplines. Prerequisites: STA 380 (or equivalent), graduate standing and consent of instructor.

Credit 1.

*STA 533 DESIGN AND ANALYSIS OF EXPERIMENTS. Topics include the design, analysis and interpretation of results from standard experimental design models including the completely randomized design, the randomized complete block, the incomplete block, factorial models, Latin squares, Greco-Latin squares, screening designs, fractional factorials, and general fixed, mixed and random effects ANOVA models. Prerequisites: STA 472 (or equivalent). Credit 3.

STA 560 SPECIAL TOPICS IN STATISTICS. Topics and courses are selected to suit individual student needs. Methods of independent study and research are stressed. Such topics as stochastic processes, Markov chain models, game theory, remote sensing, statistical decision theory, time series analysis and pattern recognition may be included. Prerequisites: Consent of instructor. Credit 3.

STA 561 THEORY AND APPLICATIONS OF PROBABILITY. Topics include probability axioms and properties, conditional probability, random variables, probability distributions, moment generating functions, laws of large numbers and the Central Limit Theorem. Prerequisites: STA 472 (or equivalent) or consent of instructor. Credit 3.

STA 562 THEORY AND APPLICATIONS OF STATISTICS. Topics include point estimation, hypothesis testing, interval estimation, nonparametric statistics, regression, correlation, analysis of variance, robustness and model fitting. Prerequisites: STA 561 (or equivalent). Credit 3.

STA 564 APPLIED MULTIVARIATE STATISTICAL ANALYSIS. Topics include the multivariate normal distribution, inferences about a mean vector, comparisons of several multivariate means, principal components analysis, clustering, discriminant and classification analysis. Prerequisites: STA 472 and MTH 568, or consent of instructor. Credit 3.

*STA 565 LINEAR STATISTICAL MODELS. Topics include the statistical properties of quadratic forms, the full-rank general linear statistical model, the less-than-full-rank model, the linear model structure of regression models, ANOVA models, ANCOVA models, the general characteristics of the fixed, mixed and random effects models and model diagnostics considerations. Prerequisites: STA 472 or STA 562 (or equivalents). Credit 3.

*STA 566 SAMPLING METHODS. Topics include the theory and applications of standard methods for performing scientific-based sampling. Among these are simple random sampling, cluster sampling, stratified random sampling, systematic sampling, probability proportional to size (pps) sampling, sampling from finite populations and ratio regression estimation. Prerequisite: STA 472, STA 562, or consent of instructor. Credit 3.

*STA 567 RELIABILITY ANALYSIS AND QUALITY CONTROL. Topics include measures of failure, reliability functions, failure models, life testing and censoring, system reliability, parameter estimation and testing, control charting, acceptance sampling plans, software reliability and process control. Prerequisites: STA 472, STA 562, or consent of instructor. Credit 3.

*STA 568 REGRESSION MODELING AND ANALYSIS. Topics include model estimation and testing, simple and multiple regression models, residual analysis, variables selection, polynomial regression, multicollinearity, ridge regression, logistic regression and real data analysis and applications. Prerequisites: STA 472, STA 562, or consent of instructor. Credit 3.

*STA 569 STATISTICAL COMPUTING AND CONSULTING. This course consists of a detailed study of the SAS package including SAS/BASICS, SAS/STAT, SAS/GRAPH and SAS/IML with emphasis on applying these tools in a consulting environment. Techniques and principles important in working with representatives of user disciplines are included. Prerequisites: STA 380 and graduate standing. Credit 3.

*STA 570 NONPARAMETRIC STATISTICS. Topics include order statistics, contingency analysis, rank tests (Wilcoxin signed-rank test, Mann-Whitney U test and others), distribution-free tests of location and scale, Kendall's tau and related areas. Prerequisites: STA 472, STA 562, or consent of instructor. Credit 3.

*STA 698 RESEARCH AND THESIS. This course includes a study of research methods in statistics, identification of an appropriate thesis problem and the preparatory work leading to a plan for its solution. Study must be supervised by a member of the graduate statistics faculty. Prerequisite: STA 562. Credit 3.

*STA 699 RESEARCH AND THESIS. This course continues the thesis research and concludes with a carefully written solution of the thesis problem and a satisfactory oral presentation of the results. Study must be supervised by a member of the graduate statistics faculty. Prerequisite: STA 698. Credit 3.