Introduction

University Services and Resources

Admissions Policies and Procedures

Academic Information

Financial Information

Programs of Study

Departments

College of Graduate Studies Home Page

 

Course Descriptions

Statistics (STA)                         Course Schedules

STA 575 Introduction to Statistical Packages 3(3-0) F
Introduction to statistical packages for data management and data analysis. SPSS, SAS and S-PLUS are introduced. Prerequisites: STA 282, STA 382 or permission of instructor.

STA 580 Applied Statistical Methods I 3(3-0) F
Applications of statistical methods including the usage of computer packages. Topics include forecasting, simple and multiple regression, and analysis of variance. Prerequisites: STA 282, STA 382. 

STA 582 Experimental Designs 3(3-0)
Randomized block designs, Latin square designs, factorial designs, fractional factorial designs, response surface methods. Prerequisite: STA 580 or equivalent.

STA 583 Nonparametric Statistics 3(3-0)
Theory and applications of nonparametric methods. Topics include one-, two-, and several sample problems, rank correlation and regression, Kolmogorov-Simirnov tests and contingency tables. Prerequisite: STA 382.

STA 584 Mathematical Statistics I 3(3-0) F
Probability defined on finite and infinite samples spaces, conditional probability and independence, random variables, expectations, moment-generating functions, probability models, limit theorems. Prerequisite: MTH 233.

STA 585 Mathematical Statistics II 3(3-0) Sp
Introductory topics from mathematical theory of statistics: population distributions, sampling distributions, point and interval estimation, tests of hypotheses. Prerequisite: STA 584.

STA 586 Clinical Trials and Survival Analysis 3(3-0)
Simple and advanced statistical techniques used in the analysis and interpretation of clinical research data. Emphasis on statistical techniques commonly used in chronic disease analysis. Prerequisites: STA 382 or equivalent.

STA 587 Statistical Theory and Methods for Quality Improvement 3(3-0)
Statistical theory and methods for optimizing quality and minimizing costs: classical and recently developed on-line methods and Taguchi's off-line quality and robust designs. Prerequisites: STA 580.

STA 588 Sampling Techniques 3(3-0)
Principles of sampling; simple random sampling; stratified random sampling; systematic sampling; cluster sampling; sample size determination; ratio and regression estimates; comparisons among the designs. Prerequisites: STA 382 or equivalent.

STA 589 Times Series Forecasting 3(3-0)
Introduction to basis timer series forecasting techniques. Topics include forecasting, Box-Jenkins models, time series regression, exponential smoothing, and transfer function models Prerequisites: STA 580, or permission of instructor.

STA 590 Applied Statistical Methods II 3(3-0) Sp
Multiway ANOVA, multiple comparison procedures, analysis of covariance, repeated measures analysis, unbalanced data and missing data analysis. Prerequisites: STA 580 and MTH 223.

STA 591 Statistical Methods for Data Mining 3(3-0)
Introduction to statistical techniques for data mining, including an overview of data mining and its applications, commonly used data mining techniques such as clustering, classification, association and predictive modeling techniques. Prerequisites: STA 580.

STA 596 Special Topics in Statistics 1-6(Spec)
Subject matter not included in regular courses. May be taken for credit more than once, total credit not to exceed six hours. Prerequisites: permission of the instructor.

STA 597 Independent Study 1-6(Spec)
Open to students with permission of instructor.  May be taken for credit more than once, total credit not to exceed 6 hours. Prerequisites: permission of department chairperson and instructor.

STA 680 Statistical Data Analysis and Consulting 3(3-0)
Advanced data analysis techniques, including categorical data analysis methods, logistic and loglinear models using statistical software such as SAS, SPSS, and MINITAB. Principles and techniques of statistical consulting. Prerequisites: STA 590 or permission of instructor.

STA 682 Linear Models 3(3-0)
Theory and application of least squares method and hypothesis testing for the linear regression models. Prerequisites: MTH 525; STA 584.

STA 684 Theory of Statistical Inference 3(3-0)
Stochastic convergence and limiting theorems, sampling distributions, Theory of point estimation and hypothesis testing, general linear hypotheses, sequential probability ratio test. Prerequisites: MTH 532 and STA 584.

STA 686 Multivariate Analysis 3(3-0)
Multivariate normal distributions, multivariate methods including multivariate analysis of variance, multivariate regression, principal component analysis, factor analysis, canonical correlation, discriminant analysis and cluster analysis. Prerequisites: STA 580, STA 584.

STA 782 Generalized Linear Models 3(3-0)
Theory and applications of generalized linear models, models for continuous data, models for binary and polytomous data, log-linear models, quasi-likelihood functions and model checking. Prerequisites: STA 682.

STA 784 Theory of Estimation 3(3-0)
Theory of point estimation in Euclidean sample spaces. Topics include unbiasedness, equivariance, global properties, large-sample theory, and asymptotic optimality. Prerequisites: STA 684; MTH 632.

Unspecified content or variable credit courses.  The following courses offered through the department are of unspecified content or variable credit: STA 596, STA 597.

Top of Page