Course Descriptions

Note: Many of the courses listed here may be taken by graduate non-statistics majors for graduate credit.  For more information, refer to the "Statistics Electives" page.
1301  Statistical Reasoning: A Guide to the Unknown
Prerequisite(s): Freshman standing and consent of statistics undergraduate faculty advisor. 

Philosophical, ethical, and sociological issues related to statistical uncertainty and randomness.

1380   Elementary Statistics

Introduction to traditional statistical concepts including descriptive statistics, binomial and normal probability models, tests of hypotheses, linear correlation and regression, two-way contingency tables, and one-way analysis of variance. Credit may not be obtained after receiving credit in STA 2381 or 3381.

2381   Introductory Statistical Methods
Prerequisite(s): A grade of C or above in MTH 1321.

Parametric statistical methods. Topics range from descriptive statistics through regression and one-way analysis of variance. Applications are typically from biology and medicine. Computer data analysis is required.

3381   Probability and Statistics
Prerequisite(s): A grade of C or above in MTH 1322.

Introduction to the fundamentals of probability, random variables, discrete and continuous probability distributions, expectations, sampling distributions, topics of statistical inference such as confidence intervals, tests of hypotheses, and regression.

3386   Regression Analysis
Pre-requisite(s): STA 3381 and MTH 2321.

A development of regression techniques including simple linear regression, multiple regression, logistic regression and Poisson regression with emphasis on model assumptions, parameter estimation, variable selection and diagnostics.

4330   SAS Programming for Statistical Science
Pre-requisite(s): STA 2381 or 3381.

Concepts in SAS programming including methods to establish and transform SAS data sets, perform statistical analyses, and create general customized reports. Methods from both BASE SAS and SAS SQL will be considered.

4360   Bayesian Data Analysis
Pre-requisite(s): STA 4385

An introduction to Bayesian inference emphasizing prior and posterior distributions, estimation, prediction, hierarchical Bayesian analysis, and applications with computer implemented data analysis.

4362   Applied Time Series Analysis
Pre-requisite(s): STA 3386.

Statistical methods of analyzing time series. Model identification, estimation, forecasting, and spectral analysis will be discussed. Applications in a variety of areas including economics and environmental science will be considered.

4370   Sampling Techniques
Prerequisite(s): Three hours of statistical methods.

Planning, execution, and analysis of sampling from finite populations. Simple random, stratified random, ratio, systematic, cluster, sub sampling, regression estimates, and multi-frame techniques are covered.

4371   Data Management and Mining
Prerequisite(s): STA 3381.

Terminology, techniques, and management of Data Mining for biostatisticians.

4372   Introduction to Biostatistics
Prerequisite(s): STA 2381 or STA 3381 or consent of the instructor.

Data Analysis for biostatisticians in the biomedical and pharmaceutical fields.

4373  Computational Methods in Statistics
Prerequisite(s): STA 2381 or STA 3381 or consent of the instructor.

Computational methods using statistical packages and programming.

4374   Statistical Process Control
Prerequisite(s): STA 3381 or equivalent.

Development of statistical concepts and theory underlying procedures used in statistical process control applications and reliability.

4382   Intermediate Statistical Methods
Prerequisite(s):  A minimum grade of C in either STA 2381 or STA 3381; or consent of instructor.

Development and application of two-sample inference, analysis of variance and multiple regression. Assumptions, diagnostics and remedial measures are emphasized. Computer statistics packages are utilized.

4385  Mathematical Statistics I
Prerequisite(s): MTH 2321 with minimum grade of C.

Introductions to the fundamentals of probability theory, random variables and their distributions, expectations, transformations of random variables, moment generating functions, special discrete and continuous distributions, multivariate distributions, order statistics, and sampling distributions.

4386  Mathematical Statistics II
Prerequisite(s): STA 4385 with minimum grade of C.

Theory of statistical estimation and hypothesis testing. Topics include point and interval estimation, properties of estimators, properties of test of hypotheses including most powerful and likelihood ratios tests, and decision theory including Bayes and minimax criteria.

4387   Introduction to Probability Methods
Prerequisite(s): STA 4385 with minimum grade of C.

Applications of probability theory to the study of phenomena in such fields as engineering, management science, social and physical sciences, and operations research. Topics include Markov chains, branching processes, Poisson processes, exponential models, and continuous-time Markov chains with applications to queuing systems. Other topics introduced are renewal theory and estimation procedures.

43C9  Capstone Statistics Course
Prerequisite(s): Approval of the statistics undergraduate faculty advisor.

Statistical concepts applied to written and oral reports for consulting. For students majoring in statistics.

4V90 Special Topics in Statistics                     1 to 3 sem. hrs.
Prerequisite(s): STA 2381 or STA 3381.

Topics in probability and/or statistics not covered in other courses. May be repeated for a maximum of 6 hours if the content is different.