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Catalog Year 2025-2026

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StatisticsCredits

A course in an area of statistics not regularly offered. May be repeated for credit on each new topic.

Provides a student the opportunity to gain expertise and experience in a special field under the supervision of a qualified person.

Independent individual study under the guidance and direction of a faculty member. Special arrangements must be made with an appropriate faculty member. May be repeated for credit of each new topic.

Simple and multiple regression, correlation, analysis of variance and covariance.

Prerequisites:
MATH 354 or STAT 354 or (MATH 455 or MATH 555) or (STAT 455 or STAT 555) with "C" (2.0) or better or consent.
Programs:

Randomized complete block design, Latin squares design, Graco- Latin squares design, balanced incomplete block design, factorial design, fractional factorial design, response surface method, fixed effects and random effects models, nested and split plot design.

Prerequisites:
MATH 354 or STAT 354 or (MATH 455 or MATH 555) or (STAT 455 or STAT 555) with "C" (2.0) or better or consent.
Programs:

A mathematical approach to statistics with derivation of theoretical results and of basic techniques used in applications. Includes probability, continuous probability distributions, multivariate distributions, functions of random variables, central limit theorem, and statistical inference. Same as MATH 555.

Prerequisites:
MATH 223 with "C" (2.0) or better or consent.
Programs:

A mathematical approach to statistics with derivation of theoretical results and of basic techniques used in applications, including sufficient statistics, additional statistical inference, theory of statistical tests, inferences about normal models, and nonparametric methods. Same as MATH 556.

Prerequisites:
(MATH 455 or MATH 555) or (STAT 455 or STAT 555) with "C" (2.0) or better or consent.
Programs:

Topics include: sampling distributions, means and variances; bias, robustness and efficiency; random sampling; systematic sampling methods including stratified random, cluster and two-state sampling; and ratio, regression, and population size estimation. Suitable software, such as MATLAB, R, SAS, etc., is introduced.

Prerequisites:
Either MATH/STAT 354 or both STAT 154 and MATH 121 with "C" (2.0) or better, or consent.

Topics on multivariate analysis for discrete data, including two/higher dimensional tables; models of independence; log linear models; estimation of expected values; model selection; and logistic models, incompleteness and regression. Suitable statistical software, such as MATLAB, R, SAS, etc., is introduced.

Prerequisites:
Either MATH/STAT 354 or both STAT 154 and MATH 121 with "C" (2.0) or better, or consent.
Programs:

Topics include derivation and usage of nonparametric methods in univariate, bivariate, and multivariate data; applications in count, score, and rank data; analysis of variance for ranked data; and regression estimation. Suitable software, such as MATLAB, R, SAS, etc., is introduced.

Prerequisites:
Either MATH/STAT 354 or both STAT 154 and MATH 121 with "C" (2.0) or better, or consent.

The study of a particular topic primarily based upon recent literature. May be repeated for credit on each new topic.

Provides a student the opportunity to gain expertise and experience in a special field under the supervision of a qualified person.

Bayesian Statistics is an alternative to Frequentist statistics. Bayesian inference uses probability for both hypotheses and data. In Bayesian statistics, population parameters are considered random variables having probability distributions. The probabilities measure a degree of belief in the parameters. Bayes' theorem is used to reformulate the beliefs using observed data. This course introduces the Bayesian approach to statistical inference and describes effective approaches to Bayesian modeling and computation.

Prerequisites:
MATH/STAT 455/555 and STAT 450/550, or consent
Programs:

Most statistical analysis and modeling techniques involve assumptions about the independence of the data. However, many real life data occur in the form of time series where observations are dependent. In this course, we will concentrate on both univariate and multivariate time series analysis and model building strategies with time dependent data. Available software will be used to complete the data analysis projects with a balance between theory and applications.

Prerequisites:
MATH/STAT 455/555 and MATH/STAT 450/550, with "C" (2.0) or better, or consent.
Programs:

Matrix theory, multivariate normal distribution of quadratic forms, estimation and hypothesis testing in the general linear model, and applications of linear models.

Prerequisites:
MATH/STAT 455/555 and STAT 450/550 with "C" (2.0) or higher, or consent.

Statistical tools used to analyze data in biological and medical research. Topics covered are Statistical Theory, Concepts of Statistical Inference, Regression and Correlation Methods, Analysis of Variance, Survival Analysis and Study Designs. Applications to medical problems.

Prerequisites:
STAT 450/550 with "C" (2.0) or higher, or consent.
Programs:

This course will cover the basic concepts of big data with an emphasis on the statistical techniques for analyzing structured and unstructured data. Students will learn concepts, techniques and tools that are necessary for working with the various facets of data science practice, including data collection and integration, exploratory data analysis, predictive modeling, descriptive modeling, data product creation, evaluation, and effective communication. The course has applications across many disciplines such as engineering, computer science, statistics, mathematics, economics and management. Prerequisite: MATH 247 and STAT 354 or instructor consent

Prerequisites:
STAT 450/550 with "C" (2.0) or higher, or consent.
Programs:

Independent individual study under the guidance and direction of a graduate faculty member.

Prerequisites:
Consent

A graduate course in a particular area of statistics not regularly offered. May be repeated for credit on each new topic.

Research under the supervision of the student's advisor leading to an alternate plan paper.

Prerequisites:
Consent
Programs:

Statistical package programs used in data collection, transformation, organization, summarization, interpretation and reporting, statistical description and hypothesis testing with statistical inference, interpreting outputs, chi-square, correlation, regression, analysis of variance, nonparametrics, and other designs, accessing and using large files (U.S. Census data, National Health Survey, etc.) Same as COMS 696

Prerequisites:
STAT 450/550 with "C" (2.0) or higher, or consent.
Programs:

Provides a student the opportunity to gain expertise and experience in a special field under the supervision of a qualified person.

Prerequisites:
Consent

Research under the supervision of the student's advisor leading to a thesis.

Prerequisites:
Consent
Programs:

Test subjectCredits

This is a course created for test purposes only. Not an actual course.

Theatre ArtsCredits

Survey of theatre arts; lectures, with lab experience available. Note: Students may not take both THEA 115 and this class.

Graduation Requirements:
Goal Area 6 - Humanities and the Arts
Programs:

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