**The Master of Arts program in Statistics requires 34 credit hours.**

MATH 528 - Regression and Time Series Models (3)

MATH 529 - Analysis of Variance in Experimental Design Models (3)

MATH 620 - Mathematical Theory Statistics 1 (4)

MATH 621 - Mathematical Theory Statistics 2 (4)

MATH 625 - Probability Theory and Applications (3)

MATH 626 - Probability and Stochastic Processes (3)

MATH 627 - Generalized Linear Models with Applications (4)

MATH 628 - Computational Methods in Statistics (4)

MATH 689 - Research Methods in Mathematics and Statistics (3)**The Master of Science program in Statistics requires 34 credit hours.**

**Required Courses:**

MATH 529 - Analysis of Variance in Experimental Design Models (3)

MATH 620 - Mathematical Theory of Statistics 1 (4)

MATH 621 - Mathematical Theory of Statistics 2 (4)

MATH 625 - Probability Theory and Applications (3)

MATH 626 - Probability and Stochastic Processes (3)

MATH 627 - Generalized Linear Models with Applications (4)

MATH 628 - Computational Methods in Statistics (4)

THES 698 - Thesis (1-6 credit hours)

**An additional 3 credit hours from:**

MATH 522 - Theory of Sampling and Surveys (3)

MATH 528 - Regression and Time Series Models (3)

**Related Links** Graduate Course Offering Schedule (PDF)

**522 Theory of Sampling and Surveys (3)**

Survey designs; simple random, stratified, cluster, and systematic sampling; ratio estimates; regression estimates; cost and variance functions.

*Prerequisite: *MATH 321 or the equivalent.

**528 Regression and Time Series Models (3)**

Addresses regression topics that include simple and multiple linear regression, polynomial regression, regression diagnostics, and forecasting. Also introduces time series topics that include exponential smoothing, auto-regressive, integrated, moving average (ARIMA) models, and forecasting.

*Prerequisite: *MATH 321 or the equivalent.

*Not open to *students who have credit in MATH 428.

**529 Analysis of Variance in Experimental Design Models (3)**

Multivariate normal distribution; quadratic forms; linear models; simple random, randomized block, Latin squares, factorial, split-plot, balanced incomplete block designs; analysis of covariance; confounding; and multiple comparison tests.

*Prerequisite: *MATH 321 or equivalent.

*Not open to *students who have credit in MATH 429.

**620 Mathematical Theory of Statistics 1 (4)**

Probability set functions, random variables, density and distribution functions, mathematical expectations, marginal and conditional distributions, sampling distributions, and limiting distributions. The mathematical rigor requires a strong background in calculus.

*Prerequisite: *MATH 166 and MATH 215.

**621 Mathematical Theory of Statistics 2 (4)**

Estimation theory and statistical tests of hypothesis. Topics include: classical and Bayesian estimation, sufficiency, completeness, uniqueness, likelihood function, exponential families, Rao-Blackwell Theorem, Rao-Cramer inequality, hypothesis testing, Neyman-Pearson Lemma, likelihood ratio tests, goodness-of-fit, contingency tables, nonparametric tests, distribution of quadratic forms, and correlation and regression, bootstrapping.

*Prerequisite: *MATH 620.

**625 Probability Theory and Applications (3)**

Basic probability theory, random variables, conditional probability and conditional expectation, Poisson process, interarrival time, and waiting time distributions.

*Prerequisite: *MATH 166 or equivalent.

**626 Probability and Stochastic Processes (3)**

Discrete and continuous time Markov chains, queuing theory, renewal theory.

*Prerequisite: *MATH 625 or equivalent.

**627 Generalized Linear Models with Applications (4)**

Methods needed to analyze non-normal data. Topics include exponential family of distributions, an overview of generalized linear models. Models for: continuous data with constant variance, binary data, polytomous data, count data, time to events or survival data.

*Prerequisite: *MATH 621 or permission of the department chairperson.

**628 Computational Methods in Statistics (4)**

Theory and application of simulation techniques used in statistics. The use of statistical software such as SAS and R in statistical analysis.

*Prerequisite: *MATH 620 or permission of the department chairperson.

**689 Research Methods in Mathematics and Statistics (3)**

The scientific method in mathematical research. Location of relevant journal articles, reference books, and reviews. Development of research and problem-solving techniques. Each student will write a mathematical paper. The instructor will assist students whose work is of exceptional quality in submitting their results for publication.

**Thesis (THES)**

**698 Thesis**

This plan requires the candidate to present a thesis embodying the results of a study of some subject directly related to the area of specialization. The thesis must show that the candidate possesses the abilities to pursue a research problem successfully and to draw valid and significant conclusions from the data. The student must have a committee of three faculty members seleced in consultation with the department chairperson.

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