Course Requirements

Candidates for the degree must complete at least 48 quarter hours of graduate level work in applied mathematics and pass two sets of comprehensive examinations. Comprehensive examinations are offered twice a year, in the autumn and spring quarters. Part- I covers the material in MAT 451-452-453, and  Part- II is based on the student's chosen area of concentration.

At the beginning of the quarter when students plan to take the comprehensive  examinations, they should register with the program director. 

Core Courses

Computer Usage

The department places strong emphasis on computation and is well supported with equipment and software necessary for research. The computer is used for  data analysis and to find solutions to problems that arise in numerical analysis, simulations, and mathematical modeling. The computer packages used in these courses are likely to play an important role in the solution of the problems students will encounter in their places of employment.

MAT 451

PROBABILITY AND STATISTICS I

The course covers elements of probability theory; distributions of random variables and linear functions of random variables; moment generating functions; and discrete and continuous probability models. COREQUISITE(S): MAT 260.
Prerequisites:
MAT 260 is a corequisite for this class.

MAT 452

PROBABILITY AND STATISTICS II

A continuation of MAT 451. More continuous probability model. Laws of large numbers and the central limit theorem. Sampling distributions of certain statistics. An introduction to the theory of estimation and principals of hypothesis testing. COREQUISITE: MAT 261.
Prerequisites:
MAT 451 is a prerequisite for this class and MAT 261 is a corequisite for this class.

MAT 453

PROBABILITY AND STATISTICS III

A continuation of MAT 452. More on hypothesis testing, most powerful, uniformly most powerful, and likelihood ratio tests. Introduction to the analysis of variance; linear regression; categorical data analysis, and nonparametric methods of inference.
Prerequisites:
MAT 452 is a prerequisite for this class.

MAT 448

STATISTICAL METHODS USING SAS

The SAS programming language. Data exploration, description and presentation. Inference methods for continuous and categorical data. Analysis of variance models and regression procedures.

MAT 456

APPLIED REGRESSION ANALYSIS

Simple linear, multiple, polynomial and general linear regression models. Model diagnostics; Model selection and Validation. Cross-listed with MAT 356.
Prerequisites:
MAT 453 is a prerequisite for this class.

MAT 459

SIMULATION MODELS AND MONTE CARLO METHOD

Techniques of computer simulation of the classical univariate and multivariate probability models, and such random processes as random walks, Markov chains, and queues. Cross-listed with MAT 359.
Prerequisites:
MAT 453 is a prerequisite for this class.