## Master of Science in Mathematics

Students may choose to earn the Master of Science in Mathematics degree with or without an option. There are three options currently available for MS in Mathematics students:

- Applied and Computational Mathematics
- Probability and Statistics
- Mathematics for Teachers
- Industrial Mathematics Professional Science Master's (this option is not accepting new students)

The Master of Science in Mathematics, including the options in Applied and Computational Mathematics, Probability and Statistics, Mathematics for Teachers options, each consist of thirty credit hours approved by the Graduate Curriculum Committee. (The Industrial Mathematics PSM is a 37 credit program, including a required internship and sequence of PMSA seminars.). All options require a four-year undergraduate degree from an accredited college or university with a satisfactory grade point average.

For the Applied and Computational Mathematics and the Probability and Statistics options, the undergraduate degree must be in mathematics or a related discipline. For the Mathematics for Teachers option, three semesters of calculus (12 credits) are required. Applicants lacking some prerequisites may be accepted as matriculated with conditions.

Program requirements include both required courses and electives (which may be offered in other departments). Up to six credits at the 400 level may be considered for inclusion in the program of study. In addition, in all options except the Industrial Mathematics Professional Science Master's Option, three or six credits may, with the permission of the student advisor and Graduate Committee, be obtained by completing a thesis. Most courses are offered on a regular basis in the late afternoon and early evening so that all programs can be completed on a part-time basis.

**Master of Science in Mathematics ("general option")**

### Applied and Computational Mathematics

The M.S. Option in Applied and Computational Mathematics focuses on techniques of mathematical modeling and the basic tools needed to investigate problems from both a theoretical and computational viewpoint. Courses range from classical applied mathematics and state of the art courses in signal processing to modern applications of software in problem solution.

*Degree Requirements: *

- MATH.5010 Real Analysis I
- MATH.5300 Applied Mathematics I
- MATH.5630 Computational Mathematics I
- Two of the following "Theory or Analysis" courses (Choose two of the following for 6 credits):

MATH.5070 Applied Functional Analysis I

MATH.5110 Complex Variables I

MATH.5260 Topology

MATH.5310 Applied Mathematics II

MATH.5450 Partial Differential Equations - Two of the following "Application" courses (Choose two of the following for 6 Credits):

MATH.5090 Probability & Mathematical Statistics

MATH.5500 Mathematical Modeling

MATH.5630 Computational Mathematics

MATH.5650 Special Functions

MATH.5720 Optimization

### Probability and Statistics

This option is a professionally oriented program that provides the necessary mathematical skills to solve many of the data analysis problems of government, industry, science, engineering, and management. Courses range from theory based courses in probability through to applied hands-on course in statistical programming, including a course in the use of SAS statistical software.

*Degree Requirements: *

- MATH.5010 Real Analysis I
- MATH.5090 Probability & Mathematical Statistics
- MATH.5880 Mathematical Statistics
- Choose one of the following "theory" courses:

MATH.5840 Stochastic Processes

MATH.5870 Measure & Probability Theory

MATH.5920 Multivariate Statistics - Choose one of the following "applied"courses:

MATH.5900 Statistical Quality Control

MATH.5910 Linear Statistical Modeling & Regression

MATH.5930 Experimental Design

### Mathematics for Teachers

The Master of Science in Mathematics for Teachers Program aims to give students a balanced combination of theory and practice, to enhance their appreciation and understanding of Mathematics as a science, and to provide them with the tools necessary to instill in their own students an interest in the subject. Courses in Mathematical Analysis, Discrete Mathematics, Linear Algebra, Number Theory, Geometry, and Probability and Statistics are designed to introduce the student to several important areas of Mathematics. Courses in Problem Solving, History of Mathematical Science, Mathematical Modeling, and Computers in the Classroom are intended to provide a deeper awareness of the contexts in which mathematical activity takes place and of the mental processes and technological aids employed by people in solving practical problems. Note that this is not a teaching certification program - contact the Graduate School of Education for information about certification.

Required courses:

### Industrial Mathematics Professional Science Master's

**This program is no longer accepting applications.**

**Admission Requirements**

Incoming students will be expected to have completed the equivalent of an undergraduate degree in mathematics. Applicants with degrees in other sciences or engineering may be admitted if they demonstrate significant background in mathematics.

Degree Requirements - Total Number of Credits: 34

**Mathematics Courses** (12 credits)

**Required**:

- MATH.5010 Real Analysis I
- MATH.5090 Introduction to Probability & Statistics
- MATH.5300 Applied Mathematics I
- MATH.5630 Computational Mathematics

**Science Cluster - One cluster of 12 credits from the following.**

(Variations on these clusters or different ones can be proposed with the guidance of the student's advisor.)

**Algorithms Cluster**

- MATH.5800 Discrete Math for Science and Engineering
- COMP.5030 Algorithms
- COMP.5040 Advanced Algorithms: Computational Geometry
- COMP.5440 Machine Learning and Data Mining

**Random Processes Cluster**

- MATH.5840 Stochastic Processes
- EECE.5090 Linear Systems Analysis
- EECE.5480 Coding and Information Theory
- EECE.5840 Probability and Random Processes

**Physics Cluster**

- MATH.5330 Mathematical Methods of Quantum Mechanics
- PHYS.5350 Introductory Quantum Mechanics I
- PHYS.5530 Electromagnetism I
- PHYS.5540 Electromagnetism II

**Statistics Cluster**

- MATH.5760 Statistical Programming using SAS
- MATH.5880 Mathematical Statistics
- MATH.5910 Linear Statistics Modeling and Regression
- MATH.5930 Experimental Design

**Epidemiology/Biostatistics Cluster**

- MATH.5760 Statistical Programming in SAS
- MATH.5910 Linear Statistics Modeling and Regression
- PUBH.5750 Introduction to Biostatistics and Epidemiology
- PUBH.6890 Advanced Regression Modeling

**PSM sequence of the Developmental Seminar (0 credit), Internship****(zero credit) and Reflective Seminar (1 credit)**

- PSMA.5000 Professional Development Seminar (0 credit)
- PSMA.5100 Internship (0 credit)
- PSMA.5010 Reflective Seminar (1 credit)

Each student must complete an internship lasting a minimum of 350 hours. Before starting the internship, the student must have completed at least 18 credit hours in the program, including 6 credit hours of PLUS coursework, must have completed the course PSMA.5000 Professional Development, and must have a GPA of at least 3.3. In cases where a PSM student is employed in their career field the PSM student will be required to do a PSM project at their place of employment. The student should register for the course PSMA.5100 PSM Internship during the internship period.

In the semester immediately following completion of the PSM Internship (or PSM Project for students employed in their career field) the student is required to take PSMA.5010 Reflective Seminar (1 credit).

**Professional Plus Courses** (9 credits)

- MKTG.5450 Professional and Scientific Communication

*Plus two-3 additional courses (six credits) from the following list:*