Program Overview

Mathematics, MS

The mission of the Graduate Mathematics program is to increase understanding and the ability to apply mathematics and statistics through in-depth study, novel applications, and research. The areas of emphasis are mathematics education and applications of mathematics and statistics.

Program Description

The program prepares students for careers in education, science, and industry and serves the community by providing expertise to local schools, coastal industry, business, and research centers.

Program Tracks

Students pursuing the Master of Science degree with a major in Mathematics will choose between:

• Applied and Computational Mathematics
• Statistics option
• Curriculum Content option

Applied and Computational Mathematics Option

This option will especially benefit individuals employed in scientific, technical, or education fields who seek advancement or additional training to enhance their knowledge and skills. The Applied and Computational Mathematics option requires a thesis.

Statistics Option

The statistics option prepares individuals to work with statistical data analysis in science, industry, or business. This option allows for a thesis or project.

Curriculum Content Option

The Curriculum Content option specifically addresses the needs of in-service teachers wishing to enhance their knowledge and skills in learning, teaching, and understanding mathematics. This option also allows for a thesis or project.

Fast Track Mathematics BS to Mathematics MS

The university allows the opportunity for high-achieving undergraduate students to count a select number of graduate credits toward their undergraduate degree and thereby obtain a graduate degree at an accelerated pace.

Student Learning Outcomes

Students will:

• Demonstrate a command of principles of general mathematics at the graduate level.
• Recognize mathematics outside the realm of the classroom, and apply graduate level mathematical content as a matter of professional practice.
• Communicate mathematics effectively at the graduate level, in oral and written form, with appropriate use of technology.

Admission Requirements

In addition to meeting all University requirements for admission to graduate study in degree-seeking status, applicants for the MS degree in mathematics must also submit an essay to the Office of Recruitment and Admissions. The essay should discuss the applicant's educational and professional goals, pertinent work and undergraduate experience, and other factors relating to the chosen option for graduate study.

Program Requirements

The course of study for the MS program in mathematics consists of the components listed below. Graduation requirements are slightly different for the Applied and Computational Mathematics and Curriculum Content options.

Applied and Computational Mathematics Option

• Core Courses: 15 hours
• Electives from mathematics or closely related field: 12-15 hours
• Thesis: 6-9 hours
• Total Hours: 36-39

Statistics Option

• Core Courses: 15 hours
• Electives from mathematics or closely related field: 12-15 hours
• Thesis or Project: 6-9 hours
• Total Hours: 36-39

Curriculum Content Option

• Core Courses: 15 hours
• Electives: 12 hours
• Thesis or Project: 6-9 hours
• Total Hours: 36

Courses

A list of available courses, including:

• MATH 5301: Foundations for Advanced Mathematics
• MATH 5310: Topics in Mathematics
• MATH 5311: Statistical Learning
• MATH 5315: Statistical Methods in Research I
• MATH 5316: Statistical Methods in Research II
• MATH 5321: Problem Solving and Mathematical Reasoning for Teachers
• MATH 5322: Mathematics Assessment
• MATH 5323: Mathematics Instruction and Mentoring
• MATH 5324: Principles of Reforming Mathematics Instruction
• MATH 5325: Structure of Number Concepts
• MATH 5326: Structure of Patterns and Algebra
• MATH 5327: Structure of Geometry and Measurement
• MATH 5328: Structure of Probability and Statistics
• MATH 5329: Structure of Modeling with Rates of Change
• MATH 5331: Evolution of Mathematical Systems
• MATH 5332: Integrating Technology in Mathematics Education
• MATH 5333: Numerical Linear Algebra
• MATH 5336: Advanced Differential Equations
• MATH 5337: Theory and Applications of Partial Differential Equations
• MATH 5338: Finite Elements Method
• MATH 5339: Numerical Analysis
• MATH 5340: Numerical Solutions of Partial Differential Equations
• MATH 5341: Statistical Methods and Data Analysis
• MATH 5342: Linear Statistical Models
• MATH 5343: Mathematical Theory of Statistics
• MATH 5344: Environmental Statistics
• MATH 5345: Computational Methods for Statistics
• MATH 5348: Optimization
• MATH 5351: Real Analysis
• MATH 5360: Combinatorics and Graph Theory
• MATH 5370: Modeling of Natural Systems
• MATH 5375: Applied Analysis
• MATH 5378: Mathematical Modeling
• MATH 5390: Special Topics
• MATH 5393: Literature Review and Research
• MATH 5394: Research Methods in Mathematics
• MATH 5396: Directed Independent Study
• MATH 5993: Literature Review and Research
• MATH 5994: Proposal Research
• MATH 5995: Thesis
• MATH 5997: Project
• MATH 6315: Statistical Methods in Research I
• MATH 6316: Statistical Methods Research II
• MATH 6317: Mixed Effects Models for Scientists
• MATH 6318: An Introduction to Bayesian Statistics
• MATH 6344: Spatial Statistics