Graduate
Student Learning Outcomes
Mathematics
Master of Science in Mathematics (M.S.)
Degree concentrations include: Applied Mathematics, Pure Mathematics, Applied Statistics, and Math Education. In addition to the Student Learning Outcomes for the B.S. degree, those who graduate with a M.S. degree in Mathematics will be able to:
- Demonstrate increased depth of understanding in most sub-disciplines of mathematics.
- Integrate sub-disciplines of mathematics and other disciplines as applicable in problem solving.
- Read and understand peer-reviewed mathematical literature.
- Identify mathematical problems and design solutions to solve these problems.
Master of Science in Mathematics - Applied Statistics Concentration (M.S.)
- Demonstrate increased depth of understanding in most sub-disciplines of mathematics.
- Integrate sub-disciplines of mathematics and other disciplines as applicable in problem solving.
- Read and understand peer-reviewed mathematical literature.
- Identify mathematical problems and design solutions to solve these problems.
- Develop a deeper knowledge and competence in the area of applied statistics.
Master of Science in Mathematics Teaching (M.S.)
In this program, it is intended that students:
- Develop an increased appreciation for higher mathematics
- Learn about the sources and history of secondary mathematics
- Learn about how abstract algebra forms the foundation for high school algebra and solving for the roots of an equation
- Learn a deeper appreciation for mathematical analysis in order to be able to teach calculus effectively in the high school
- Study alternate forms of geometry, including projective or hyperbolic geometry, in order to inform their teaching of proofs in high school geometry
- Learn the art of probabilistic and statistical thinking
- Depending on the students' interests, learn more about solving differential equations and applied mathematics
- Study the logical foundations of mathematics in set theory or through construction and development of the number systems
Master of Science in Computational Data Science (M.S.)
After graduation, a student should be able to:
- Synthesize data analysis principles across the statistical and computer sciences in topics such as pattern analysis, prediction, and big data processing.
- Construct data science algorithms, including derivation and programming implementation in a variety of languages and platforms (C++, Python, Java, SAS, R, Matlab).
- Be able to assess new programming language trends in industry, by gaining solid background in computing and algorithmic thinking.
- Differentiate the processes from "raw data to outcome", which spans from considering the domain-specific constraints and charactertistics (e.g., static vs. sequence, sparsity, dimensionality, etc.) to efficient method implementation, as software with desired specifications.
- Integrate advanced knowledge in a broad range of related topics, such as survival analysis in Computer Science.
- Assess different solutions to specific data-specific problems.
- Summarize state-of-the-art data science methods and applications in scientific project reports and software documentation.
Doctor of Philosophy in Mathematics (Ph.D.)
In addition to the Student Learning Outcomes for the M.S. degree, those who graduate with a Ph.D. degree in Mathematics will be able to:
- Demonstrate a basic understanding of the fundamental ideas underlying the basic mathematical disciplines.
- Demonstrate the ability to recognize significant research problems.
- Demonstrate the ability to analyze problems, reach research solutions, and transmit the fundamental ideas to others.
- Demonstrate a comprehensive knowledge in mathematical sciences through successful completion of a qualifying and preliminary examination.
- Document an original contribution to mathematics through independent experimental design, peer-reviewed publication of results, and presentation and defense of an original thesis.
Doctor of Philosophy in Biostatistics (Ph.D.)
In addition to the Student Learning Outcomes for the M.S. degree, those who graduate with a Ph.D. degree in Biostatistics will be able to:
- Demonstrate a basic understanding of the fundamental ideas underlying the basic mathematical disciplines.
- Demonstrate the ability to recognize significant research problems.
- Demonstrate the ability to analyze problems, reach research solutions, and transmit the fundamental ideas to others.
- Demonstrate a comprehensive knowledge in biostatistics through successful completion of a qualifying and preliminary examination.
- Document an original contribution to biostatistics through independent experimental design, peer-reviewed publication of results, and presentation and defense of an original thesis.
