Department of Mathematics
The Department of Mathematics offers courses leading to the Master of Science degree in Statistical Analytics, Computing and Modeling (SACM). The program has two concentrations; Statistics and Applied Mathematics. In each case, the student can choose a Thesis or Project exit option.
Graduate level courses may also serve to provide a supporting field for other majors.
Mathematics (MATH)
MATH 5305 Graduate Research Project 3 SCH (3)
A Graduate Research Project must be completed and submitted to the Graduate Office for a grade to be assigned, otherwise IP notations are recorded. This course is specifically designed for Plan II and Plan III students. Prerequisite: departmental approval.
MATH 5306 Thesis 3 SCH (3)
Designed for thesis option students. The course requires completion of thesis research. Prerequisite: departmental approval. May be repeated for maximum of 6 semester hours.
MATH 5321 Real Analysis 3 SCH (3-0)
Lebesgue integration and Lebesgue measure. LP spaces. Differentiability properties of monotone functions.
MATH 5325 Advanced Linear Algebra 3 SCH (3-0)
Vector spaces and linear transformations, orthogonality, eigenvalues, and numerical methods. Prerequisite: consent of the instructor.
MATH 5340 Matrix Methods Linear Models 3 SCH (3-0)
Common matrix methods in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; the distribution of quadratics forms. Prerequisite: STAT 4303 and MATH 3340 or equivalents.
MATH 5341 Abstract Algebraic Theories 3 SCH (3-0)
Groups and their generalizations. Homomorphism and isomorphism theorem. Direct sums and products. Linear spaces and representations. Field extensions and Galois groups. Prerequisite: MATH 4340 or its equivalent.
MATH 5360 Analytic Decision Theory 3 SCH (3-0)
Introduction to mathematical decision theory and game theoretic analysis. Classification of games, definitions in game theory, sequential-/simultaneous-move games, pure and mixed strategies, equilibrium concepts and matrix games. Prerequisite: MATH 3340 or equivalent.
MATH 5374 Numerical Analysis 3 SCH (3-0)
Underlying principles of numerical analysis. Topics include: finite differences and interpolation, numerical differentiation and integration, solving algebraic and transcendental equations, computations with matrices, the method of lease squares, and numerical solutions of differential equations. Attention is given to the solutions of problems using computer. Prerequisite: MATH 4341 or equivalent.
MATH 5390 Advanced Topics in Math 1-3 SCH (1-3)
Different areas of advanced mathematics with emphasis on rigor, critical reasoning and the concept of proof. May be repeated as topic changes.
Statistics (STAT)
STAT 5305 Graduate Research Project 3 SCH (0-3)
Designed for project option students. A Graduate Research Project must be completed and submitted to the Graduate Office for a grade to be assigned, otherwise S/U (Satisfactory/Unsatisfactory) notations are recorded. Prerequisite: departmental approval.
STAT 5306 Thesis 3 SCH (0-0-3)
Designed for thesis option students. The course requires completion of thesis research. Prerequisite: departmental approval. Maximum credit applicable towards the degree is 6 semester hours.
STAT 5332 Big Data and Computing 3 SCH (3-0)
Introduction to use of SAS (and R)/PC statistical software, including data entry, data summaries, descriptive statistics, and interpretation of SAS (and R) output for some standard statistical procedures. Prerequisites: graduate standing and approval of instructor.
STAT 5344 Predictive Analytics 3 SCH (3-0)
STAT 5346 Design of Experiments 3 SCH (3-0)
Hypothesis testing, principles of design of an experiment, t-test, completely randomized design, randomized block design, multiple comparison techniques, factorial designs, random effect models, fixed effect models, BIBD, nested designs, analysis of covariance and split plot design. Prerequisite: STAT 4301 or STAT 4303 or equivalent.
STAT 5350 Probability for Analytics 3 SCH (3-0)
Mathematical treatment of probability distributions, probability concepts and laws; sample spaces, combinations and permutations, Bayes' theorem, discrete/continuous random variables, expected value, distribution of functions of random variable, two-dimensional variables, central limit theorem; t, F, and chi-square distributions. Prerequisite: STAT 4301 or STAT 4303 or equivalent.
STAT 5351 Inferential Analytics 3 SCH (3-0)
Theory of estimation and hypothesis testing, maximum likelihood, method of moments, likelihood ratio tests, consistency, bias, efficiency and sufficiency. Prerequisite: STAT 5350 or equivalent.
STAT 5361 Multivariate Statistics 3 SCH (3-0)
STAT 5370 Survey Sampling Analytics 3 SCH (3-0)
Survey sampling from initial planning phases through collection and storage of the data; simple random sampling, stratified random sampling, auxiliary information, estimators, chi-square contingency table analysis for two and three way tables, handling of small expected frequencies, matched pairs, measures of association; use of statistical software on big survey data. Prerequisite: STAT 4301 or STAT 4303 or equivalent.
STAT 5374 Survey Models Social Science 3 SCH (3-0)
Sensitive data and privacy issues in survey sampling. Randomized response models and variations. Estimation of prevalence of two or more sensitive characteristics. Use of Cramer-Rao lower bound of variance. Measures of protection of respondents. Models using complex designs. Prerequisite: PSYC/SOCI 3381.
STAT 5375 Operations Research 3 SCH (3-0)
Geometric linear programming, the Simplex method, duality theory, sensitivity analysis, project planning and integer programming. Optional topics include, but are not limited to: the transportation problem, the upper bounding technique, the dual Simplex method, parametric linear programming, queuing theory, decision analysis, and simulation. Prerequisite: Any introductory course in linear algebra.
STAT 5390 Advanced Topic in Statistics 3 SCH (3-0)
Different areas of advanced statistics will be covered at separate offerings of this course. Topics include sampling techniques, multivariate analysis, quality control techniques. May be repeated once. Prerequisite: 6 semester hours of advanced statistics or the equivalent.
Fee: $15.00
Statistical Analytics, Computing and Modeling (SACM), M.S.
This program is designed to provide the student with competency in the major areas of statistical and mathematical application, a working knowledge of mathematical and/or statistical software and enough theoretical background to serve as a foundation for continued professional development.
The Master of Science in Statistical Analytics, Computing and Modeling (SACM) has two tracks, a Statistics Concentration, and an Applied Mathematics Concentration. In each case, the student can choose the Thesis option (Total 30 SCH) or the Project Option (Total 36 SCH).
A student entering the program is expected to have completed at least 6 semester hours of advanced mathematics beyond multivariate calculus and differential equations. Students lacking these prerequisites may be admitted conditionally.
Thesis Option
The thesis option requires 30 SCH to complete the M.S. degree of which 24 hours must be from core courses including Thesis. Elective courses comprise 6 hours of the curriculum. Students have the flexibility to select the elective hours from a list of courses to meet degree requirements. Elective hours may be taken from other disciplines with advisor's approval.
Project Option
The project option requires 36 SCH to complete the M.S. degree of which 21 hours must be from core courses including Project. Elective courses comprise 15 hours of the curriculum. Students have the flexibility to select the electives hours from a list of courses to meet degree requirements. Elective hours may be taken from other disciplines with advisor's approval.
Applied Mathematics Concentration
Code | Title | Semester Credit Hours |
---|---|---|
Required Courses | 15 | |
Advanced Linear Algebra | ||
Numerical Analysis | ||
Real Analysis | ||
Advanced Topics in Math 1 | ||
Advanced Topics in Math 2 | ||
Thesis Option | 30 | |
MATH 5306 | Thesis (This course must be taken twice for six semester credit hours.) | 6 |
Elective Courses | 9 | |
Project Option | 36 | |
MATH 5305 | Graduate Research Project | 3 |
Elective Courses | 18 |
Code | Title | Semester Credit Hours |
---|---|---|
Elective Courses | ||
Select 9 hours (thesis option) or 18 hours (project option) from the following or closely related field with advisor's approval. | ||
MATH 5340 | Matrix Methods Linear Models | 3 |
MATH 5341 | Abstract Algebraic Theories | 3 |
MATH 5360 | Analytic Decision Theory | 3 |
MATH 5390 | Advanced Topics in Math 3 | 3 |
- 1
Topic in Differential Equations with Applications
- 2
Topic in (Applied) Modern Algebra
- 3
May be repeated if a different topic
Statistics Concentration
Code | Title | Semester Credit Hours |
---|---|---|
Required Courses | 18 | |
Advanced Linear Algebra | ||
Numerical Analysis | ||
Probability for Analytics | ||
Inferential Analytics | ||
Big Data and Computing | ||
Predictive Analytics | ||
Thesis Option | 30 | |
STAT 5306 | Thesis | 6 |
Elective Courses | 6 | |
Project Option | 36 | |
STAT 5305 | Graduate Research Project | 3 |
Elective Courses |
Code | Title | Semester Credit Hours |
---|---|---|
Elective Courses | ||
Select 6 hours (thesis option) or 15 hours (project option) from the following or closely related field with advisor's approval. | ||
STAT 5361 | Multivariate Statistics | 3 |
STAT 5346 | Design of Experiments | 3 |
STAT 5370 | Survey Sampling Analytics | 3 |
STAT 5374 | Survey Models Social Science | 3 |
MATH 5340 | Matrix Methods Linear Models | 3 |
MATH 5360 | Analytic Decision Theory | 3 |
Planned Course Offerings
This section provides a comprehensive list of graduate courses offered by the Department of Mathematics, along with a two-year schedule indicating when each course is expected to be available. Please note that course offerings and scheduling are subject to change based on faculty availability and student demand. To ensure steady progress toward degree completion, students are strongly encouraged to work closely with their advisor to develop a personalized academic plan.
Mathematics (MATH)
Course | Fall 2025 | Spring 2026 | Fall 2026 | Spring 2027 |
---|---|---|---|---|
MATH 5305 | X | X | X | X |
MATH 5306 | X | X | X | X |
MATH 5321 | X | X | ||
MATH 5325 | X | X | X | X |
MATH 5340 | X | X | X | X |
MATH 5341 | X | X | ||
MATH 5360 | X | X | ||
MATH 5374 | X | |||
MATH 5390 | X | X | X | X |
Statistics (STAT)
Course | Fall 2025 | Spring 2026 | Fall 2026 | Spring 2027 |
---|---|---|---|---|
STAT 5305 | X | X | X | X |
STAT 5306 | X | X | X | X |
STAT 5332 | X | X | X | X |
STAT 5344 | X | X | ||
STAT 5346 | X | X | ||
STAT 5350 | X | X | ||
STAT 5351 | X | X | ||
STAT 5361 | X | X | ||
STAT 5370 | X | X | ||
STAT 5375 | X | |||
STAT 5390 | X | X | X | X |
Marketable Skills
Texas A&M University-Kingsville is dedicated to equipping graduate and doctoral students with the advanced marketable skills necessary for professional and academic excellence beyond the university setting. These skills encompass a range of high-level interpersonal, analytical, and applied competencies that are sought after in today’s competitive workforce.
Our graduate programs are structured to cultivate these capabilities through rigorous academic inquiry, experiential learning, faculty-mentored research, professional internships, and opportunities for scholarly and community engagement.
Below are the marketable skills cultivated through the department's graduate academic program.
Statistical Analytics, Computing and Modeling, M.S.
- Effective communication
- Analytical and logical reasoning
- Use of statistical computer software
- Data collection, analysis, and interpretation
- Ability to carry out research independently