Mathematics

MATH 1020 Contemporary Mathematics (MOTR MATH 120): 3 semester hours

Prerequisites: A satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course. This course presents methods of problem solving, centering on problems and questions which arise naturally in everyday life. Topics may include aspects of algebra, the mathematics of finance, probability and statistics, exponential growth, and other topics chosen from traditional and contemporary mathematics which do not employ the calculus. It is designed for students who do not plan to take calculus and may not be used as a prerequisite for other mathematics courses. Credit will not be granted for MATH 1020 if credit has been granted for MATH 1310, MATH 1800, MATH 1100, MATH 1102, or MATH 1105. Concurrent enrollment in MATH 1020 and any of these courses is not permitted. This course fulfills the University's general education mathematics proficiency requirement.

MATH 1021 Choice and Chance: 3 semester hours

Same as PHIL 1021. Prerequisites: A satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course. This course provides an introduction to inductive logic and the theory of probability in an organized and systematic way, so as to give students tools for more effective decision-making. We will introduce the probability calculus, basic concepts of utility theory, decision theory and different approaches to understanding probability. This course is designed to be accessible to students of all levels. This course fulfills the University's general education mathematics proficiency requirement.

MATH 1025 Geometry in the Real World: 3 semester hours

Prerequisites: A satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course. This course presents topics in geometry designed to enrich the student's understanding of mathematics. Geometry as it applies to the physical world and such fields as art, music, nature, motion, architecture and city planning will be examined. This course is designed to be accessible to students of all levels. This course fulfills the University's general education mathematics proficiency requirement.

MATH 1026 The Music of Math: 3 semester hours

Prerequisites: A satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course. This course presents topics in mathematics as they relate to music. Fundamental concepts of music such as intervals, scales, chords, tuning will be explored by developing an understanding of their mathematical underpinnings. An ability to read music in treble and bass clef is strongly recommended. This course fulfills the University's general education mathematics proficiency requirement.

MATH 1030 College Algebra (MOTR MATH 130): 3 semester hours

Prerequisites: A satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course, or approval of the department. This is a foundational course in math. Topics may include factoring, complex numbers, rational exponents, simplifying rational functions, functions and their graphs, transformations, inverse functions, solving linear and nonlinear equations and inequalities, polynomial functions, inverse functions, logarithms, exponentials, solutions to systems of linear and nonlinear equations, systems of inequalities, matrices, and rates of change. This course fulfills the University's general education mathematics proficiency requirement.

MATH 1035 Trigonometry: 2 semester hours

Prerequisites: MATH 1030 (may be taken concurrently) or a satisfactory score on the UMSL Math Placement Examination obtained at most one year prior to enrollment in this course. This course is a study of the trigonometric and inverse trigonometric functions with emphasis on trigonometric identities and equations.

MATH 1045 PreCalculus (MOTR MATH 150): 5 semester hours

Prerequisites: A satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course. This course is intended for students planning to take MATH 1800. It covers a range of topics including polynomials, logarithms, and complex numbers; functions and their graphs; systems of equations and inequalities; trigonometry; and more. fulfills the University's general education mathematics proficiency requirement. This course fulfills the University's general education mathematics proficiency requirement.

MATH 1100 Basic Calculus: 3 semester hours

Prerequisites: MATH 1030 or MATH 1045 or a satisfactory score on the UMSL Math Placement Examination obtained at most one year prior to enrollment in this course. This course introduces plane analytic geometry and basic differential and integral calculus with applications to various areas. No credit for Mathematics majors. Credit not granted for both MATH 1800 and MATH 1100.

MATH 1105 Basic Probability and Statistics: 3 semester hours

Prerequisites: MATH 1030 or MATH 1040 or MATH 1045 or a satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course or consent of the department. This course is an introduction to probability and statistics. Topics may include probability, descriptive statistics, discrete and continuous random variables and their distribution functions, sampling and sampling distributions, confidence intervals, and one-variable hypothesis testing. Credit will not be granted for more than one of MATH 1310, MATH 1320, and MATH 1105.

MATH 1150 Structure of Mathematical Systems I: 3 semester hours

Prerequisites: 45 hours of college credit and a satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course OR successful completion of MATH 1030 no more than 2 years prior to enrollment in this course. This course examines topics including problem solving, patterns, sets, numeration systems, whole numbers and operations, positive rational numbers and operations, and an introduction to variables and equations, with an emphasis placed on using multiple techniques for each of the aforementioned topics.

MATH 1320 Introduction to Probability and Statistics: 3 semester hours

Prerequisites: MATH 1030 or MATH 1045 or consent of instructor. The course will cover basic concepts and methods in probability and statistics. Topics may include descriptive statistics, probabilities of events, random variables and their distributions, sampling distributions, estimation of population parameters, confidence intervals and hypothesis testing for population means and population proportions, chi-square tests. A student may not receive credit for more than one of MATH 1310, MATH 1320 and MATH 1105.

MATH 1800 Analytic Geometry and Calculus I: 5 semester hours

Prerequisites: MATH 1030 and MATH 1035, or MATH 1045, or a satisfactory score on the UMSL Math Placement Examination, obtained at most one year prior to enrollment in this course, or consent of instructor. This course provides an introduction to differential and integral calculus. Topics may include limits, derivatives, related rates, Newton's method, the Mean-Value Theorem, Max-Min problems, the integral, the Fundamental Theorem of Integral Calculus, areas, volumes, and average values.

MATH 1900 Analytic Geometry and Calculus II: 5 semester hours

Prerequisite: MATH 1800. This course covers analytical geometry and additional aspects of calculus. Topics may include inverse functions, integration techniques, further applications of integration, parametric and polar equations, and infinite series, including Taylor series of functions.

MATH 2000 Analytic Geometry and Calculus III: 5 semester hours

Prerequisite: MATH 1900. Topics include vectors, cylindrical and spherical coordinates, vector-valued functions, arc length and curvature, functions of several variables, partial and directional derivatives, gradients, extrema, Lagrange multipliers, multiple integrals, change of variables, surface area, vector fields, Stokes' Theorem.

MATH 2010 Introduction to Inquiry Approaches to STEM Education (STEP I): 1 semester hour

Same as CHEM 2010, PHYSICS 2010, BIOL 2010, and SEC ED 2010. Prerequisites: Concurrent enrollment BIOL 1821, BIOL 1831, CHEM 1111, CHEM 1121, PHYSICS 2111, PHYSICS 2112, MATH 1800, or MATH 1900 or have a declared STEM major. Students who want to explore teaching careers become familiar with lesson plan development by writing, teaching and observing lessons in a local school class. Students build and practice inquiry-based lesson design skills and become familiar with and practice classroom management in the school setting. As a result of the STEP I experiences students should be able to decide whether to continue to explore teaching as a career and ultimately finishing the remainder of the WE TEACH MO curriculum leading to teacher certification. The classroom observations and teaching represent a major field component and requires at least one two hour block of free time during the school day once a week.

MATH 2011 Designing Inquiry-Based STEM Experiences (STEP II): 1 semester hour

Same as CHEM 2011, PHYSICS 2011, BIOL 2011, and SEC ED 2011. Prerequisites: BIOL 2010, CHEM 2010, PHYSICS 2010, MATH 2010, or SEC ED 2010. Students explore teaching careers, become familiar with STEM school setting through observing and discussing the school environment and by developing and teaching inquiry-based lessons.

MATH 2020 Introduction to Differential Equations: 3 semester hours

Prerequisite: MATH 2000. Topics will be chosen from: linear differential equations, equations with constant coefficients, laplace transforms, power series solutions, systems of ordinary differential equations.

MATH 2300 Introduction to Discrete Structures: 3 semester hours

Prerequisites: MATH 1100 or MATH 1800, and CMP SCI 1250. This course treats fundamental mathematical concepts in discrete structures useful for computer science. Topics include logic, sets, equivalence relations and partitions, functions, elementary number theory, cardinality, basic combinatorial methods, trees and graphs.

MATH 2450 Elementary Linear Algebra: 3 semester hours

Prerequisite: MATH 1100 or MATH 1900. An introduction to linear algebra. Topics will include complex numbers, geometric vectors in two and three dimensions and their linear transformations, the algebra of matrices, determinants, solutions of systems of equations, eigenvalues and eingenvectors.

MATH 2510 Structure of Mathematical Systems II: 3 semester hours

Prerequisites: MATH 1150. Topics include an introduction to probability, statistics, and displays of data; a study of elementary geometry, including points, lines, planes, angles, properties of triangles, properties of quadrilaterals, other 2- and 3-dimensional shapes; similarity; measurement and conversions; Pythagorean Theorem; perimeter; area; surface area, and volume. This course does not apply towards the elective requirements for any of the majors, minors or related areas in mathematics and statistics.

MATH 3000 Discrete Structures: 3 semester hours

Prerequisites: MATH 1800 or MATH 1100, and CMP SCI 1250 or equivalent. This course introduces fundamental concepts and important data structures in Discrete Mathematics and serves as an important foundation for subsequent courses in Computer Science. It provides a formal system on which mathematical reasoning is based, and various problem-solving strategies with emphasis on the algorithmic approach (both iterative and recursive). Topics include logic, sets, functions and relations; methods of proof, including mathematical induction; elements of number theory; order of growth and basic analysis of algorithms efficiency; recurrence relations; basic counting methods; graphs and trees. This course does not apply towards the elective requirements for any of the majors, minors or related areas in mathematics and statistics.

MATH 3250 Foundations of Mathematics: 3 semester hours

Prerequisites: MATH 1900 and CMP SCI 1250. The course will focus on developing an understanding of proofs and rigorous mathematical reasoning. Topics will include logic, sets, relations, functions, number theory, and counting methods.

MATH 3320 Applied Statistics: 3 semester hours

Prerequisites: MATH 1320. The course will cover topics including multiple regression, analysis of variance, generalized linear models, and applications of these methods. Using R for statistical analysis will be part of the course.

MATH 3520 Structure of Mathematical Systems III: 3 semester hours

Prerequisites: MATH 2510. Topics from MATH 1150 and MATH 2510 are continued. Other topics include integers and the real number system, relations and functions, coordinate system and linear equations, congruence, geometric constructions, geometric proofs, isometries, tessellations, and trigonometry. This course does not apply towards the elective requirements for any of the majors, minors or related areas in mathematics and statistics.

MATH 4005 Exploratory Data Analysis with R: 3 semester hours

Prerequisites: (MATH 1100 or MATH 1800) and (ANTHRO 3220/SOC 3220 or BIOL 4122 or CRIMIN 2220 or ECON 3100 or MATH 1320 or POL SCI 3000 or PSYCH 2201). This course covers data analysis methods with R. It introduces the basic goals and techniques of the data science process, methods of characterizing and visualizing data and building predictive and inferential models. R will be introduced at the beginning of the class and then used throughout the rest of the class.

MATH 4010 Financial Mathematics I: 3 semester hours

Prerequisites: MATH 1900 or MATH 1100, and MATH 1320 or SCMA 3300 (or equivalents). This course introduces the theory of interest, annuities (certain), annuities with differing pay periods, amortization schedules, and sinking funds.

MATH 4020 Financial Mathematics II: 3 semester hours

Prerequisite: MATH 4010. This course introduces the premium-discount formula for bonds, bond amortization, term structure of interest rates, and pricing theory for options.

MATH 4030 Applied Mathematics I: 3 semester hours

Prerequisite: MATH 2020 and MATH 2450. Topics chosen from Fourier series, special functions, partial differential equations, and boundary value problems.

MATH 4070 Introduction to Nonlinear Optimization: 3 semester hours

Prerequisites: MATH 1320, MATH 2000, MATH 2450 and (MATH 3000 or MATH 3250). This course will introduce the theory, methods, and applications of nonlinear optimization. It will cover convex functions, convex analysis, linear and quadratic programs, semidefinite programming and other optimization problems. Topics may include duality theory, algorithms of descent method, Newton's method and interior-point methods, and applications to signal processing, statistics and other fields will be covered. Credit cannot be earned for both MATH 4070 and MATH 5070.

MATH 4080 Introduction to Scientific Computation: 3 semester hours

Prerequisites: MATH 2000 and MATH 2450. This course will introduce fundamental algorithms in numerical linear algebra, matrix factorizations including SVD and QR, direct and iterative methods for solving linear systems, least squares problems and eigenvalue problems. Other topics covered will be chosen from numerical integration and differentiation, iterative methods for ODEs and PDEs, Discrete Fourier transform and FFT, spline smoothing and kernel smoothing. Credit cannot be earned for both MATH 4080 and MATH 5080.

MATH 4090 Introduction to High-dimensional Data Analysis: 3 semester hours

Prerequisites: MATH 1320, MATH 2000 and MATH 2450. This course introduces several advanced classical and modern techniques for modeling and analysis of high-dimensional datasets with low-dimensional structures. The topics covered in this course include principal component analysis, factor analysis, clustering-based methods, and sparse and low-rank recovery theory and algorithms. Credit cannot be earned for both MATH 4090 and MATH 5090.

MATH 4100 Real Analysis I: 3 semester hours

Prerequisites: MATH 3250, or CMP SCI 3130, or consent of instructor. This course provides an introduction to real analysis in one variable. Topics include the real number system, limits, continuity, differentiability, and sequences and series of functions.

MATH 4160 Complex Analysis I: 3 semester hours

Prerequisites: MATH 2000 or consent of the instructor. This course introduces complex numbers and their geometrical representation, point sets, analytic functions of a complex variable, complex integration, Taylor and Laurent series, residue theorem, and conformal mapping.

MATH 4200 Mathematical Statistics I: 3 semester hours

Prerequisites: MATH 1320 and MATH 2000. Introduction to the theory of probability and statistics using concepts and methods of calculus.

MATH 4210 Mathematical Statistics II: 3 semester hours

Prerequisites: MATH 4200. Continuation of MATH 4200. Sampling distributions, estimation theory, properties of estimators, hypothesis testing, NeymanPearson Theorem, likelihood ratio tests, introduction of analysis of variance and linear models. Basics of some nonparametric procedures.

MATH 4225 Introduction to Statistical Computing: 3 semester hours

Prerequisites: MATH 1320, MATH 2000 and MATH 2450. This course will introduce fundamental algorithms in Monte Carlo methods: random variable generation, Monte Carlo integration, Monte Carlo optimization, Markov chain Monte Carlo, Metropolis-Hastings algorithm, Gibbs sampler, Langevin algorithms and Hamilton Monte Carlo, perfect, iterated and sequential importance sampling. Other topics covered may include particle systems, hidden Markov models, parallel and cloud computing. Credit cannot be earned for both MATH 4225 and MATH 5225.

MATH 4250 Introduction to Statistical Methods in Learning and Modeling: 3 semester hours

Prerequisites: MATH 1320, MATH 2000 and MATH 2450. This course will introduce basic statistical principles and methods for modeling, inference, prediction and classification. The topics will be chosen from linear regression, basis expansion methods, kernel smoothing methods, model regularization, model selection and assessment, and other nonparametric methods. Credit cannot be earned for both MATH 4250 and MATH 5250.

MATH 4260 Introduction to Stochastic Processes: 3 semester hours

Prerequisites: MATH 4200. Basic theory and applications of stochastic processes. Markov chains, recurrent and transient states, stationary distributions, ergodic theorem, renewal processes, discrete martigales and stationary processes.

MATH 4350 Theory of Numbers: 3 semester hours

Prerequisites: MATH 2450 and either MATH 3000 or MATH 3250; or consent of instructor. This course examines the properties of integers, multiplicative functions, congruences, primitive roots, and quadratic residues.

MATH 4390 Topics in Probability and Statistics: 3 semester hours

Prerequisites: Consent of instructor. A seminar on special topics in probability and statistics to be determined by the interests of the instructor. May be repeated for credit provided different topics are studied.

MATH 4400 Introduction to Abstract Algebra I: 3 semester hours

Prerequisites: MATH 2450 and either MATH 3250 or CMP SCI 3130; or consent of instructor. This course introduces groups, rings, and fields, with an emphasis on groups and rings.

MATH 4450 Linear Algebra: 3 semester hours

Prerequisites: MATH 2450 and either MATH 3250 or CMP SCI 3130; or consent of instructor. This course focuses on topics selected from vector spaces, bases, linear transformations, matrices, canonical forms, eigenvalues, hermitian and unitary matrices, inner product spaces, and quadratic forms.

MATH 4460 Introduction to Coding Theory: 3 semester hours

Prerequisites: MATH 2450 and either MATH 3000 or MATH 3250. This course is an introductory course in coding theory. Topics may include linear codes, generator and parity check matrices, dual codes, weight and distance, encoding and decoding, and the Sphere Packing Bound; various examples of codes like the Hamming codes, Golay codes, binary Reed-Muller codes, and the hexacode; Shannon's theorem for the binary symmetric channel, upper and lower bounds on the size of linear and nonlinear codes; constructions and properties of finite fields, basic theory of cyclic codes; concepts of idempotent generator, generator polynomial, zeros of a code, and defining sets, special families of BCH and Reed-Solomon cyclic codes as well as generalized Reed-Solomon codes. Credit cannot be granted for both MATH 4460 and MATH 5460.

MATH 4470 Introduction to Statistical Data Analysis for GIS: 3 semester hours

Prerequisites: MATH 1320, MATH 2450 or consent of instructor. This course covers statistical concepts and techniques that are standard for solving geospatial problems. Emphasis will be placed on descriptive statistics and inferential statistics, with a view toward working with geographic and geospatial data. Topics may include geographical data characteristics, visualization of GIS data, mappings and spatial patterns, descriptive statistics for geospatial data, inferential spatial statistics, autocorrelation, point pattern analysis, area pattern analysis, mapping regression models, spatial statistics applications (disease transmission, racial bias, etc.). Credit cannot be earned for both MATH 4470 and MATH 5470.

MATH 4480 Introduction to Remote Sensing Digital Image Analysis: 3 semester hours

Prerequisites: MATH 2000 and MATH 2450, or consent of instructor. This course covers commonly-used techniques for remote sensing digital images. Specifically, it covers remote sensing image pre-processing techniques including: radiometric normalization and geometric correction, manipulating satellite data with different formats, image classification and land use change detection. This course focuses on core mathematical principles, with only a secondary look at implementation. Credit cannot be earned for both MATH 4480 and MATH 5480.

MATH 4500 Special Readings: 1-10 semester hours

Prerequisites: 6 credit hours at the Math 4000 level and consent of the instructor. Advanced topics in Mathematics. May be repeated for credit if the topic differs.

MATH 4550 Combinatorics: 3 semester hours

Prerequisites: MATH 2450 and either MATH 3000 or MATH 3250; or consent of instructor. This course introduces advanced counting methods including the use of generating functions for the solution of recurrences and difference equations. Additional topics may include: graphs and trees, combinatorial designs, combinatorial games, error-correcting codes, and finite-state machines.

MATH 4555 Topics in Math for the Teacher: 3 semester hours

Prerequisites: Consent of instructor. This course will cover various topics in Algebra, Analysis, and Geometry to deepen a teacher's understanding of the pre-collegiate Mathematics curriculum. It can be taken more than once for credit. Students may not receive credit for both MATH 4555 and MATH 5550.

MATH 4580 Mathematical Logic: 3 semester hours

Prerequisites: MATH 2450 and one of MATH 3250, CMP SCI 3130, or PHIL 4460; or consent of instructor. This course focuses on a study of the logic of mathematics by the axiomatic method, with a development of the propositional calculus and restricted predicate calculus emphasizing its application to the foundations of mathematics.

MATH 4660 Foundations of Geometry: 3 semester hours

Prerequisites: MATH 2450 and either MATH 3250 or CMP SCI 3130; or consent of instructor. This course focuses on a development of portions of Euclidean geometry from a selected set of axioms, including a discussion of consistency, independence, categoricity, and completeness of the axioms.

MATH 4670 Introduction to Non-Euclidean Geometry: 3 semester hours

Prerequisites: MATH 2000, MATH 2450, and either MATH 3250 or CMP SCI 3130; or consent of instructor. This course focuses on a summary of the history of the non-Euclidean geometries and a study of hyperbolic plane geometry.

MATH 4750 Introduction to Mathematics of Artificial Neural Networks: 3 semester hours

Prerequisites: MATH 1320, MATH 2000, and MATH 2450. This course provides an introduction to the mathematical ideas and techniques underlying the modern theory of artificial neural networks. Guidance and training for implementing practical applications are also provided. Topics may include fundamentals of supervised learning, testing, and validation for parametric statistical models, feedforward neural networks, forward propagation, activation functions, loss functions, batch/stochastic/mini-batch gradient descent, the backpropagation algorithm, preventing overfitting, basics of convolutional neural networks (CNNs), other specialized architectures. Credit cannot be earned for both MATH 4750 and MATH 5750.

MATH 4890 Topics in Mathematics: 3 semester hours

Prerequisite: Consent of instructor.

MATH 4995 Internship in Actuarial Science: 1-3 semester hours

Same as ECON 4995. Prerequisites: Junior standing and consent of program director. Supervised off-campus training in a private or public sector position in which the student applies the knowledge and skills learned in their actuarial science coursework. The internship is monitored by a faculty member and the student must provide a written report at the end of the project. This course may be repeated for a maximum of 6 credit hours.

MATH 5070 Nonlinear Optimization: 3 semester hours

Prerequisites: Graduate standing. This course will introduce the theory, methods, and applications of nonlinear optimization. It will cover convex functions, convex analysis, linear and quadratic programs, semidefinite programming and other optimization problems. Topics chosen from duality theory, algorithms of descent method, Newton's method and interior-point methods, and applications to signal processing, statistics and other fields will be covered. Topics are identical to MATH 4070 but material is covered at a greater depth and additional projects/assignments are required. Credit cannot be earned for both MATH 4070 and MATH 5070.

MATH 5080 Scientific Computation: 3 semester hours

Prerequisites: Graduate standing. This course will introduce fundamental algorithms in numerical linear algebra, matrix factorizations including SVD and QR, direct and iterative methods for solving linear systems, least squares problems and eigenvalue problems. Other topics covered will be chosen from numerical integration and differentiation, iterative methods for ODE's and PDE's, Discrete Fourier transform and FFT, spline smoothing and kernel smoothing. Topics are identical to MATH 4080 but material is covered at a greater depth and additional projects/assignments are required. Credit cannot be earned for both MATH 4080 and MATH 5080.

MATH 5090 High-dimensional Data Analysis: 3 semester hours

Prerequisites: Graduate standing. This course introduces several advanced classical and modern techniques for modeling and analysis of high-dimensional datasets with low-dimensional structures. The methods covered in this course include principal component analysis, factor analysis, clustering-based methods, and sparse and low-rank recovery theory and algorithms. Topics are identical to MATH 4090 but material is covered at a greater depth and additional projects/assignments are required. Credit cannot be earned for both MATH 4090 and MATH 5090.

MATH 5100 Real Analysis II: 3 semester hours

Prerequisites: MATH 4100. Introduction to measure and integration. Topics include the Riemann-Stieltjes integral, Lebesgue measure, measurable functions, the Lebesgue integral, Radon-Nikodym and Fubini theorems and the basics of Lp-spaces.

MATH 5225 Statistical Computing: 3 semester hours

Prerequisites: Graduate standing. This course will introduce fundamental algorithms in Monte Carlo methods: random variable generation, Monte Carlo integration, Monte Carlo optimization, Markov chain Monte Carlo, Metropolis-Hastings algorithm, Gibbs sampler, Langevin algorithms and Hamilton Monte Carlo, perfect, iterated and sequential importance sampling. Other topics covered may include particle systems, hidden Markov models, parallel and cloud computing. Topics are identical to MATH 4085 but material is covered at a greater depth and additional projects/assignments are required. Credit cannot be earned for both MATH 4225 and MATH 5225.

MATH 5250 Statistical Methods in Learning and Modeling: 3 semester hours

Prerequisites: Graduate standing. This course will introduce basic statistical principles and methods for modeling, inference, prediction and classification. The topics will be chosen from linear regression, basis expansion methods, kernel smoothing methods, model regularization, other nonparametric methods, and model selection and assessment. Topics are identical to MATH 4250 but material is covered at a greater depth and additional projects/assignments are required. Credit cannot be earned for both MATH 4250 and MATH 5250.

MATH 5320 Topics in Statistics and its Applications: 3 semester hours

Prerequisites: MATH 4210 or consent of instructor. The course studies classical and recently developed statistical procedures selected from areas including multivariate analysis, linear and non-linear models, nonparametric methods, and statistical learning. Emphasis is on applications of the procedures.

MATH 5460 Coding Theory: 3 semester hours

Prerequisites: Graduate standing. This course is an introductory course in coding theory. Topics may include linear codes, generator and parity check matrices, dual codes, weight and distance, encoding and decoding, and the Sphere Packing Bound; various examples of codes like the Hamming codes, Golay codes, binary Reed-Muller codes, and the hexacode; Shannon's theorem for the binary symmetric channel, upper and lower bounds on the size of linear and nonlinear codes; constructions and properties of finite fields, basic theory of cyclic codes; concepts of idempotent generator, generator polynomial, zeros of a code, and defining sets, special families of BCH and Reed-Solomon cyclic codes as well as generalized Reed–Solomon codes. Topics are identical to MATH 4460 but material is covered at a greater depth and additional projects/assignments are required. Credit cannot be granted for both MATH 4460 and MATH 5460.

MATH 5470 Statistical Data Analysis for GIS: 3 semester hours

Prerequisites: Graduate standing, MATH 1320, MATH 2450 or consent of instructor. This course covers statistical concepts and techniques that are standard for solving geospatial problems. Emphasis will be placed on descriptive statistics and inferential statistics, with a view towards working with geographic and geospatial data. Topics may include: geographical data characteristics, visualization of GIS data, mappings and spatial patterns, descriptive statistics for geospatial data, inferential spatial statistics, autocorrelation, point pattern analysis, area pattern analysis, mapping regression models, spatial statistics applications (disease transmission, racial bias, etc.). Credit cannot be earned for both MATH 4470 and MATH 5470.

MATH 5480 Remote Sensing Digital Image Analysis: 3 semester hours

Prerequisites: MATH 2000 and MATH 2450, or consent of instructor. This course covers commonly-used techniques for remote sensing digital images. Specifically, it covers remote sensing image pre-processing techniques, including radiometric normalization and geometric correction, manipulating satellite data with different formats, image classification, and land use change detection. This course focuses on core mathematical principles, with only a secondary look at implementation. Credit cannot be earned for both MATH 4480 and MATH 5480.

MATH 5500 Directed Readings: 1-6 semester hours

Prerequisite: Consent of instructor. Independent readings at an advanced level.

MATH 5550 Topics in Advanced Math for the Teacher: 3 semester hours

Prerequisite: Consent of instructor. This course will look at various topics in Algebra, Analysis, and Geometry that will deepen a teacher's understanding of the Mathematics of the precollegiate curriculum. It can be taken more than once for credit.

MATH 5600 Topics in Computation: 3 semester hours

Prerequisite: Consent of instructor. The course will cover various advanced topics in computation, and can be taken more than once for credit. Examples of such topics are: computer graphics, computer architecture, theories of language, analysis of operating systems, numerical geometry and computer aided design, etc.

MATH 5750 Mathematics of Artificial Neural Networks: 3 semester hours

Prerequisites: MATH 1320, MATH 2000, MATH 2450, and graduate standing. This course provides an introduction to the mathematical ideas and techniques underlying the modern theory of artificial neural networks. Guidance and training for implementing practical applications are also provided. Topics may include fundamentals of supervised learning, testing, and validation for parametric statistical models, feedforward neural networks, forward propagation, activation functions, loss functions, batch/stochastic/mini-batch gradient descent, the backpropagation algorithm, preventing overfitting, basics of convolutional neural networks (CNNs), other specialized architectures. Topics are identical to MATH 4750, but the material is covered at a greater depth, and additional projects/assignments are required. Credit cannot be earned for both MATH 4750 and MATH 5750.

MATH 5770 Advanced Topics in Nonlinear Optimization: 3 semester hours

Prerequisites: MATH 4070 or MATH 5070; or consent of the instructor. Topics chosen from theory and algorithms of Lagrange multipliers, algorithms for solving variational inequalities, forward-backward splitting algorithms and proximal alternating minimization algorithm for non-convex optimization problems.

MATH 5820 Topics in Algebra: 3 semester hours

Prerequisite: Consent of instructor. Topics selected from the theory of groups, rings, fields, algebras and other algebraic systems. May be taken more than once for credit with consent of department.

MATH 5890 Advanced Topics in Mathematics: 3 semester hours

Prerequisites: Consent of the instructor. The course will cover various advanced topics in mathematics, statistics, or data science. May be taken more than once if the topic differs.

MATH 6900 Masters Thesis: 1-6 semester hours

Prerequisite: Consent of instructor. Thesis work under the supervision of a faculty member. The course is designed for those students intending to present a thesis as part of their M.A. program. Students who do not write a thesis cannot apply MATH 6900 to a degree.

MATH 7990 Ph.D. Dissertation Research: 1-9 semester hours

Prerequisites: Completion of comprehensive examinations. May be taken for no more than nine hours.