Help student develop skills, strategies and reasoning required to succeed in mathematics. Include the study of numeracy and real number system; algebraic concepts, notation and reasoning; quantitative relationships; mathematical models and problem solving.

Fundamental Math (3) Designed to provide students with the concepts and skills necessary for successful performance in college level mathematics. Assists students in passing state-required tests. Provides the academic foundation for success in MATH 131. Three hours of lecture and one hour of laboratory per week.

Analytical Math (3) Designed to provide students with the necessary mathematical foundation to pass freshman level mathematics courses. Assists students in passing state-required tests. Three hours of lecture and one hour of laboratory per week.

Calculus and Analytic Geometry III (4) Sequences, infinite series, conic sections, polar coordinates, two-dimensional and three-dimensional vectors, parametric equations, partial differentiation, and multiple integrals. Four hours of lecture per week. Prerequisite: MATH 242.

Important methods of solution of ordinary differential equations of the first order and of higher orders with applications to geometry and physics.

Transitional mathematics course toward the study of advanced mathematics. Various topics in the foundations of mathematics discussed.

Graph theory has been applied to many fields including other branches in mathematics, chemistry, biology and so on. With the current intensive interests in network systems, graph theory becomes even more popular. This course introduces some major topics in graph theory. More specifically, it discusses degrees, isomorphic graph, trees, connectivity, traversability, coloring graphs. If time allows, we will also discuss digraph, matching and factorization.

Logic and postulates relating to geometries. Modern plan geometry as developed from Euclidean geometry, measurement, and metric system. Properties of geometric figures, congruence, theory of parallel lines, and non-euclidian geometry.

Introduction to mathematical systems such as groups, rings, and fields.

Selected topics in applied differential equations (including transform techniques), linear programming, numerical methods, and statistics with emphasis on applications to the solution of problems in science and engineering.

Applied Mathematical Analysis (3) Vector analysis; algebra and geometry of vectors; vector differential and integral calculus; theorems of Green, Gauss, and Stokes. Three hours of lecture per week. Prerequisite: MATH 314.

The History of Mathematics (3) General view of the development of the elementary branches of mathematics; growth of higher mathematics in the eighteenth and nineteenth centuries. Three hours of lecture per week. Prerequisite: Twelve credits of college mathematics.

This course introduces some of the high-level computing languages and software that are widely used in industry and universities. These software are extremely efficient on matrix operations, and also they focus on numerical computing in interactive environment. In this course, we focus on introducing MATLAB and R language, and give a brief tour of Mathematics. The aim of the course is to have students to learn what these three pieces of software can do and how they can use the tools for their own computing purposes.

Concepts and Structure of Mathematics (3) Structure of the number system, elements of set theory, properties of real numbers, and basic concepts of mathematical systems. Presented for nonmajors. Three hours of lecture per week. Prerequisite: Consent of the instructor.

Applications of various mathematical topics and mathematical needs of people in some of the trades, professions, and scientific disciplines.

The real number system; elementary point set theory; sequences and series; continuity; possibly topics from differentiation and integration.

Introduction to Complex Analysis (3) Complex numbers and complex geometry; limits, continuity, derivatives, and the Cauchy-Riemann equations; analytic and harmonic functions; Cauchy's Integral Theorem and its consequences. Three hours of lecture per week. Prerequisites: MATH 314 and MATH 331.

Linear Operators: Linear first order equations; the wave equation; the hear equation; Laplace's Equation; Green's Function and Sturm-Liouville problems; Fourier Series; Numerical Solutions.

Topics include metric spaces, connectedness, and compactness. The topology of Euclidean spaces discussed in detail as well as its generalization to non-metric topological spaces.

Computer Arithmetic and associated error analysis. Solution of non linear equations. Interpolation and approximation methods. Numerical differentiation and integration. Initial value problems for ordinary differential equations.

This course introduces theory and applications for statistics learning techniques including linear and logistic regression, classification and regression trees, random forests and neural networks. R programming will be used throughout the course.

This course introduces theory and applications for statistics learning techniques including maximal marginal classifiers, support vector machines, K-means and hierarchical clustering, and re-sampling methods. R programming will be used throughout the course.

This course is intended as comprehensive concepts-centric biostatistics primer. Those who complete the course will be able to read and respond to the scientific literature, including the Methods and Results sections, biological science, and related fields. Successful learners will also be prepared to participate as part of a research team in biological science and related fields. R programming will be used throughout the course.

Topics in Mathematics I (3) New developments and trends in mathematics discussed. Three hours of lecture per week. Prerequisite: Consent of the instructor.

Introduction to probability and statistical inference making use of the calculus developed in MATH 241 and MATH 242.

Moments of distributions and Stieltjes integral; joint density functions; conditional means; moment generating functions; sequences of random variables; distribution theory; and hypothesis testing.

Group theory; Lagrange's Theorem; Isomorphism Theorem; Cayley's Theorem; rings and fields.

Independent Study: Undergraduate (3) Intensive study of a topic in mathematics under the direction of a faculty member. Prerequisites: Senior standing and consent of the instructor.

This course will combine ideas from different areas of mathematics with emphasis on current topics of interest and serve as a capstone course for all mathematics majors. topics vary at instructor's discretion. The course will include student presentations, written projects, mathematical reasoning, problem solving and senior exit exam.

Seminar (3) Various topics in mathematics discussed. Three hours of lecture per week. Prerequisite: Consent of the instructor.

Concise overview of elementary algebra, including progressions, exponents, radicals, quadratic equations, binomial theorem, inequalities, absolute values, and mathematical induction.

Definitions and relations of the six trigonometric functions, proofs of formulas, solutions of triangles, trigonometric identities and equations, inverse trigonometric functions, vectors, and applications related to these topics.

Presentation of mathematical theories and approaches as applied to business and economics.

Limits and continuity, derivatives, graphing and optimization, exponential and logarithmic functions, antiderivatives, integration, applications to management, economics, and business.

Contemporary Mathematics is a course designed for liberal and fine arts, non-mathematics, and non-business majors. It will provide knowledge of the nature of mathematics as well as training in mathematical thinking and problem solving. Topics may include logic and mathematics reasoning, sets, problem solving, applications, networks, graphs, probability, statistics, geometry, mathematics of finance, and number theory.

Contemporary Mathematics is a course designed for liberal and fine arts, non-mathematics, non-science, and non business majors. It will provide knowledge of the nature of mathematics, as well as training in mathematical thinking and problem solving. Topics include statistics, probability, combinatiatorics, and game theory. Emphasis will be given to methods and models utilizing these topics in real world applications.

Basic statistics topics presented for students planning to work in health-related fields.

Sets, functions, logic, numeration theory, advanced definition perspectives, arithmetic operations (properties and algorithms), rational numbers, system of real numbers, and mathematical applications. Problem solving emphasized.

Basic concepts and methods of probability, statistics, and geometry, including discrete probability, random events, and conditional probability. Analysis of data, informational display, measurement, and geometry (as approached through similarity and congruence, coordinates, and transformations). Problem solving emphasized.

A course designed to prepare math, computer science, and engineering majors for a background in abstraction, notation, and critical thinking for the mathematics most directly related to computer science. Topics include: logic, relations, functions, basic set theory, countability and counting arguments, proof techniques, mathematical induction, combinatorics, theory, and mathematical proof techniques.

Designed to prepare students for the study of MATH 241. Elementary functions that are differentiated and integrated in calculus stressed, including polynomial, rational, algebraic, exponential, logarithmic, and trigonometric functions.

Introduces and provides models for application of the concepts of vector algebra. Topics include finite dimensional vector spaces and their geometric significance; representing and solving systems of linear equations using multiple methods, including Gaussian elimination and matrix inversion; matrices; determinants; linear transformations; quadratic forms; eigenvalues and eigenvector; and applications in science and engineering.

Important methods of solution of ordinary differential equations of the first order and of higher orders with applications to geometry and physics.

This course covers elementary functions including polynomial, rational, algebraic, exponential, logarithmic, and trigonometric functions.

Inequalities, functions, graphs, straight lines, linear equations, limits, continuity, differentiation, maximum-minimum problems, mean value theorem, related rates, and indefinite integrals.

Definite and indefinite integrals, techniques of integration, transcendental functions, and applications of the definite integral.

Sequences, infinite series, conic sections, polar coordinates, two-dimensional and three-dimensional vectors, parametric equations, partial differentiation, and multiple integrals.

This course introduces probability which forms the foundation for understanding statistics, randomness and uncertainty. This course covers discrete and continuous probability distributions, random variables and their distributions, cumulative distribution functions, expectation, variance and covariance. R will be used through out the course.

This course introduces graphical and descriptive methods in statistics, probability and distributions, sampling, estimation, hypothesis testing, regression, exploratory and diagnosis methods, and also discusses analysis of variance if time allows.

This is the second part of a two-semester course in Introduction to Real Analysis. Topics include real number system; sequences and series; limit, continuity and differentiation; the Riemann integral; sequences and series of functions; elementary metric space theory including compactness, connectedness and completeness; differentiation and integration of functions of several variables.

This course is intended for undergraduates to introduced student of mathematical proofs in Linear systems of equations, matrices, determinants, vector spaces and linear transformations, eigenvalues and eigenvectors..

Continuation of MATH 4377, Determinants, eigenvalues, eigenvectors, and diagonalization, canonical forms, and inner product and norm, Gram-Schmidt process.