Mathematics

An introductory overview of the tools and techniques for extracting knowledge from data. Topics to be covered include Python basics, visualization, sampling, hypothesis testing, estimation, prediction, certainty assessment, and informed decision making. The necessary preparation is three years of high-school mathematics including algebra 2.

An intermediate course combining data, computation, and inferential thinking. Topics to be covered include data collection and cleaning, visualization, statistical inference, predictive modeling, and distributed computing.

This course extends the ideas of linear models to data sets used in professional settings. Topics includes linear and non-linear regression, logistic regression, discriminant analysis, principle component analysis, cross validation, and related topics. This course will use appropriate statistical software.

This course covers methodologies and algorithms to transform big data into meaningful insights. Topics include Hadoop Ecosystem, Hadoop MapReduce, MongoDB, Spark basics, SparkSQL and hands on real world applications.

A study of data science topics not ordinarily covered in the established courses. Prerequisite: consent of Data Science faculty.

An independent study of a data science topic not covered elsewhere.

Students will design, develop, implement, and effectively communicate an original data science project.

On-the-job supervised experience and study dealing with applications of data science.

This course investigates mathematics by introducing selected mathematical models and examining how they are applied to real world problems. Students are expected to use mathematical techniques in the application of the models studied in the course. The required preparation is MATH 060 or three years of high school mathematics.

A study of the fundamental concepts of algebra. Topics include: equations and inequalities polynomial, rational, exponential, and logarithmic functions and their graphs, and systems of linear equations.Prerequisites: This course requires either of these prerequisites MATH 060 - Intermediate Algebra (Minimum grade: 2.0 GPA Equivalent) or A score of 60 on test Intermediate Alg Placement Test - CAT, unless student meets Algebra College Level placement Corequisites: Math 090 if prerequisite placement score is not met. Math 090 section number and Math 110 section number must be the same.

Solving systems of linear equations, matrix operations, and an introduction to linear programming, including the simplex method, mathematics of finance, counting techniques, and probability. The required preparation is MATH 110 or three years of high school mathematics.

Trigonometry, both circular functions and right triangle, trigonometric equations, logarithms, exponential functions, and complex numbers. The required preparation is MATH 110 or three years of high school mathematics, not including trigonometry. Students who do not meet the stated requirements may be dropped from the course.

This is the mathematics content course for elementary education majors, which focuses on the content areas that must be taught at the elementary school level. Topics include problem solving, numeracy, discrete math, probability, statistics, and geometry. An understanding of the underlying mathematical concepts is developed to allow students to master the associated mathematical procedures.

A detailed study of the mathematics needed for calculus. Concepts are presented and explored from symbolic, graphical, and numerical perspectives. Basic concepts covered include polynomial, rational, exponential, logarithmic, and trigonometric functions, complex numbers, linear systems, numerical patterns, sequences and series. Students must have passed Math 060 with a B- or better, or Math 110 with a C- or better, or met one of the other stated prerequisites. Students who do not meet the stated requirements may be dropped from the course.

Differential calculus of elementary functions, including applications. Introduction to integration. The required preparation is MATH 125 or MATH 135 or three years of high school mathematics including trigonometry.

A continuation of Calculus I to include further techniques of integration and applications, Taylor approximations, sequences and series, plane analytical geometry, parametric equations, including polar coordinates. Students who do not receive a grade of C- or better in Math 150 (or equivalent) may be dropped from the course.

Introduction to measures of central tendency, measures of dispersion, frequency distributions, large and small samples, testing of hypotheses, and correlation analysis. Use of computers in statistical analysis. The required preparation is MATH 110 or three years of high school mathematics.

Use of statistical software including SPSS and MINITAB. Graphical and numerical methods of summarizing data, hypothesis testing, regression analysis, ANOVA, and other statistical procedures. Check the validity of statistical model assumptions. The required preparation is completion or enrollment in MATH 200 or equivalent or familiarity with statistical procedures.

Use of statistical software R for data analyses. Graphical and numerical methods of summarizing data, hypothesis testing, regression analysis, ANOVA, and other statistical procedures. Check the validity of statistical model assumptions. The required preparation is completion or enrollment in Math 200 or equivalent, or familiarity with statistical procedures.

Vectors and the geometry of two and three space, functions of several variables, differentiability, arc length and surface area, extrema and Lagrange multipliers, multiple integration, line and surface integrals, and the theorems of Green, Gauss, and Stokes. Students who do not receive a grade of a C- or better in Math 151 (or equivalent) may be dropped from the course.

The postulation systems of geometry, including Euclidean and non-Euclidean geometries, projective and affine geometry. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

The integers, including Peano postulates, divisibility, congruencies, Diophantine equations, and continued fractions. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

The nature of mathematics, the axiomatic method, the theory of sets, the real number continuum, and various viewpoints on the foundations of mathematics. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

A survey of some of the techniques of combinatorials mathematics and their application. Topics include connectivity, planarity and colorability of graphs, graph isomorphisms, enumeration techniques, recurrence relations, and generating functions. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

Finite differences and applications; interpolation formulas; inversion of matrices; numerical methods of solution of equations; numerical differentiation and integration. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

Exact solutions and applications of differential equations. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

Matrices and determinants with applications to vector spaces (linear transformations and eigenvalues) and the solution of systems of linear equations. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

Several types of optimizing techniques, including linear programming, simulations, applications of probability, and dynamic programming.

A study of different topics in mathematics. See current course schedule for topic listing when offered.

Independent study of mathematical topics not ordinarily covered in the established courses. May be repeated.

An introduction to calculus of probabilities and mathematical statistics, including discrete and random variables, mathematical expectation, probability distributions, sampling, hypothesis tests, regression, and correlation. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

Topics may include groups, rings, fields, or fields. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

A theoretical investigation of the real numbers. Topics include sequences, series and convergence, limits and continuity of functions, differentiation, and integration. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

Partial differential equations of physics and engineering including Laplace, heat and wave equations, Fourier series methods and the methods of separation of variables. Additional topics may include Sturm-Liouville problems, Greens functions, and the method of characteristics. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

The algebra of complex numbers, analytic functions, mapping properties of the elementary functions, Cauchys Theorem, Cauchys integral formula and residues. Students must earn a grade of C- or better in all prerequisite courses. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

This course is designed to acquaint the student with current research in mathematics by a review of current mathematical literature sources. Students integrate and synthesize their backgrounds by presenting a problem solving or research project. The Department of Mathematics & Computer Science reserves the right to remove students from the course who do not meet the course prerequisites.

A study of more advanced topics in mathematics not normally provided as part of the curriculum.

On-the-job supervised experience and study dealing with applications of mathematics.

An introduction to mathematical logic. Topics include: Sentential logic, the predicate calculus, the statement calculus and its completeness theorem, first order theories, consistency and completeness, and Godels Theorem. This course meets CECP Guidelines.

Number theory, which is one of the most ancient branches of mathematics and continues to be an active area of research, is the study of integers, the most basic structure of mathematics, and many of their fascinating properties. For example, it has a major recent day application in communications and cryptography. Topics include proof by induction, divisibility, primes, uniqueness of factorization, congruencies, Chinese Remainder Theorem, Cryptography, Pythagorean triples and other Diophantine equations, Pells Equation, primarily testing, factoring methods, primitive roots, perfect numbers, rational versus irrational, and continued fractions, quadratic congruencies, and quadratic reciprocity. The required preparation for this course is an undergraduate major in mathematics or mathematics education.

An extension of the usual material presented in an undergraduate course in Discrete Mathematics. Topics will include: coding theory, Polya enumeration, scheduling and bin packing, and combinatorial games. A current computer software package will be utilized to explore these topics. The required preparation for this course is an undergraduate major in mathematics or mathematics education.

This course is designed to give students both the theoretical and practical aspects of statistics. Topics include probability distributions of discrete and continuous random variables, mathematical expectations, multivariate distributions, correlations, confidence intervals, hypothesis testing, linear regression, and use of technology. The required preparation for this course is an undergraduate course in statistics, and an undergraduate major in mathematics or mathematics education.

A first graduate course in abstract algebra. Topics may include: groups, subgroups, quotient groups, homomorphisms, isomorphisms, group actions, direct and semidirect products, the Sylow theorems, rings, integral domains, fields, field extensions, and Galios Theory. The required preparation for this course is an undergraduate major in Mathematics or Mathematics Education

This course reviews Euclidean, synthetic, analytic, plane and solid geometry, then compares Euclidean geometry to the more recent developments in geometry dealing with non-metric properties. Projective geometry, affine geometry, and topological geometry are used as examples of non-Euclidean systems. The required preparation for this course is an undergraduate major in mathematics or mathematics education.

Topics include: metric spaces, compactness, countability, convergence, continuity, uniform convergence and continuity, differentiation, and integration. The objective of this course is to provide a foundation in the mathematical analysis behind the Calculus. The required preparation for this course is an undergraduate major in Mathematics or Mathematics Education

An extension of the usual material presented in an undergraduate course in Linear Algebra. Topics include vector spaces and linear transformations, algebra of polynomials, invariant subspaces, LU, QR and singular value decompositions, symmetric, positive definite, and Hermitian matrices, inner product spaces, and the spectral theorem. The required preparation for this course is an undergraduate major in mathematics or mathematics education.

A study of more advanced topics in mathematics not normally provided as part of the curriculum.

Advanced interdisciplinary study of Mathematics. Student may use interdisciplinary research involving Mathematics, and/or Statistics, projects, paper review, or other experiences outside the classroom in real world situations as credit for prior learning towards the 18 graduate credits requirement in Mathematics.