Mathematics

Study of mathematically related recreations, such as puzzles, constructions, logic, fractals, 2D and 3D puzzles. The content varies by semester. This course may not be used to satisfy SLO 5.

Sets, the real number system, other numerical systems, logic, geometry, probability, and statistics.

Topics covered include problem-solving, logic, sets, numeration systems, whole number operations, basic number theory, integers, rational numbers, proportional reasoning, decimals, percent, real numbers, introduction to algebraic reasoning, functions, and the Cartesian coordinate system. This course and MA 112 together should prepare students for the Praxis Core Assessment.

A course in basic mathematical concepts for prospective teachers. Topics covered include probability, statistics, and geometry. This course and MA 111 together should prepare students to take the Praxis Core Assessment.

Solving linear equations and inequalities in one or two variables, exponents and polynomials, factoring methods and solutions of quadratic equations, rational expressions, radical expressions, functions, and graphs. This course is designed to prepare students who have to take MA115 or MA116 later.

Real and complex numbers; linear, quadratic, rational, and absolute value equations and inequalities; variation; circles; linear, polynomial, rational, exponential, and logarithmic functions; and combinations of functions.

Mathematics for business and economics applications. Topics include linear, quadratic, exponential, and logarithmic functions; systems of linear equations; and mathematics of finance.

Trigonometric and inverse trigonometric functions and identities; trigonometric form of complex numbers; polar and parametric equations; vectors and the dot product; systems of linear equations and matrices; conic sections; and an introduction to sequences and series.

Introduction to propositional logic, predicate calculus, proofs, sets, functions, and mathematical induction.

Graphical presentation of data, measures of central tendency, dispersion and ranking, basic probability, the binomial and normal distributions, estimation of parameters, hypothesis testing, and measures of correlation. Technology will be used to represent and analyze data.

An introduction to axiomatic study and proof of foundational concepts of Euclidean geometry, trigonometry, coordinates and vectors, transformations, non-Euclidean and three-dimensional geometry. Technology for exploring, learning, and presenting geometry will be covered. This course is designed for secondary mathematics education majors.

Power, polynomial, rational, and trigonometric functions, limits, continuity, Intermediate Value Theorem, Extreme Value Theorem, derivatives, Mean Value Theorem, L’Hôpital’s Rule, applications of derivatives, and antiderivatives. Graphing calculators will be used in exploring concepts covered and in applications. (Offered in Fall Semester.)

Continuation of topics in MA 205 with exponential and logarithmic functions, integration, Fundamental Theorem of Calculus, applications of integration, integration techniques, and use of a computer algebra system to explore these topics.

An introduction to linear algebra in the context of finite-dimensional real vector spaces for application in other disciplines. Coverage includes systems of linear equations and matrix algebra, Gaussian elimination, determinants, linear independence, bases, dimension, linear transformations, eigenvectors, eigenvalues, eigenspaces, similarity, and orthogonality.

An introduction to discrete structures in mathematics. Topics covered include basic logic, algorithms, induction and recursion, counting methods, introduction to discrete probability, graphs, and trees, with the use of technology for exploring concepts and creating simulations.

Classifying differential equations, solutions and applications of certain first-order differential equations and of higher-order linear equations, Laplace transforms, and series solutions.

Topics include history of number and operations, algebra, geometry, calculus, probability, data analysis, statistics, discrete mathematics, and measurement systems. Ancient cultures, medieval Europe and the Renaissance, the era of Newton and Leibnitz, and the modern age will be discussed. Substantial writing is required.

This course provides instruction in basic facts on infinite series, Taylor polynomials and series, parametric equations, polar coordinates, vectors and geometry in space, and calculus on vector-valued functions.

The course provides instruction in basic facts on differentiation and integration of functions of several variables, limits and continuity, partial derivatives, differentials, extrema of functions of two variables, iterated integrals, triple integrals, Jacobians, vector analysis, Green's Theorem and Stoke's Theorem.

Basic axioms and theorems, conditional probability and independence, permutations and combinations, random variables and distributions, expectation and variance.

This course is a non-theoretical second course in statistics and data analysis. Course content includes inferences based on a single sample and two samples, analysis of variance, multiple regression, and model building, categorical data analysis, and nonparametric statistics.

Introductory number theory and group theory, with a brief introduction to rings, integral domains, and fields.

Topics include instructional planning, assessments, instructional strategies, classroom environment, dispositions of educators, technology, motivation and expectations for learners, content knowledge, problem-solving strategies, monitoring classroom learning, classroom management, current SC standards for mathematics instruction, and the SC Teaching Standards 4.0 rubric. Intended for prospective secondary mathematics teachers.

Estimation and hypothesis testing, regression and correlation, analysis of variance, nonparametric methods.

Cardinality, induction, ordered fields, Completeness Axiom, topology of the real numbers, compact sets, sequences, convergence of sequences, limit theorems for sequences, monotone and Cauchy sequences, limits and continuity of functions.

Methods of approximating solutions of equations, approximate differentiation and integration, and at least one of the following: numerical linear algebra, finite difference equations, or the Runge-Kutta method.

Completion of all required Math and Education coursework. Passing scores on all licensure exams (P in ED002), 2.75 cumulative GPA, "C" or higher in last field experience prior to Clinical Practice.

A non-theoretical, business applications oriented study of methods for quantitative analysis for decision-making. Topics studied include breakeven analysis, basic probability and probability distributions, time series analysis and forecasting, linear programming, and queueing models. This course is designed for graduate credit in the MBA program.