Mathematics

Courses

MAT0099: Principles of Algebra

Credits 4.0
The course is designed to develop the basic concepts in algebra that are needed as background for intermediate algebra and college math. The approach emphasizes the relationship between arithmetic and algebra, using graphs and applications to motivate students and provide real-world examples. The course begins with signed numbers, proceeds to solving linear equations, and concludes with the Rectangular Coordinate System and graphs. A minimum grade of C is required to pass this course.

MAT1001: College Algebra I

Credits 4.0
The course is designed to develop the concepts needed for College Algebra II using graphs and applications to motivate students and provide real-world examples. The course covers the solution of systems of linear equations, exponents and polynomials, factoring, rational expressions, functions, and quadratic equations. MyMathLab or a comparable resource may be used for lecture, homework and assessment assignment delivery.

MAT1005: College Algebra II

Credits 4.0
College Algebra provides students with lecture and extensive practice in the concepts required as background for Pre-Calculus and Calculus. The course emphasizes the graphs and properties of functions in general, with emphasis on linear, quadratic, polynomial, rational, exponential, and logarithmic functions. MyMathLab or a comparable resource may be used for lecture, homework and assessment assignment delivery.

MAT1500: College Mathematics

Credits 4.0
College Mathematics covers the fundamentals of several areas of mathematics, including set theory, logic, geometry, graph theory, probability, and statistics. MyMathLab or a comparable resource may be used for lecture, homework and assessment assignment delivery.

MAT2058: Statistics

Credits 4.0

Statistics provides students with lecture and extensive practice in the concepts of descriptive and inferential statistics. The course emphasizes practical calculation and application. It begins with sample statistics and population parameters, proceeds to measures of central tendency, dispersion, and position, introduces the least-squares best-fit line and several key probability distributions, and concludes with the sampling distribution of sampling means, and hypothesis testing. MyStatLab or a comparable resource may be required in the course.