Mathematics Courses at Ashford University
These math courses can be essential to your business career. Taken in programs such as the Master of Accountancy or the Master of Business Administration (MBA), you will expand your mathematics knowledge and learn to perform computations in various numerations systems from ancient to modern. You will also learn to utilize algorithms for solving algebraic equations and use algebraic logic and methods to solve problems.
Mathematics Class Descriptions and Credit Information
MAT 221 Introduction to Algebra
This course establishes a strong base for an Algebraic exploration of mathematical topics. Student understanding is built up through learning the basics of real numbers and Algebra terminology, writing, solving, and graphing equations, and manipulating polynomials through various operations. Students will develop a familiarity and ease of working with the language and notation of Algebra while learning to think logically through algorithms and solving methods. Emphasis will be placed on developing an awareness of the use of mathematics as it exists in the world today.
MAT 222 Intermediate Algebra
In this course students will explore a wider range of Algebra topics beyond the introductory level. Topics will include polynomials, functions, rational expressions, systems of equations and inequalities, operations with radicals, and quadratic equations. Emphasis will be placed on developing an awareness of the use of mathematics as it exists in the world today.
MAT 232 Statistical Literacy
This course is designed to meet general education quantitative reasoning (mathematics) requirements. It will cover such topics as sampling, bias, probability, distributions, graphical methods of portraying data, measures of center, dispersion and position and the Central Limit Theorem. It will also cover computational techniques such as correlation, regression and confidence intervals.
MAT 540 Statistical Concepts for Research
This course demonstrates how to apply selected statistical techniques to a wide variety of problems and situations arising in the areas of business, economics, finance, management, social science, health, psychology, and education. Topics include graphical description of data; measures of location and dispersion; probability; discrete and continuous random variables; sampling distributions and estimation; confidence intervals and hypothesis tests; simple linear regression and correlation.