# Mathematics & Analytics

All first-year students should take the University’s Mathematics Placement Test upon admission. Transfer students will need to take the test only if they cannot provide evidence of having completed a college course in mathematics or analytics equivalent to one of the courses listed in the Mathematics and Analytics section of the University’s General Education Program

Students who do not wish to take the Mathematics Placement Test must successfully complete MATH 90: Fundamentals of Mathematics before registering for a course in the Mathematics and Analytics Category of General Education.

Select 1 course

Introduces functions and graphs, continuity and exponential functions. Standard topics to be covered include concepts and rules of the differentiation of one variable functions, the meaning and application of derivatives in decision making management problems, integrals and the limits of one variable functions, as well as rules, interpretation, logarithm functions, definite integral, functions of several variables and application of partial derivatives. Students practice with various mathematical methods and learn how to model and analyze real world examples using mathematical tools and apply deductive reasoning as well. Prerequisites: MATH90 or its equivalent. Credits: 3
Introduces discrete and continuous probability spaces, statistical independence, distributions, discrete and continuous random variables, expectations, moment generating functions, limiting distributions, estimation of parameters, confidence intervals, hypothesis testing with applications, linear regression and correlation and multiple linear regressions. Students learn to define probability as a measure of uncertainty and as a set function, apply the algebra of sets and use various counting techniques to determine elementary probabilities. The class includes calculation of probabilities, means, variances, and moment-generating functions, and investigates approximation theorems. Students also study basic statistical inference theory. Prerequisites: MATH150. Credits: 3
Develops different mathematical techniques and investigates various examples and applications, emphasizing in techniques and applications of derivatives and integration, multiple integrals, limits, continuity, series and polar coordinates. Prerequisite: MATH150 Credits: 3
Covers the development of mathematical tools necessary for algorithmic applications in computer science. The course includes set theory and logic, various algebraic structures, graph theory, Boolean algebra, and computability theory. Students understand mathematical reasoning and logic, work with discrete structures to represent discrete objects and relationships between them, specify algorithms for certain classes of problems and appreciate the many application areas of discrete mathematics, from computer science and networking to chemistry, botany, zoology, linguistics, geography, business, and the Internet. Prerequisites: IT150, MATH150 Credits: 3
Develops different fundamental methods of solving first and higher order equations and analyzes essentials of matrix algebra, linear and nonlinear systems, power series solutions and Laplace transforms.Prerequisites: MATH150 Credits:3
Provides knowledge of how statistics are used to evaluate theories in the social sciences. Students will become familiar with a variety of descriptive and inferential statistical techniques such as: frequency distributions, descriptive statistics, probability, correlation, and hypothesis testing. During the course, students will learn how to use SPSS (a computer statistical program for Social Sciences) to carry out statistical procedures. Credits 3. Prerequisites: MATH90 or its equivalent