Mathematics

Accelerated treatment of both elementary and intermediate algebra topics. Polynomials and rational expressions; solving linear, quadratic, and rational equations; linear inequalities; systems of linear equations; graphing lines, parabolas, and circles; radicals and rational exponents; complex numbers; introduction to functions; introduction to exponential functions and logarithms; applications; problem solving skills.

Polynomials and rational expressions; solving linear, quadratic, and rational equations; linear inequalities; systems of linear equations; graphing lines, parabolas, and circles; radicals and rational exponents; complex numbers; introduction to functions; introduction to exponential functions and logarithms; applications; problem solving skills.

Survey of mathematics for students with nontechnical goals. Topics include problem solving, set theory, logic, number theory, modeling with functions, geometry, finance, combinatorics, probability, and the role of mathematics in modern society. This course is designed to enhance student appreciation of both the beauty and utility of mathematics.

Linear, quadratic, algebraic, exponential, and logarithmic functions, interest and ordinary annuity problems; introduction to differential and integral calculus of one variable with applications to business and economics.

Support for students who are concurrently enrolled in MATH 75, Mathematical Analysis for Business. Topics include concepts and skills from elementary and intermediate algebra that are needed to understand the basics of Mathematical Analysis for Business. Concepts are taught in the context of the linked Math 75 course.

Descriptive statistics: organization of data, sample surveys, experiments and observational studies, measures of central tendency and dispersion, correlation, regression lines, and analysis of variance (ANOVA). Probability theory. Random variables: expected value, variance, independence, probability distributions, normal approximation. Sampling: sampling distributions, and statistical inference, estimating population parameters, interval estimation, standard tests of hypotheses.

Support for students who are concurrently enrolled in MATH 80, Probability and Statistics. Topics include concepts and skills from arithmetic, pre-algebra, elementary and intermediate algebra, and descriptive statistics that are needed to understand the basics of college-level statistics. Concepts are taught in the context of the linked Math 80 course.

Real functions and their graphs; one-to-one and inverse functions; polynomial, rational, exponential and logarithmic functions; complex numbers and zeros of polynomials; linear systems and matrices; geometric transformations and conic sections; topics in discrete mathematics.

Support for students who are concurrently enrolled in MATH 90, Precalculus Algebra. Topics include concepts and skills from elementary and intermediate algebra that are needed to understand the basics of precalculus algebra. Concepts are taught in the context of the linked Math 90 course.

Polynomial and rational expressions; radicals and rational exponents; equations and inequalities; real functions and their graphs; one-to-one and inverse functions; exponential and logarithmic functions; complex numbers and zeros of polynomials; linear systems and matrices; geometric transformations and conic sections; topics in discrete mathematics; applications.

Trigonometric functions and their graphs; trigonometric identities and equations; inverse trigonometric functions; solving triangles; complex numbers.

Complete both precalculus algebra and trigonometry by taking this single class.? Topics covered include real functions and their graphs; one-to-one and inverse functions; algebraic, exponential and logarithmic, and trigonometric functions; complex numbers and zeros of polynomials; matrices; transformations and conic sections; discrete mathematics; polar coordinates; and applications of trigonometric identities.

MATH 100A is the first course in a two-semester sequence in applied calculus. Lines, algebraic functions, exponential functions, logarithmic functions, limits, derivatives, and integrals, with applications.

Math 100B is the second course in a two-semester sequence in applied calculus. Techniques of integration, periodic functions, Taylor polynomials, multi-variable calculus, and differential equations, with applications to business, economics, and science.

Foundations of Data Science combines an introductory look into the fundamental skills and concepts of computer programming and inferential statistics with hands-on experience in analyzing datasets by using common tools within the industry. Additionally, the course investigates ethical issues surrounding Data Science, such as data privacy.

First course in a three-semester calculus sequence, this course covers differential calculus through the study of limits, continuity, differentiation, applications of differentiation, and an introduction to integration.

A second course in single-variable calculus. Applications of integration, techniques of integration, numerical integration, indeterminate forms, improper integrals, parametrized curves, polar coordinates, infinite sequences and series, and power series.

Advanced calculus course focusing on vectors, curves and surfaces in 3-dimensional space, differentiation and integration of multivariate functions, line and surface integrals, and, in particular, the theorems of Green, Stokes, and Gauss.

Support for students who are concurrently enrolled in MATH 110A, Calculus I. Topics include concepts and skills from precalculus and trigonometry that are needed to understand the basics of Calculus I. Concepts are taught in the context of the linked Math 110A course.

Set theory, logic, proof techniques, mathematical induction, relations and functions, recursion, combinatorics, elementary number theory, trees and graphs, analysis of algorithms. Emphasis on topics of relevance to mathematics and computer science majors.

Real vector spaces, subspaces, linear dependence and span, matrix algebra and determinants, basis and dimension, inner product spaces, linear transformations, eigenvalues and eigenvectors, proofs of basic results.

Ordinary differential equations and first order linear systems of differential equations; methods of explicit solution; qualitative methods for the behavior of solutions; theoretical results for the linear structure, existence, and uniqueness of solutions.

Topics include real vector spaces, subspaces, linear dependence, span, matrix algebra, determinants, basis, dimension, inner product spaces, linear transformations, eigenvalues, eigenvectors, and proofs. Ordinary differential equations and first-order linear systems of differential equations; explicit solutions; qualitative analysis of solution behavior; linear structure, existence, and uniqueness of solutions. Partial differential equations.