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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.

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.

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.

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.

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.

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.

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.

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.