Mathematics (BS)

A calculus-based course in classical probability theory. Topics covered include probability axioms and properties, discrete and continuous random variables, joint distributions, conditional distributions, expectation and variance, covariance and correlation, moment generating functions, central limit theorem.

Computer algebra systems will be introduced. Topics include methods for approximate solutions of equations in one variable, polynomial approximation methods, numerical calculus, numerical solutions to ordinary differential equations, linear systems of equations, and difference equations.

Introduces and provides models for application of the concepts of vector algebra. Topics include finite dimensional vector spaces and their geometric significance; representing and solving systems of linear equations using multiple methods, including Gaussian elimination and matrix inversion; matrices; determinants; linear transformations; quadratic forms; eigenvalues and eigenvector; and applications in science and engineering.