Fifth Math Options

MAD 3401 Numerical Analysis (3).
Prerequisite: MAC 2313. Programming skills required.

Major topics: solutions to scalar nonlinear and finite difference equations; numerical differentiation and integration; error and convergence; general interpolation problems, interpolation and quadrature, numerical solutions of algebraic and transcendental equations.

Polynomial interpolation, data fitting, solutions to nonlinear equations, numerical integration, and differentiation. Not open to mathematics majors.

Root finding, interpolation and polynomial approximation, numerical differentiation and integration, direct and iterative methods for systems of linear equations.

Vector calculus. Solution of partial differential equations by separation of variables, Sturm-Louville problems, Fourier series, complex numbers, complex integrals.

Not open to students having credit in MAP 4341. Fourier series and Fourier transforms, introduction to partial differential equations.

Major topics: solution of first-order partial differential equations, classification of linear second-order partial differential equations, separation of variables, initial value and initial boundary value problems.

Separation of variables,Fourier Series, Sturm-Liouville problems, multidimensional initial boundary value problems, nonhomogeneous problems, Bessel functions and Legendre polynomials.

Investigation of systems of linear equations, vector spaces over a field, linear transformations, theory of determinants and canonical forms.

Gaussian elimination, vector spaces, least squares problems, determinants, eigenvalues and eigenvectors, linear transformations, applications.

This course will cover calculus-based probability, discrete and continuous random variables, joint distributions, sampling distributions, and central limit theorem. Topics include descriptive statistics, interval estimates and hypothesis tests, ANOVA, correlation, simple and multiple regression, analysis of categorical data, and statistical quality control.

Major topics: analysis of variance; multiple regression; contingency tables; experimental design, calculus based.

The objective of the Numerical Methods for Engineers class is to teach programming and numerical methods to solve engineering/scientific problems in an effective and efficient manner to meet the needs of industry, government, and academia. To achieve the objective, the course will leverage on the use of MATLAB which is now the de facto standard for scientific computing. This teaching style is intended to keep students engaged and have them develop practical programming skills. The students should have completed Calculus I, II, and III (MAC2311, 2312, & 2313), and differential equations or engineering math (MAP3305 or 2302). We do not assume expert knowledge of programming for students entering this class.