MATH 434: Numerical Analysis I
Credit hours (3)
Prerequisites: MATH 271, MATH 260, and ITEC 109 or 120; or permission of instructor.
Introduction to scientific programming, numerical solutions nonlinear equations and
                                    problems from linear algebra, interpolation, numerical integration, and numerical
                                    methods for differential equations.
Detailed Description of Course
The first part of this course typically covers:
    1) Programming using MATLAB, MAPLE or other programming environments.
    2) Floating point arithmetic.
    3) Solution of non-linear equations, Newton's method, secant method, and other
                                    iterative schemes.
    4) Linear systems of equations, matrix factorizations.
    5) Interpolation.
    6) Least squares approximation.
    7) Eigenvalue computation.
The second part typically covers:
    1) Numerical differentiation.
    2) Numerical integration, including Newton-Cotes formulas, adaptive quadrature,
                                    and Gaussian quadrature
    3) Numerical methods for differential equations, including Euler's method, Runge-Kutta
                                    methods, boundary value problems, and methods for partial
       differential equations.
    4) Selected additional topics, such as fast Fourier transform, numerical optimization,
                                    random number generators, and stochastic differential
       equations.
Detailed Description of Conduct of Course
This course will contain an introduction to scientific computing; the particular software
                                    used will vary among instructors.  Most instructors will use the lecture method, with
                                    some classes being taught in the computer lab.
Goals and Objectives of the Course
Acquire a working knowledge of algorithms and modern computer software for approximating
                                    solutions of scientific computing problems.
Assessment Measures
The assessment measures will vary among instructors and may include in-class examinations,
                                    homework assignments, computer projects, and performance in class and in laboratory
                                    activities.
Other Course Information
Students who plan to work in an applied science need exposure to and hands-on experience
                                    with methods and computer software that is applicable to many of the general problems
                                    they will encounter.  Math 434:435 is intended to be the sequence that provides this
                                    exposure and experience.
 
Review and Approval
November 7, 2017
November 17, 2015
March 2009
September 2001