Math 441/620 - Numerical Analysis

Spring 2003 - Matthias K. Gobbert

Section 0101 - Schedule Number 3639/3682

This page can be reached via my homepage at http://www.math.umbc.edu/~gobbert.

Grading Information

Final scores and grades ordered by your assigned number:

Basic Information

Matthias K. Gobbert, Math/Psyc 416, (410) 455-2404, gobbert@math.umbc.edu,
office hours: TTh 04:00-05:00 or by appointment
Lectures: TTh 05:30-06:45, MP 401; see the schedule for more information.
Prerequisites: Math 225, Math 251, Math 301, CMSC 201, or instructor approval
Copies of the following books are on reserve in the library.
- Required textbook: Kendall E. Atkinson, An Introduction to Numerical Analysis, second edition, Wiley, 1989. Associated webpage: http://www.math.uiowa.edu/~atkinson/keabooks.html
- Recommended book on Matlab: Desmond J. Higham and Nicholas J. Higham, Matlab Guide, SIAM, 2000. Associated webpage: http://www.ma.man.ac.uk/~higham/mg
Notice that the bookstore may stock the books under Math 441.
Grading policy:

Homework Presentations Project Midterm Final
30% 10% 10% 20% 30%

The homework is weighted so heavily, because it includes the computer assignments that are vital to understanding the course material. The presentations consist of presenting selected homework problems in class on the board; I will assign the problems to individual students throughout the semester. Both Math 441 and 620 will have projects with professional grade type-set reports, but they will be different in level; they will be group projects and will be assigned as early as possible in the semester. See also the general policies and procedures for more information.

Overview

Numerical Analysis is concerned with the approximation of continuous mathematical objects by constructs with only finitely many coefficients. This takes various forms including the approximation of a function by a series with finitely many terms or the approximation of a derivative by a finite difference. These approximations incur numerical error, in the examples above known as truncation error and discretization error, respectively. Numerical Analysis is dedicated to the analysis of these errors.

This course will also include computational work to gain practical experience with the numerical methods discussed. The methods covered include polynomial interpolation, numerical differentiation and integration, approximation theory and orthogonal polynomials, the solution of non-linear systems of equations, and an introduction to numerical methods for ordinary differential equations.

Other Information

Schedule including date for the midterm exam
General policies and procedures including grading guidelines
Guidelines on how to report on computer results

The recommended literature on my homepage includes listings of books on computers programming
A brief introduction to Unix/Linux at UMBC
My introduction to Matlab at UMBC
An introduction to LaTeX including a sample file and a template file for project reports.

Official UMBC Honors Code

By enrolling in this course, each student assumes the responsibilities of an active participant in UMBC's scholarly community in which everyone's academic work and behavior are held to the highest standards of honesty. Cheating, fabrication, plagiarism, and helping others to commit these acts are all forms of academic dishonesty, and they are wrong. Academic misconduct could result in disciplinary action that may include, but is not limited to, suspension or dismissal.

To read the full Student Academic Conduct Policy, consult the UMBC Student Handbook, the Faculty Handbook, or the UMBC Policies section of the UMBC Directory.

Homework	Presentations	Project	Midterm	Final
30%	10%	10%	20%	30%