Instructor

Roy H. Goodman

624 Cullimore Hall, (973) 642-4261

Office Hours

Monday 1:00-2:30, Thursday 4:00-5:30 or by appointment

Textbook

J. Faires and R. Burden, Numerical Methods, 3rd Edition

Additional References

Examinations

Midterm: Thursday, 10/22, (before drop deadline)

Final: Thursday 12/17, Both during regular class hours

Homework

(Guidlines)

Homework assignments/projects will be given frequently; many will involve writing computer programs in a computer language such as C, Matlab, or FORTRAN. Each assignment must be turned in at the beginning of class. Late assignments are NOT accepted. Early assignments are always welcome and are appropriate for preplanned absences from class. As a standing assignment, you should read the relevant sections of the textbook prior to lecture. Homework must follow the guidlines described in the linked document.

Drop Deadline

November 2 (set by university).  No exceptions.

Grading

40% Homework/Projects

30% Midterm Examination (10/22)

30% Final Examination (12/17)

Attendance

Attendance at and participation in all lectures is expected. If you know in advance that you will be absent from class for a legitimate reason, please tell me prior to your absence so that appropriate arrangements (if any) can be made. Tardiness to class is very disruptive of the classroom environment and should be avoided.

Honor Code

The NJIT Honor Code applies to all activities associated with the course, including but not limited to homework, examinations, and projects. As an example, when you submit a homework assignment, you are certifying that your paper contains only your work and is not copied from other people or sources.

Course Topics

(Link to week-by-week topics and assignments.)

The minimal set of topics for this course appear in Chapters 1-8 & 10 of the text.

• Solution of nonlinear equations: bisection method, secant method, Newton's method, fixed point iteration, nonlinear systems
• Numerical solution of linear systems: Gaussian elimination, iterative methods
• Interpolation and approximation: polynomial interpolation, splines, least squares
• Numerical differentiation and integration: Newton-Cotes formulas, Gaussian quadrature
• Numerical methods for ordinary differential equations: single step methods, multistep methods, shooting techniques for boundary value problems

Course Description

A practical introduction to the numerical methods of science and engineering. Numerical solution of linear systems. Interpolation and quadrature. Iterative solution of nonlinear systems. Computation of eigenvalues and eigenvectors. Numerical solution of initial- and boundary-value problems for ODEs. Introduction to numerical solution of PDEs. Includes examples requiring student use of a computer with some use of software packages. See here.

Prerequisites

(This course is not intended for students in the Master's in Applied Mathematics program or in the doctoral program in Mathematical Sciences.) Math 222 (differential equations), Math 337 (linear algebra), and proficiency in a computer language (FORTRAN, C, or C++, Matlab, etc.), or departmental approval.  See here.

Cell Phones

Must be turned off. Or this might happen to you