Introduction to Numerical Analysis
MTH 351 - Sec 001

MWF 13:00-13:50
STAG 110
Winter 2016


Professor:

Dr. Nathan Louis Gibson  

Office:

Kidd 056

Office Hours:

MW 15:00-15:50

Course Website:

http://www.math.oregonstate.edu/~gibsonn/Teaching/MTH351-001W16

Text Book:

Atkinson and Han, Elementary Numerical Analysis, Third Edition, Wiley


Course Description

Introduction to the computation of approximate solutions to mathematical problems that cannot be solved by hand: analysis of errors; rootfinding for nonlinear equations in one variable; interpolation of functions; numerical integration. All courses used to satisfy MTH prerequisites must be completed with C- or better. PREREQS: MTH 253 [C-] or MTH 306 [C-] and programming experience.

Learning Outcomes: After completing this class, successful students will be able to:


General Info

While it may not be stated explicitly each day, students are expected to read each section to be covered before class. Questions not addressed during class time should be asked in recitation. Any questions still unanswered may be asked in office hours.

Students are responsible for any material missed due to absence, see Calendar.

Accommodations are collaborative efforts between students, faculty and Disability Access Services (DAS). Students with accommodations approved through DAS are responsible for contacting the faculty member in charge of the course prior to or during the first week of the term to discuss accommodations. Students who believe they are eligible for accommodations but who have not yet obtained approval through DAS should contact DAS immediately at 737-4098.

Students are expected to be familiar with Oregon State University's Statement of Expectations for Student Conduct.

As preparation for this class, you should review the materials covered in MTH 253.


Grades

Grades for each assignment will be posted to the Canvas Site.

Grade Distribution

Homework 25%
Computer Assignments 25%
Midterm 25%
Final 25%
Total 100%

Grade Scale

A 93
A- 90
B+ 87
B 83
B- 80
C+ 77
C 73
C- 70
D+ 67
D 63
D- 60


Matlab

A scientific programming language is required for this course. Matlab is preferred due to the integration of computation and visualization, and the fact that the text book authors provide support. Online resources, including links to Matlab Tutorials and Matlab programs used in the text, are available at the publisher's website www.wiley.com/college/atkinson (click on Student Companion Site).

Oregon State University has subscribed to a Total Academic Headcount (TAH) Site License for MATLAB. This new licensing includes many, but not all MATLAB toolboxes. OSU faculty, staff and students can install on up to 4 personally-owned devices or computers. For more information visit Information Services -- MATLAB or matlab.mathworks.com.

The following are online resources for learning Matlab:


Homework

Homework is required for this course. Assignments will consist (mostly) of problems from the text. Exam problems will (mostly) be similar to homework problems. There will be (approximately) 5 homework assignments. Only problems marked with * need to be turned in for a grade.

Students may work together, but must turn in individual copies. (If typed, the wording must differ!)

HW1 -- Not Due

HW2 -- Due Jan 22

HW3 -- Due Feb 5

HW4 -- Due Feb 15

HW5 -- Due Mar 4

HW6 -- Due Mar 11

Only problems marked with * need to be turned in for a grade.


Computer Assignments (Labs)

Computer, or programming, assignments are required for this course. Assignments will be posted on the course website and announced in class. There will be approximately 5 programming assignments. Students should complete assignments individually. Any questions should be directed to the professor.

Upload a Published pdf file of your script, including plots produced and answers to all questions, to the appropriate Assignment in Canvas. It is helpful to also include a zip file of all scripts used.


Links

Taylor Series

Example of Noise in Function Evaluation

See image of weather.com interpolation of temperature data.

See interesting paper on fixing Secant method

See interesting paper on naming of Gaussian Elimination

Matlab demonstrations
testloop.m -- Section 2.1.3
compare.m -- Compares Bisection, Secant, and Newton methods (requires sample codes).
cobweb.m -- Graphical display of fixed point iterations
Integrate_GUI.m -- Publisher's GUI for numerical integration (requires Integrate_GUI.fig)
Maple demonstrations
trapsimp.mw -- Compares Mid-point, Trapezoid and Simpson's rules (requires Maple 10)

Introductory Materials from Chapter 1:
Sec 1.1
Sec 1.2
Sec 1.3

Binary Numbers

Math Modeling

Canvas Site
Alternative Texts
A First Course in Numerical Methods
Numerical Computing with MATLAB


Exams

There will be one midterm and one final exam (not cummulative, thus essentially Exam 2). There will be no curve, but partial credit will be given for significant progress toward a solution. No books, notes, or calculators are allowed. Expressions which are not easily computed may be left unsimplified. Exam problems will either be similar to suggested problems from the book or will test concepts from the lecture and/or computing assignments.


Last updated: Thu Mar 03 16:15:44 PST 2016