Introduction to Numerical Analysis
MTH 351  Sec 010
MWF 9:009:50
BEXL 328
Winter 2024
Professor:  Dr. Nathan Louis Gibson

Office:  Kidd 056

Office Hours:  MW 10:0010:50

Course Website:
 http://www.math.oregonstate.edu/~gibsonn/Teaching/MTH351010W24

Text Book:
 
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:
 Apply wellknown numerical methods to solve a variety of problems
 Understand advantages and disadvantages of various methods
 Analyze numerical methods to determine properties of error and convergence
 Utilize MATLAB codes to understand the performance of methods
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 7374098.
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 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

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 personallyowned devices or computers.
For more information visit Information Services  MATLAB or matlab.mathworks.com.
The following are online resources for learning Matlab:
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.
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 detailed answers to all questions, to
the appropriate Assignment in Canvas. It is helpful to also
include a zip file of all scripts used.
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 or compare.pdf  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
Midpoint, 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
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:
Fri Jan 26 13:11:46 PST 2024