Syllabus – Math 5315 / CSE 7365, Introduction to Numerical Analysis, Fall 2018

Instructor:

Daniel R. Reynolds

Class and Office Hours:

Lecture: 152 Dallas Hall, Tu/Th, 12:30-1:50 pm.

Office Hours: 139 Clements Hall, Tu/W/Th 2-3 pm, W 9-11, or by appointment (arrange by email).

Textbook (required):

D.R. Kincaid and E.W. Cheney, Numerical Analysis: Mathematics of Scientific Computing, American Mathematical Society, 3rd edition, 2009. (ISBN: 0821847880)

Course Description:

MATH 5315 / CSE 7365 – Introduction to Numerical Analysis [3 credits]

Numerical solution of linear and nonlinear equations, interpolation and approximation of functions, numerical integration, floating-point arithmetic, and the numerical solution of initial value problems in ordinary differential equations. Student use of the computer is emphasized.

Prerequisites: MATH 3313, and MATH 3315/CSE 3365 or MATH 3316; a programming course (e.g., C, Fortran, or MATLAB).

Student Learning Objectives:

  • Math Major SLO 5: Students will be able to demonstrate fluency in the use of advanced tools or methods common to the field.

Computing:

Computing assignments in this class will be performed in either Matlab or Python, unless otherwise approved by the instructor. Because SMU has a site license for Matlab, it may be installed for free on your personal computer (Windows, Mac or Linux). Matlab is is also available on most public computers across campus. For additional information on accessing Matlab, please see the Matlab Access page.

Similarly, Python is free and may be installed on any computer. I require that Python programs be turned in as .py files (i.e. not as IPython or Jupyter notebooks), so that they can be run at the OS X / Linux command line. I also require that all students using Python must use Python v3.x to provide some uniformity in grading.

Reading:

Reading the assigned sections of the textbook is required, and will be necessary for completing each homework assignment. You are responsible for all of the material in the assigned reading, whether it has been presented in the lecture or not.

The assigned readings for each section will be listed on the Reading page.

Warm-up quizzes:

Prior to each lecture, you must complete a short quiz based on your reading for that topic; these will be turned in on Canvas. These “warm-up” quizzes must be completed before the beginning of class (late work will not be accepted). The goal of these problems is for you to think about each topic before class, so that it will be easier to learn during discussion. If all problems are attempted, the lowest possible grade you can attain on this is a 70.

It is recommended that you work on these problems together.

Homework:

Homework will be assigned on the course Homework page. These will be due periodically throughout the semester, and will be comprised of both theoretical and computational work.

  • Computational portions of each assignment will be turned in electronically through Canvas. You must turn in all Matlab or Python scripts, functions, and input files required to run your code (including any files provided by the instructor).
  • Theoretical portions of each assignment will be turned in electronically through Canvas.

Each homework assignment is due by 5:00 pm on the specified date.

Late work will lose points based on the following schedule:

  • 1 minute to 24 hours – 20% deduction
  • 24 hours to 48 hours – 50% deduction
  • over 48 hours – no credit

These assignments will involve a substantial amount of work – I strongly recommend that you begin these when assigned and do not procrastinate.

Exams:

We will have 2 in-class exams, the dates of which are posted on the course web page. The exam questions will be based off of the reading and homework. These exams will be non-cumulative, and will be open-book/open-notes, but calculators and other electronic devices are prohibited.

We will have a final exam during the regularly-scheduled exam period (12/10, 11:30 am). This will be cumulative, and will be open-book/open-notes, but again, calculators and other electronic devices are prohibited.

Grading:

Your course grade will be determined using the following formula:

10% Quizzes

30% Homework

30% Mid-term exams

30% Final exam

If your final exam grade is higher than your lowest regular exam grade, then I will instead determine your grade using the formula:

10% Quizzes

30% Homework

15% Best mid-term exam

45% Final exam

My grading scheme is somehow too complex for Canvas to handle, so the overall grade shown in Canvas will be incorrect. As this is an upper-level Math course and I provide all numerical grades and the formula to you, I expect that you can determine your actual overall grade yourself. All final grades are assigned on a standard grading scale.

Honor Code:

The SMU Honor Code applies to all homework and exams in this course. Work submitted for evaluation must represent your own individual effort. Any giving or receiving of aid without my express consent on academic work submitted for evaluation shall constitute a breach of the SMU Honor Code.

I take honor code violations very seriously, and will report all violations to the SMU Honor Council. The minimum penalty for a violation is a “0” on the assignment, and the maximum penalty is immediate failure of the course. These penalties are in addition to those imposed by the SMU Honor Council.

Examples of honor code violations include:

  • Submitting a computer code which includes a program, or even part of a program, written by anyone else (other than the instructor). This includes programs written by students from previous semesters, and programs downloaded from the internet.
  • Submitting computer outputs (numerical results or plots) produced by someone else’s program.
  • Submitting computer outputs with fabricated results.
  • Copying theoretical work from another student.
  • Supplying your own work for another student to copy.

A generally applicable rule of thumb in this course is: you are encouraged to talk about program strategy (e.g. algorithms from the book, helpful websites, etc.) and proof strategy (e.g. general techniques like proof by contradiction, important definitions from the book, etc.) all you want, but you should never look at another student’s codes or written work.

See the SMU Honor Code website for more information.

SMU Regulations:

Disability Accommodations: Students needing academic accommodations for a disability must first register with Disability Accommodations & Success Strategies (DASS). Students can call 214-768-1470 or visit http://www.smu.edu/Provost/ALEC/DASS to begin the process. Once registered, students should then schedule an appointment with the professor as early in the semester as possible, present a DASS Accommodation Letter, and make appropriate arrangements. Please note that accommodations are not retroactive and require advance notice to implement.

Religious Observance: Religiously observant students wishing to be absent on holidays that require missing class should notify their professors in writing at the beginning of the semester, and should discuss with them, in advance, acceptable ways of making up any work missed because of the absence. (See University Policy No. 1.9.)

Excused Absences for University Extracurricular Activities: Students participating in an officially sanctioned, scheduled University extracurricular activity should be given the opportunity to make up class assignments or other graded assignments missed as a result of their participation. It is the responsibility of the student to make arrangements with the instructor prior to any missed scheduled examination or other missed assignment for making up the work. (University Undergraduate Catalogue)

Campus Carry: In accordance with Texas Senate Bill 11, also known as the “campus carry” law, following consultation with the entire University community SMU determined to remain a weapons-free campus. Specifically, SMU prohibits possession of weapons (either openly or in a concealed manner) on campus. For more information, please see: http://www.smu.edu/BusinessFinance/Police/Weapons_Policy.