MACM 316
Numerical Analysis I

INSTRUCTOR:	John Stockie E-mail: jstockie  [at]  sfu.ca Web: http://www.sfu.ca/~jstockie
CLASS TIMES:	MWF - 12:30-13:20   (remote, with Zoom, video recordings will be posted)
CANVAS:	All assignments, due dates, lecture notes and other course-related information will be posted on Canvas. It is your responsibility to check your SFU Canvas account regularly and read the announcements there.
MY OFFICE HOURS:	Mondays - 14:30-15:30    (with Zoom) Outside of this time, please send me an email or use the Canvas discussion boards.
TUTORIALS:	Each of you is assigned to a tutorial section that will be led by one of your TA's on Zoom as indicated below:
	Alamgir Hossain (Workshop Coordinator), email: mahossai [at] sfu.ca Wednesdays - 14:30-15:20 (D101) Thursdays - 9:30-10:20 (D104)
	Mohsen Seifi (TA), email: smseifi [at] sfu.ca Wednesdays - 15:30-16:20 (D102) 16:30-17:20 (D103)
	Anton Iatcenko (TA), email: aiatcenk [at] sfu.ca Thursdays - 10:30-11:20 (D105) 11:30-12:20 (D106)
	Tutorials are an essential supplement to lectures, and will focus on addressing questitons related to the current homework and computing assignments. Your TAs may also provide help with Matlab programming, or review assignment/quiz/test solutions. If you want to succeed in this course then I strongly recommend that you attend!
COMPUTATIONAL WORKSHOP:	In addition to your tutorial section, there are two open "computational workshop" sessions each week that are dedicated specifically to dealing with questions regarding the Computing Assignments: Thursdays 14:30-17:30 (NN1, NN2) Fridays      14:30-16:00 (NN3) In this on-line version of the course, these sessions will be conducted on a discussion board that is monitored by TAs during the above time slots. If needed, you can also set up a separate video meeting with the TAs.
TEXTBOOK:	Numerical Analysis, 10th edition, by R. L. Burden, J. D. Faires and A. M. Burden (Cengage Learning) This textbook also has a Companion Website with supplementary materials for both students and teachers. If you have an older edition of the book (e.g., the 9th edition), the content is largely the same; however, please be aware that homework questions are assigned from the 10th edition and those question numbers will differ between editions.
LECTURE NOTES:	I will teach from "skeleton" lecture notes that will be posted in advance of each lecture. I will fill in the blanks during lectures with additional information and examples, so you may find it helpful to print the notes ahead of each class. My lecture notes are mostly based on the textbook but some material will be drawn from other sources.
ASSESSMENT:	Homework Problems: Homework problems are assigned roughly each week, and most questions will be selected from textbook exercises -- make sure you refer to the 10th edition!! These problems will not be handed in or marked for credit, but they will form the basis for your weekly quizzes. Quizzes: The week after each homework assignment is posted, there will be a short quiz held during Wednesday's lecture (usually the last 15 minutes) that is based on the homework. The only exception is "Quiz ZERO", which is a special asynchronous assignment to be done during the first week. Computing Assignments: Computing problems are assigned roughly every two weeks and will be graded. They are due on Fridays by 11:00pm and must be submitted as a 2-page PDF file using Crowdmark (1-page report, 1-page Matlab code). I expect that you are capable of writing your own Matlab codes from scratch, although some assignments may involve modifying a piece of Matlab code that I provide to you. Before submitting your first assignment, please familiarize yourself with my expectations for submitted work by reading the Guidelines for Computing Assignments. Clicker Questions: Every student must have the iClicker Reef app installed on their smartphone or computer, which also requires that you pay a subscription fee. You must have this app running during lectures since it allows you to submit responses to the multiple-choice/true-false questions that I present. Your answers are not marked for correctness. Instead, you will earn a participation mark of 5% on your final grade, provided that you respond to at least 75% of questions throughout the semester. If your response rate is below 75%, the clicker grade will be scaled proportionally (e.g., a 70% response rate will get you 0.7*5 = 3.5 marks out of the possible 5). Midterm Test: There will be one midterm test of 50 minutes in length, held during lecture on Wednesday October 21. Final Exam: The final exam will be held in December (date/time to be announced) and will cover all material from the course.
LATE POLICY:	All missed quizzes or late assignments automatically receive a mark of ZERO. I recognize that you may miss a quiz or computing assignment due to illness or other unexpected absence. To account for such circumstances fairly and consistently, while also minimizing administrative overhead, I will drop everyone's lowest quiz grade and lowest computing assignment grade. The ONLY exception to this rule is if you miss multiple assignments/quizzes for a valid documented reason, in which case you must provide me with an SFU Certificate of Illness.
TEST PROCTORING:	All written tests (quizzes, midterms and final exam) will be monitored on video via Zoom. For this reason, you must have a video camera and it must be turned on and directed towards you for the duration of the time you are writing any test.

MARKING SCHEME:	Quizzes (≈weekly):   22% Clicker questions (participation only):   5% Computing assignments (≈bi-weekly):   25% ☆☆ Midterm test (Wed Oct 21):   18% Final examination (TBA):    30%
	☆☆ Implementing, testing and understanding numerical algorithms is an essential part of MACM 316. Consequently, in order to pass this course, you must obtain a passing grade on the computing assignments (⩾12.5/25) and on the final examination, as well as achieving an overall passing grade in the course. Students requiring any special accommodations (for reasons of disability, religion, varsity sport, etc.) MUST inform me during the first week of semester, or as soon as possible after that.
ACADEMIC INTEGRITY:	Academic dishonesty has no place in a university and I have ZERO tolerance for it. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences identified under the SFU Code of Academic Integrity and Good Conduct. Cheating includes, but is not limited to: Handing in assignment solutions copied (even partially) from other sources such as books, solution manuals, web pages, other students' work, etc. Using computers, smartphones or reference materials during tests, unless they are explicitly allowed. Accepting assistance from other students or individuals during quizzes or tests. In all of these circumstances, any students involved in the offense will receive a mark of zero for the entire work in question. The Chair of the Mathematics Department will be notified and the offense will be documented in your SFU academic record. Further action may also be taken as outlined in the SFU Policies and Procedures for Student Discipline.
PREREQUISITES:	MATH 152 or MATH 155 or MATH 158; and MATH 232 or MATH 240; and computing experience.

OUTLINE:

(this is the official outline and may differ slightly from what may be posted elsewhere)

Number systems and errors: Ch 1 (all) -- 1.5 weeks Floating-point representation for real numbers Round-off error, error propagation, error estimation Review of concepts from calculus Nonlinear equations: Ch 2 (except 2.6) -- 2 weeks Bisection, secant and Newton's methods Fixed point iteration Rate of convergence Systems of linear equations: Chs 6 & 7 (all) -- 3 weeks Gaussian elimination: factorization, pivoting, matrix inverses Norm, determinant, condition number Iterative methods Eigenvalue problems Interpolation and approximation: Ch 3 (except 3.4 & 3.6) plus Secs 8.1 & 8.5 -- 2 weeks Interpolating polynomials: Lagrange and Newton forms, error formula Spline interpolation Trigonometric interpolation, Fourier series Least squares fitting Differentiation and integration: Ch 4 (only 4.1-4.4 & 4.7) -- 1.5 weeks Numerical differentiation, finite differences, Richardson extrapolation Numerical integration: quadrature rules, extrapolation ODE initial value problems: Ch 5 (except 5.6-5.8) -- 2 weeks Euler's method Taylor and Runge-Kutta methods Convergence, stability, stiffness Systems of differential equations