MACM 316
Numerical Analysis I

INSTRUCTOR:	John Stockie Office: K10518 E-mail: jstockie  [at]  sfu.ca Web: http://www.sfu.ca/~jstockie
CLASS TIMES:	MWF - 12:30-13:20 (AQ 3181)
CANVAS:	All lecture notes, assignments, due dates, 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 2:30-3:30    (in [math west] room WMC 2830) Outside of this time, you can post questions on the Canvas discussion boards or ask me in person before/after lectures.
TUTORIALS:	You are assigned to a tutorial section that will be led by one of your TAs (Ben Buckley, Jingzhou Na, Mahdi Salehzadeh) at the times indicated below:        Wednesdays: 14:30-15:20 (D101), Mahdi 15:30-16:20 (D102), Ben 16:30-17:20 (D103), Ben Thursdays: 9:30-10:20 (D104), Jingzhou 10:30-11:20 (D105), Ben 11:30-12:20 (D106), Mahdi
	All tutorials are held in [math west] room WMC 2830. Please try to attend the tutorial section in which you are registered, since seating is limited. Tutorials are an important supplement to lectures, and will focus on addressing questions 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! If you need to communicate with your TAs, then use the appropriate Canvas discussion groups or speak to them in person (during tutorials). Please do not send email!
COMPUTATIONAL WORKSHOP:	In addition to your tutorial section, there are two open Computational Workshop sessions scheduled weekly (starting in week 2). These slots are dedicated specifically to obtaining help with questions on the current Computing Assignment:          Mondays 14:30-17:30 (Jingzhou & Ben) Fridays 14:30-17:30 (Jingzhou & Mahdi)
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 students. If you have an older edition of the book (9th ed. or earlier) then the actual content is largely the same; however, please be aware that homework is assigned from the 10th edition and so the question/page numbers will differ between editions.
LECTURE NOTES:	I teach from "skeleton notes" that I will post on Canvas before each lecture. I will fill in the blanks with additional information and worked out examples during class, so you may find it helpful to print the notes in advance (or download them to a tablet). My lecture notes are based primarily on the textbook but some material is drawn from other sources. If you miss a lecture for any reason, then it is your responsibility to obtain the missed material from another student.
ASSESSMENT:	Homework Problems: Homework problems are assigned every week and most questions will be selected from the 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 quiz. Quizzes: The week after each set of homework problems is posted, there will be a short quiz held in Wednesday's lecture (normally during the last 15 minutes) that is based on the material in the lecture notes and homework from that 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 (short) Matlab codes from scratch, although some assignments will 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 student app installed on their smartphone (Mobile app) or computer (Web app), 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 pose while teaching. 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 for the semester falls below 75%, then your clicker grade will be reduced accordingly (for example, with a 70% response rate you would receive 0.7*5 = 3.5 marks out of the maximum 5). Midterm Test: There is one midterm test of 50 minutes in duration held during lecture on Wednesday October 18. Final Exam: The final exam will be held during the examination period in December and will cover all material from the course.
LATE POLICY:	Any missed quiz or late computing assignment will automatically receive a mark of ZERO, with no exceptions. I recognize that you may miss a quiz / CA due to illness or some other unexpected absence. To account for such circumstances fairly and consistently (while also minimizing administrative overhead) I will drop everyone's lowest quiz and lowest CA. The ONLY exception to this rule is if you miss multiple assignments/quizzes for a valid documented reason, in which case you must discuss with me in person and complete the SFU Academic Concession Self-Declaration Form.

MARKING SCHEME:	Quizzes (≈weekly):   15% Computing assignments (≈bi-weekly):   25% ☆☆ iClicker questions (participation only):   5% Midterm test (Wed Oct 18):   15% Final examination (Mon Dec 11):    40%
	☆☆ 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) 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 on the SFU Student Services pages on Academic Integrity. 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 quizzes or 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.
EQUITY, DIVERSITY & INCLUSION:	As your instructor, I strive to foster a learning environment that supports a diversity of thoughts, experiences and identities, including gender, race, religion, age, national origin, sexual orientation, neurodiversity and ability. I also value your participation in this course. Please let me know if there is any way that I can better support your learning needs. As a student, I expect that you will review and adhere to the SFU Student Conduct Policy. The Department of Mathematics Equity, Diversity and Inclusion Advisory Group is a committee that works towards ensuring that the department is a safe, respectful and inclusive working and learning environment. I encourage you to reach out to the EDI Advisory Group with any concerns and/or ideas regarding equity, diversity and inclusion. Additional SFU EDI Resources: https://www.sfu.ca/edi/support/students.html
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 is 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 difference approximations, 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