Please note:

To view the Fall 2017 Academic Calendar go to http://www.sfu.ca/students/calendar/2017/fall.html

Department of Mathematics Simon Fraser University Calendar | Spring 2018

Operations Research Major

Bachelor of Science

This program prepares students for careers in industry or a variety of graduate and professional programs.

Prerequisite Grade Requirement

To enroll in a course offered by the Department of Mathematics, a student must obtain a grade of C- or better in each prerequisite course. Some courses may require higher prerequisite grades. Check the MATH course’s Calendar description for details.

Students will not normally be permitted to enroll in any course for which a D grade or lower was obtained in any prerequisite. No student may complete, for further credit, any course offered by the Department of Mathematics which is a prerequisite for a course the student has already completed with a grade of C- or higher, without permission of the department.

Program Requirements

The program requires the completion of 120 units which includes a Faculty of Science requirement of a minimum of 28 upper division units, and additional upper division units to total a minimum of 44 upper division units (excluding EDUC 401, 407).

The specific program requirements are divided into three parts: required lower division courses, required upper division courses, and completion of an interdisciplinary requirement.

In addition to the program requirements set out below, general university and Faculty of Science regulations must be met.

Computing science courses that are completed in the operations research major program will count towards the requirement that 12 units must be completed from outside of the Faculty of Science.

A minimum program 2.00 cumulative grade point average (CGPA) must be obtained on the overall major program requirements, as well as a minimum program 2.00 grade point average in the upper division major courses.

Lower Division Requirements

Students complete

both of

CMPT 120 - Introduction to Computing Science and Programming I (3)

An elementary introduction to computing science and computer programming, suitable for students with little or no programming background. Students will learn fundamental concepts and terminology of computing science, acquire elementary skills for programming in a high-level language and be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode, data types and control structures, fundamental algorithms, computability and complexity, computer architecture, and history of computing science. Treatment is informal and programming is presented as a problem-solving tool. Prerequisite: BC Math 12 or equivalent is recommended. Students with credit for CMPT 102, 128, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129, 130 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.

Section Instructor Day/Time Location
D100 Angelica Lim
Mo, Fr 9:30 AM – 10:20 AM
We 9:30 AM – 10:20 AM
AQ 3181, Burnaby
AQ 3182, Burnaby
D101 Angelica Lim
Th 9:30 AM – 10:20 AM
ASB 9838, Burnaby
D102 Angelica Lim
Th 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D103 Angelica Lim
Th 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D104 Angelica Lim
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D105 Angelica Lim
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
D106 Angelica Lim
Th 2:30 PM – 3:20 PM
ASB 9838, Burnaby
D107 Angelica Lim
Th 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D108 Angelica Lim
Th 3:30 PM – 4:20 PM
ASB 9838, Burnaby
CMPT 129 - Introduction to Computing Science and Programming for Mathematics and Statistics (3)

A second course in computing science and programming intended for students studying mathematics, statistics or actuarial science and suitable for students who already have some background in computing science and programming. Topics include: a review of the basic elements of programming: use and implementation of elementary data structures and algorithms; fundamental algorithms and problem solving; basic object-oriented programming and software design; computation and computabiiity and specification and program correctness. Prerequisite: CMPT 102 or CMPT 120. Students with credit for CMPT 125 or 135 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Brad Bart
Mo 1:30 PM – 2:20 PM
We 1:30 PM – 2:20 PM
Fr 1:30 PM – 2:20 PM
SSCC 9002, Burnaby
AQ 3005, Burnaby
SSCK 9500, Burnaby
D101 Brad Bart
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D102 Brad Bart
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
D103 Brad Bart
Th 2:30 PM – 3:20 PM
ASB 9838, Burnaby
D104 Brad Bart
Th 3:30 PM – 4:20 PM
ASB 9838, Burnaby

(or equivalent: CMPT 125 (3) or CMPT 126 (3) or CMPT 128 (3))

or both of

CMPT 130 - Introduction to Computer Programming I (3)

An introduction to computing science and computer programming, using a systems oriented language, such as C or C++. This course introduces basic computing science concepts. Topics will include: elementary data types, control structures, functions, arrays and strings, fundamental algorithms, computer organization and memory management. Prerequisite: BC Math 12 (or equivalent, or any of MATH 100, 150, 151, 154, or 157). Students with credit for CMPT 102, 120, 128 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.

CMPT 135 - Introduction to Computer Programming II (3)

A second course in systems-oriented programming and computing science that builds upon the foundation set in CMPT 130 using a systems-oriented language such as C or C++. Topics: a review of the basic elements of programming; introduction to object-oriented programming (OOP); techniques for designing and testing programs; use and implementation of elementary data structures and algorithms; introduction to embedded systems programming. Prerequisite: CMPT 130. Students with credit for CMPT 125, 126, or 129 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 John Edgar
We 1:30 PM – 2:20 PM
Fr 12:30 PM – 2:20 PM
SUR 3310, Surrey
SUR 3310, Surrey
D101 John Edgar
We 2:30 PM – 3:20 PM
SUR 4080, Surrey
D102 John Edgar
We 3:30 PM – 4:20 PM
SUR 4080, Surrey
D103 John Edgar
We 4:30 PM – 5:20 PM
SUR 4080, Surrey
D104 John Edgar
We 12:30 PM – 1:20 PM
SUR 4080, Surrey

and all of

CMPT 225 - Data Structures and Programming (3)

Introduction to a variety of practical and important data structures and methods for implementation and for experimental and analytical evaluation. Topics include: stacks, queues and lists; search trees; hash tables and algorithms; efficient sorting; object-oriented programming; time and space efficiency analysis; and experimental evaluation. Prerequisite: (MACM 101 and ((CMPT 125 and 127), CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252). Quantitative.

Section Instructor Day/Time Location
D100 David Mitchell
Mo 1:30 PM – 2:20 PM
We 1:30 PM – 2:20 PM
Fr 1:30 PM – 2:20 PM
DFA 300, Burnaby
SSCB 9201, Burnaby
SSCB 9201, Burnaby
D101 David Mitchell
Mo 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D102 David Mitchell
Mo 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D103 David Mitchell
Mo 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D104 David Mitchell
Mo 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D105 David Mitchell
Fr 2:30 PM – 3:20 PM
ASB 9838, Burnaby
D106 David Mitchell
Fr 2:30 PM – 3:20 PM
ASB 9838, Burnaby
D107 David Mitchell
Fr 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D108 David Mitchell
Fr 3:30 PM – 4:20 PM
ASB 9838, Burnaby
E100 Leonid Chindelevitch
Tu 5:30 PM – 8:20 PM
HCC 1900, Vancouver
MACM 101 - Discrete Mathematics I (3)

Introduction to counting, induction, automata theory, formal reasoning, modular arithmetic. Prerequisite: BC Math 12 (or equivalent), or any of MATH 100, 150, 151, 154, 157. Quantitative/Breadth-Science.

Section Instructor Day/Time Location
D100 Binay Bhattacharya
Mo, Fr 10:30 AM – 11:20 AM
We 10:30 AM – 11:20 AM
SWH 10081, Burnaby
SSCB 9201, Burnaby
D101 Binay Bhattacharya
Tu 9:30 AM – 10:20 AM
AQ 5008, Burnaby
D102 Binay Bhattacharya
Tu 9:30 AM – 10:20 AM
RCB 5125, Burnaby
D103 Binay Bhattacharya
Tu 2:30 PM – 3:20 PM
AQ 5035, Burnaby
D104 Binay Bhattacharya
Tu 2:30 PM – 3:20 PM
AQ 5047, Burnaby
D105 Binay Bhattacharya
Tu 3:30 PM – 4:20 PM
AQ 5014, Burnaby
D106 Binay Bhattacharya
Tu 3:30 PM – 4:20 PM
AQ 5035, Burnaby
D107 Binay Bhattacharya
Tu 4:30 PM – 5:20 PM
AQ 5020, Burnaby
D108 Binay Bhattacharya
Tu 4:30 PM – 5:20 PM
AQ 5039, Burnaby
D200 Steve Pearce
Tu 1:30 PM – 2:20 PM
Th 12:30 PM – 2:20 PM
SWH 10081, Burnaby
SSCB 9201, Burnaby
D201 Steve Pearce
We 9:30 AM – 10:20 AM
AQ 2104, Burnaby
D202 Steve Pearce
We 9:30 AM – 10:20 AM
BLU 11901, Burnaby
D203 Steve Pearce
We 2:30 PM – 3:20 PM
BLU 11911, Burnaby
D204 Steve Pearce
We 2:30 PM – 3:20 PM
WMC 2260, Burnaby
D205 Steve Pearce
We 3:30 PM – 4:20 PM
WMC 2268, Burnaby
D206 Steve Pearce
We 3:30 PM – 4:20 PM
BLU 11911, Burnaby
D207 Steve Pearce
We 4:30 PM – 5:20 PM
BLU 11911, Burnaby
D208 Steve Pearce
We 4:30 PM – 5:20 PM
WMC 2268, Burnaby
D300 Toby Donaldson
Mo, We, Fr 11:30 AM – 12:20 PM
SUR 3310, Surrey
D301 Toby Donaldson
Mo 12:30 PM – 1:20 PM
SUR 3120, Surrey
D302 Toby Donaldson
Mo 1:30 PM – 2:20 PM
SUR 3120, Surrey
D303 Toby Donaldson
Mo 2:30 PM – 3:20 PM
SUR 3120, Surrey
D304 Toby Donaldson
Mo 3:30 PM – 4:20 PM
SUR 3120, Surrey
MACM 201 - Discrete Mathematics II (3)

A continuation of MACM 101. Topics covered include graph theory, trees, inclusion-exclusion, generating functions, recurrence relations, and optimization and matching. Prerequisite: MACM 101 or (ENSC 251 and one of MATH 232 or MATH 240). Quantitative.

Section Instructor Day/Time Location
D100 Bojan Mohar
Mo 12:30 PM – 1:20 PM
We, Fr 12:30 PM – 1:20 PM
DFA 300, Burnaby
DFA 300, Burnaby
D200 Mahsa Faizrahnemoon
Mo, We, Fr 8:30 AM – 9:20 AM
SUR 5280, Surrey
OPO1
TBD
OP02
TBD
MATH 208W - Introduction to Operations Research (3)

Introduction to methods of operations research: linear and nonlinear programming, simulation, and heuristic methods. Applications to transportation, assignment, scheduling, and game theory. Exposure to mathematical models of industry and technology. Emphasis on computation for analysis and simulation. Prerequisite: MATH 150 or 151 or 154 or 157. Students with credit for MATH 208 may not take this course for further credit. Writing/Quantitative.

Section Instructor Day/Time Location
D100 Tamon Stephen
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SUR 2710, Surrey
SUR 2710, Surrey
MATH 251 - Calculus III (3)

Rectangular, cylindrical and spherical coordinates. Vectors, lines, planes, cylinders, quadric surfaces. Vector functions, curves, motion in space. Differential and integral calculus of several variables. Vector fields, line integrals, fundamental theorem for line integrals, Green's theorem. Prerequisite: MATH 152; or MATH 155 or MATH 158 with a grade of at least B. Recommended: It is recommended that MATH 240 or 232 be taken before or concurrently with MATH 251. Quantitative.

Section Instructor Day/Time Location
E100 Steven Ruuth
Mo, We 4:30 PM – 5:50 PM
WMC 3520, Burnaby
OP01
TBD
STAT 270 - Introduction to Probability and Statistics (3)

Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158. Students wishing an intuitive appreciation of a broad range of statistical strategies may wish to take STAT 100 first. Quantitative.

Section Instructor Day/Time Location
C100 Distance Education
D100 Boxin Tang
Mo 9:30 AM – 10:20 AM
We, Fr 9:30 AM – 10:20 AM
EDB 7618, Burnaby
SWH 10081, Burnaby
D900 Maryam DehghaniEstarki
Tu 8:30 AM – 10:20 AM
Th 8:30 AM – 9:20 AM
SUR 3170, Surrey
SUR 3170, Surrey
OP01
TBD
OP09
TBD
STAT 285 - Intermediate Probability and Statistics (3)

This course is a continuation of STAT 270. Review of probability models. Procedures for statistical inference using survey results and experimental data. Statistical model building. Elementary design of experiments. Regression methods. Introduction to categorical data analysis. Prerequisite: STAT 270. Quantitative.

Section Instructor Day/Time Location
D100 Liangliang Wang
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SECB 1013, Burnaby
SECB 1012, Burnaby
D101 Liangliang Wang
Mo 8:30 AM – 9:20 AM
AQ 5008, Burnaby
D102 Liangliang Wang
Mo 9:30 AM – 10:20 AM
AQ 5008, Burnaby
D104 Liangliang Wang
We 12:30 PM – 1:20 PM
AQ 5051, Burnaby

and one of

MATH 150 - Calculus I with Review (4)

Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Topics as for Math 151 with a more extensive review of functions, their properties and their graphs. Recommended for students with no previous knowledge of Calculus. In addition to regularly scheduled lectures, students enrolled in this course are encouraged to come for assistance to the Calculus Workshop (Burnaby), or Math Open Lab (Surrey). Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B+, or MATH 100 with a grade of at least B-, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 151, 154 or 157 may not take MATH 150 for further credit. Quantitative.

Section Instructor Day/Time Location
C100 Distance Education
D100
Mo, Tu, We, Fr 8:30 AM – 9:20 AM
WMC 3520, Burnaby
D200
Mo, We, Fr 11:30 AM – 12:20 PM
We 1:30 PM – 2:20 PM
SUR 2750, Surrey
SUR 2750, Surrey
OP01
TBD
OP02
TBD
MATH 151 - Calculus I (3)

Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Logarithmic and exponential functions, trigonometric functions, inverse functions. Limits, continuity, and derivatives. Techniques of differentiation, including logarithmic and implicit differentiation. The Mean Value Theorem. Applications of differentiation including extrema, curve sketching, Newton's method. Introduction to modeling with differential equations. Polar coordinates, parametric curves. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least A, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 154 or 157 may not take MATH 151 for further credit. Quantitative.

MATH 154 - Calculus I for the Biological Sciences (3) *

Designed for students specializing in the biological and medical sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications; mathematical models of biological processes. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 157 may not take MATH 154 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Ladislav Stacho
Mo 8:30 AM – 9:20 AM
We, Fr 8:30 AM – 9:20 AM
SSCB 9200, Burnaby
SSCB 9200, Burnaby
OP01
TBD
MATH 157 - Calculus I for the Social Sciences (3) *

Designed for students specializing in business or the social sciences. Topics include: limits, growth rate and the derivative; logarithmic exponential and trigonometric functions and their application to business, economics, optimization and approximation methods; functions of several variables. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 154 may not take MATH 157 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Luis Goddyn
Mo, Fr 11:30 AM – 12:20 PM
We 11:30 AM – 12:20 PM
SWH 10081, Burnaby
DFA 300, Burnaby
D200 Natalia Kouzniak
Mo, We, Fr 12:30 PM – 1:20 PM
SUR 3090, Surrey
OP01
TBD
OP02
TBD

and one of

MATH 152 - Calculus II (3)

Riemann sum, Fundamental Theorem of Calculus, definite, indefinite and improper integrals, approximate integration, integration techniques, applications of integration. First-order separable differential equations and growth models. Sequences and series, series tests, power series, convergence and applications of power series. Prerequisite: MATH 150 or 151; or MATH 154 or 157 with a grade of at least B. Students with credit for MATH 155 or 158 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 8:30 AM – 9:20 AM
SSCC 9001, Burnaby
D200
Mo, We, Fr 11:30 AM – 12:20 PM
SUR 5280, Surrey
D300
Mo, We, Fr 8:30 AM – 9:20 AM
WMC 2810, Burnaby
OP01
TBD
OP02
TBD
MATH 155 - Calculus II for the Biological Sciences (3) *

Designed for students specializing in the biological and medical sciences. Topics include: the integral, partial derivatives, differential equations, linear systems, and their applications; mathematical models of biological processes. Prerequisite: MATH 150, 151 or 154; or MATH 157 with a grade of at least B. Students with credit for MATH 152 or 158 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Petr Lisonek
Mo, We, Fr 8:30 AM – 9:20 AM
RCB IMAGTH, Burnaby
D200 Natalia Kouzniak
Mo, We, Fr 9:30 AM – 10:20 AM
SUR 5280, Surrey
OP01
TBD
OP02
TBD
MATH 158 - Calculus II for the Social Sciences (3) *

Theory of integration and its applications; introduction to multivariable calculus with emphasis on partial derivatives and their applications; introduction to differential equations with emphasis on some special first-order equations and their applications to economics and social sciences; continuous probability models; sequences and series. Prerequisite: MATH 150 or 151 or 154 or 157. Students with credit for MATH 152 or 155 may not take MATH 158 for further credit. Quantitative.

Section Instructor Day/Time Location
E100 Michael Monagan
Mo 4:30 PM – 5:20 PM
We 4:30 PM – 6:20 PM
SSCC 9001, Burnaby
SSCC 9001, Burnaby
OP01
TBD

and one of

MATH 232 - Applied Linear Algebra (3) *

Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 make not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Cedric Chauve
Mo, We, Fr 11:30 AM – 12:20 PM
SSCC 9001, Burnaby
D200 Randall Pyke
Mo, We, Fr 2:30 PM – 3:20 PM
SUR 3090, Surrey
OP01
TBD
OP02
TBD
MATH 240 - Algebra I: Linear Algebra (3)

Linear equations, matrices, determinants. Real and abstract vector spaces, subspaces and linear transformations; basis and change of basis. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. Applications. Subject is presented with an abstract emphasis and includes proofs of the basic theorems. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 232 cannot take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100
Mo, We, Fr 11:30 AM – 12:20 PM
BLU 10921, Burnaby
OP01
TBD

* with a B grade or better

Upper Division Requirements

Students complete all of

MATH 308 - Linear Optimization (3)

Linear programming modelling. The simplex method and its variants. Duality theory. Post-optimality analysis. Applications and software. Additional topics may include: game theory, network simplex algorithm, and convex sets. Prerequisite: MATH 150, 151, 154, or 157 and MATH 240 or 232. Quantitative.

Section Instructor Day/Time Location
D100 Luis Goddyn
Mo 2:30 PM – 3:20 PM
We 2:30 PM – 3:20 PM
Fr 2:30 PM – 3:20 PM
AQ 3005, Burnaby
WMC 3260, Burnaby
SWH 10041, Burnaby
D101
Tu 2:30 PM – 3:20 PM
WMC 2830, Burnaby
D102
Tu 3:30 PM – 4:20 PM
TASC2 8500, Burnaby
D103
Tu 4:30 PM – 5:20 PM
AQ 5037, Burnaby
MATH 348 - Probabilistic Models in Operations Research (3)

Inventory theory, Markov decision process and applications, queuing theory, forecasting models, decision Analysis and games, probabilistic dynamic programming, simulation modeling, project planning using PERT/CPM, sequencing and scheduling. Prerequisite: STAT 270. Pre-/Co-requisite: MATH 308. Quantitative.

MATH 402W - Operations Research Clinic (4)

Problems from operations research will be presented and discussed in class. Students will also work on a problem of their choice and present their solution in report form as well as a presentation. Prerequisite: MATH 308 and STAT 285. Writing/Quantitative.

Section Instructor Day/Time Location
D100 Tamon Stephen
Tu, Th 10:30 AM – 12:20 PM
SUR 2980, Surrey

and four of

MATH 309 - Continuous Optimization (3)

Theoretical and computational methods for investigating the minimum of a function of several real variables with and without inequality constraints. Applications to operations research, model fitting, and economic theory. Prerequisite: MATH 232 or 240, and 251. Quantitative.

MATH 408 - Discrete Optimization (3)

Model building using integer variables, computer solution, relaxations and lower bounds, heuristics and upper bounds, branch and bound algorithms, cutting plane algorithms, valid inequalities and facets, branch and cut algorithms, Lagrangian duality, column generation of algorithms, heuristics algorithms and analysis. Prerequisite: MATH 308. Quantitative.

MATH 448 - Network Flows (3)

Applications of network flow models; flow decomposition; polynomial algorithms for shortest paths, maximum flows and minimum costs flows; convex cost flows; generalized flows, multi-commodity flows. Prerequisite: MATH 308. Recommended: MATH 345. Quantitative.

Section Instructor Day/Time Location
D100 Abraham Punnen
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SUR 3240, Surrey
SUR 3240, Surrey
STAT 350 - Linear Models in Applied Statistics (3)

Theory and application of linear regression. Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model diagnostics. Introduction to weighted least squares and generalized linear models. Prerequisite: STAT 285, MATH 251, and one of MATH 232 or MATH 240. Quantitative.

Section Instructor Day/Time Location
E100 Gamage Perera
Mo 5:30 PM – 7:20 PM
We 5:30 PM – 6:20 PM
SUR 5140, Surrey
SUR 5140, Surrey
E101 Gamage Perera
We 8:30 AM – 9:20 AM
SUR 2710, Surrey
E102 Gamage Perera
We 9:30 AM – 10:20 AM
SUR 2710, Surrey
STAT 380 - Introduction to Stochastic Processes (3)

Review of discrete and continuous probability models and relationships between them. Exploration of conditioning and conditional expectation. Markov chains. Random walks. Continuous time processes. Poisson process. Markov processes. Gaussian processes. Prerequisite: STAT 330, or all of: STAT 285, MATH 208, and MATH 251. Quantitative.

Section Instructor Day/Time Location
D100 Richard Lockhart
Mo, We, Fr 9:30 AM – 10:20 AM
AQ 5016, Burnaby
D101 Richard Lockhart
Fr 10:30 AM – 11:20 AM
AQ 5009, Burnaby
D102 Richard Lockhart
Fr 11:30 AM – 12:20 PM
AQ 5009, Burnaby

and at least one of

CMPT 305 - Computer Simulation and Modelling (3)

This course is an introduction to the modelling, analysis, and computer simulation of complex systems. Topics include analytic modelling, discrete event simulation, experimental design, random number generation, and statistical analysis. Prerequisite: CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and STAT 270.

CMPT 307 - Data Structures and Algorithms (3)

Analysis and design of data structures for lists, sets, trees, dictionaries, and priority queues. A selection of topics chosen from sorting, memory management, graphs and graph algorithms. Prerequisite: CMPT 225, MACM 201, MATH 151 (or MATH 150), and MATH 232 or 240.

Section Instructor Day/Time Location
D100 Valentine Kabanets
Mo 10:30 AM – 11:20 AM
We, Fr 10:30 AM – 11:20 AM
WMC 3260, Burnaby
AQ 3005, Burnaby
D300 Valentine Kabanets
Mo 2:30 PM – 3:20 PM
We 2:30 PM – 3:20 PM
Fr 2:30 PM – 3:20 PM
AQ 3159, Burnaby
SSCC 9002, Burnaby
SSCK 9500, Burnaby
MACM 316 - Numerical Analysis I (3)

A presentation of the problems commonly arising in numerical analysis and scientific computing and the basic methods for their solutions. Prerequisite: MATH 152 or 155 or 158, and MATH 232 or 240, and computing experience. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 12:30 PM – 1:20 PM
AQ 3182, Burnaby
D101
We 2:30 PM – 3:20 PM
AQ 5016, Burnaby
D102
We 3:30 PM – 4:20 PM
AQ 5016, Burnaby
D103
We 4:30 PM – 5:20 PM
AQ 5016, Burnaby
D104
Th 9:30 AM – 10:20 AM
AQ 5018, Burnaby
D105
Th 10:30 AM – 11:20 AM
AQ 5030, Burnaby
D106
Th 11:30 AM – 12:20 PM
RCB 6125, Burnaby
D107
We 5:30 PM – 6:20 PM
AQ 5016, Burnaby
MATH 343 - Applied Discrete Mathematics (3)

Structures and algorithms, generating elementary combinatorial objects, counting (integer partitions, set partitions, Catalan families), backtracking algorithms, branch and bound, heuristic search algorithms. Prerequisite: MACM 201 (with a grade of at least B-). Recommended: knowledge of a programming language. Quantitative.

MATH 345 - Introduction to Graph Theory (3)

Fundamental concepts, trees and distances, matchings and factors, connectivity and paths, network flows, integral flows. Prerequisite: MACM 201 (with a grade of at least B-). Quantitative.

and at least 6 additional units from the following list

ECON 435 - Econometric Methods (5)

The application of econometric techniques to the empirical investigation of economic issues. Prerequisite: ECON 201 or 301 and BUEC 333. Entry into this course requires a minimum CGPA of 3.0 or permission of the department. Quantitative.

STAT 341 - Introduction to Statistical Computing and Exploratory Data Analysis - R (2)

Introduces the R statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. Students with credit for STAT 340 may not take STAT 341 for further credit.

Section Instructor Day/Time Location
D100 Brad McNeney
Th 12:30 PM – 2:20 PM
EDB 7618, Burnaby
D101 Brad McNeney
Fr 12:30 PM – 1:20 PM
SECB 1014, Burnaby
D102 Brad McNeney
Fr 1:30 PM – 2:20 PM
SECB 1014, Burnaby
D103 Brad McNeney
We 12:30 PM – 1:20 PM
SECB 1014, Burnaby
D104 Brad McNeney
We 1:30 PM – 2:20 PM
SECB 1014, Burnaby
STAT 342 - Introduction to Statistical Computing and Exploratory Data Analysis - SAS (2)

Introduces the SAS statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333. Students with credit for STAT 340 may not take STAT 342 for further credit.

STAT 410 - Statistical Analysis of Sample Surveys (3)

An introduction to the major sample survey designs and their mathematical justification. Associated statistical analyses. Prerequisite: STAT 350. Quantitative.

Section Instructor Day/Time Location
E100 Jack Davis
Mo 4:30 PM – 6:20 PM
We 4:30 PM – 5:20 PM
RCB 8100, Burnaby
AQ 4150, Burnaby
E101 Jack Davis
We 3:30 PM – 4:20 PM
AQ 5036, Burnaby
E102 Jack Davis
We 5:30 PM – 6:20 PM
AQ 5027, Burnaby
STAT 430 - Statistical Design and Analysis of Experiments (3)

An extension of the designs discussed in STAT 350 to include more than one blocking variable, incomplete block designs, fractional factorial designs, and response surface methods. Prerequisite: STAT 350 (or MATH 372). Quantitative.

STAT 460 - Bayesian Statistics (3)

The Bayesian approach to statistics is an alternative and increasingly popular way of quantifying uncertainty in the presence of data. This course considers comparative statistical inference, prior distributions, Bayesian computation, and applications. Prerequisite: STAT 330 and 350. Quantitative.

STAT 475 - Applied Discrete Data Analysis (3)

Introduction to standard methodology for analyzing categorical data including chi-squared tests for two- and multi-way contingency tables, logistic regression, and loglinear (Poisson) regression. Prerequisite: STAT 302 or STAT 305 or STAT 350 or BUEC 333 or equivalent. Students with credit for the former STAT 402 or 602 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Joan Hu
Tu 10:30 AM – 11:20 AM
Th 9:30 AM – 11:20 AM
AQ 3005, Burnaby
AQ 3005, Burnaby
D101 Joan Hu
We 9:30 AM – 10:20 AM
AQ 4125, Burnaby
D102 Joan Hu
We 3:30 PM – 4:20 PM
AQ 5028, Burnaby
D103 Joan Hu
We 4:30 PM – 5:20 PM
AQ 5038, Burnaby
D104 Joan Hu
We 5:30 PM – 6:20 PM
AQ 5015, Burnaby
STAT 485 - Applied Time Series Analysis (3)

Introduction to linear time series analysis including moving average, autoregressive and ARIMA models, estimation, data analysis, forecasting errors and confidence intervals, conditional and unconditional models, and seasonal models. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.

Interdisciplinary Requirement

With advisor approval, students also complete at least 15 units from application areas. Application courses are chosen from ACMA, BUEC, BUS, ECON, MACM, MATH, REM and STAT courses. Courses used to fulfil upper division requirements cannot be used to fulfil this requirement. If the operations research major is completed as part of a second bachelor's degree, then the interdisciplinary requirement may be waived if the previous degree contains an approved major. Approvals are given individually. Those majors that are approved will not be limited to the disciplines listed above.

University Degree Requirements

Students must also satisfy University degree requirements for degree completion.

Writing, Quantitative, and Breadth Requirements

Students admitted to Simon Fraser University beginning in the fall 2006 term must meet writing, quantitative and breadth requirements as part of any degree program they may undertake. See Writing, Quantitative, and Breadth Requirements for university-wide information.

WQB Graduation Requirements

A grade of C- or better is required to earn W, Q or B credit

Requirement

Units

Notes
W - Writing

6

Must include at least one upper division course, taken at Simon Fraser University within the student’s major subject
Q - Quantitative

6

Q courses may be lower or upper division
B - Breadth

18

Designated Breadth Must be outside the student’s major subject, and may be lower or upper division
6 units Social Sciences: B-Soc
6 units Humanities: B-Hum
6 units Sciences: B-Sci

6

Additional Breadth 6 units outside the student’s major subject (may or may not be B-designated courses, and will likely help fulfil individual degree program requirements)

Students choosing to complete a joint major, joint honours, double major, two extended minors, an extended minor and a minor, or two minors may satisfy the breadth requirements (designated or not designated) with courses completed in either one or both program areas.

 

Residency Requirements and Transfer Credit

  • At least half of the program's total units must be earned through Simon Fraser University study.
  • At least two thirds of the program's total upper division units must be earned through Simon Fraser University study.

Elective Courses

In addition to the courses listed above, students should consult an academic advisor to plan the remaining required elective courses.