Please note:

To view the Summer 2022 Academic Calendar, go to www.sfu.ca/students/calendar/2022/summer.html.

Department of Statistics and Actuarial Science | Faculty of Science Simon Fraser University Calendar | Fall 2022

Data Science Honours

Bachelor of Science

The Department of Statistics and Actuarial Science and its partners, the Department of Mathematics, the Beedie School of Business, and the School of Computing Science, offer an honours program in Data Science (DATA) leading to a bachelor of science (BSc) with honours degree. This is a highly structured program providing a multidisciplinary approach to quantitative methods for business and industry in an environment of rapid changes in technology. The honours program offers specialization in one of three concentrations: Mathematics, Statistics, or Open Concentration.

The program is managed by a steering committee consisting of representatives from the above-mentioned departments, and faculty serve as liaisons between participating departments and the program director.

Students formally apply to be admitted into the program. Applications can be considered both for students entering Simon Fraser University, and for students already enrolled. Admission into the program is decided on a competitive basis. Students must maintain a 3.0 cumulative grade point average (CGPA) in DATA program course work to remain in the program and to graduate. It is strongly recommended that students contact the Statistics advisor or program director early about admission and scheduling.

Students who wish to combine the DATA honours program with another major or minor program should consult with the Statistics advisor.

More information can be found on our website: https://www.sfu.ca/stat-actsci/undergraduate/current-students/program-info/data-science.html.

Program Requirements

Under University regulations, an honours degree requires the completion of a minimum of 120 units, including a minimum of 60 upper division units. Honours program students require a graduation cumulative grade point average of not less than 3.00.

Mathematics Concentration Requirements

Lower Division Requirements

Students complete a minimum of 65 units.

Business Administration

Students complete all of

BUS 200 - Business Fundamentals (3)

Explore the fundamentals of modern business and organizational management. Working with case studies, students will build upon the basics of revenue, profits, contribution and costs, as well as integrate advanced aspects of business models, innovation, competitive advantage, core competence, and strategic analysis. Breadth-Social Sciences.

Section Instructor Day/Time Location
D100 Sasha Ramnarine
Th 2:30 PM – 5:20 PM
AQ 3005, Burnaby
E100 Shannon Wong
We 5:30 PM – 8:20 PM
AQ 3005, Burnaby
BUS 217W - Critical Thinking in Business (3)

Examine and review today's global economy through critical analysis of differing perspectives. Develop and improve critical thinking and communication skills appropriate to the business environment. Prerequisite: BUS 201 with a minimum grade of C- and 15 units; OR 45 units and corequisite: BUS 202; OR business administration joint major, joint honours, or double degree students with 45 units; OR data science major with 15 units. Writing.

Section Instructor Day/Time Location
D100 Luana Carcano
We 2:30 PM – 5:20 PM
AQ 3154, Burnaby
D200 Matthew Martell
Tu 2:30 PM – 5:20 PM
SRYC 5240, Surrey
D300 Susan Christie-Bell
We 2:30 PM – 5:20 PM
RCB 8100, Burnaby
D400 Matthew Martell
Th 9:30 AM – 12:20 PM
WMC 2230, Burnaby
E100 Jerome Francis
We 5:30 PM – 8:20 PM
WMC 2230, Burnaby
E200 Michelle Corbett
Tu 5:30 PM – 8:20 PM
RCB 8100, Burnaby
BUS 251 - Financial Accounting I (3)

An introduction to financial accounting, including accounting terminology, understanding financial statements, analysis of a business entity using financial statements. Includes also time value of money and a critical review of the conventional accounting system. Prerequisite: 12 units. Quantitative.

Section Instructor Day/Time Location
D100 Susan Bubra
Th 12:30 PM – 2:20 PM
RCB IMAGTH, Burnaby
D101 Th 2:30 PM – 3:20 PM
BLU 10655, Burnaby
D102 Th 6:30 PM – 7:20 PM
WMC 2523, Burnaby
D103 Th 3:30 PM – 4:20 PM
BLU 10655, Burnaby
D104 Th 6:30 PM – 7:20 PM
WMC 3511, Burnaby
D105 Th 4:30 PM – 5:20 PM
WMC 3253, Burnaby
D106 Th 4:30 PM – 5:20 PM
WMC 3255, Burnaby
D107 Th 5:30 PM – 6:20 PM
WMC 3513, Burnaby
D108 Th 5:30 PM – 6:20 PM
WMC 3515, Burnaby
D200 Praise Ma
Fr 10:30 AM – 12:20 PM
SRYC 5240, Surrey
D201 Fr 12:30 PM – 1:20 PM
SRYC 5060, Surrey
D202 Fr 12:30 PM – 1:20 PM
SRYC 5320, Surrey
D203 Fr 1:30 PM – 2:20 PM
SRYC 5060, Surrey
D204 Fr 1:30 PM – 2:20 PM
SRYC 5320, Surrey
E100 Susan Bubra
Th 5:30 PM – 7:20 PM
RCB IMAGTH, Burnaby
E101 Th 7:30 PM – 8:20 PM
WMC 3253, Burnaby
E102 Th 7:30 PM – 8:20 PM
WMC 3250, Burnaby
E103 Th 7:30 PM – 8:20 PM
WMC 2507, Burnaby
E104 Th 8:30 PM – 9:20 PM
WMC 3513, Burnaby
BUS 272 - Behaviour in Organizations (3)

Theories, concepts and issues in the field of organizational behaviour with an emphasis on individual and team processes. Core topics include employee motivation and performance, stress management, communication, work perceptions and attitudes, decision-making, team dynamics, employee involvement and conflict management. Prerequisite: 12 units.

Section Instructor Day/Time Location
D100 Sam Thiara
Tu 10:30 AM – 12:20 PM
SSCC 9002, Burnaby
D101 Tu 12:30 PM – 1:20 PM
AQ 2122, Burnaby
D102 Tu 12:30 PM – 1:20 PM
WMC 3513, Burnaby
D103 Tu 1:30 PM – 2:20 PM
WMC 3515, Burnaby
D104 Tu 1:30 PM – 2:20 PM
AQ 5006, Burnaby
D105 Tu 2:30 PM – 3:20 PM
AQ 2122, Burnaby
D106 Tu 2:30 PM – 3:20 PM
WMC 2260, Burnaby
D107 Tu 3:30 PM – 4:20 PM
WMC 3513, Burnaby
D200 Sam Thiara
Th 10:30 AM – 12:20 PM
SRYC 3170, Surrey
D201 Th 12:30 PM – 1:20 PM
SRYC 5060, Surrey
D202 Th 12:30 PM – 1:20 PM
SRYC 5320, Surrey
D203 Th 1:30 PM – 2:20 PM
SRYC 5060, Surrey
D204 Th 1:30 PM – 2:20 PM
SRYC 5320, Surrey
D300 William Scott
Tu 12:30 PM – 2:20 PM
EDB 7618, Burnaby
D301 Tu 2:30 PM – 3:20 PM
WMC 3513, Burnaby
D302 Tu 2:30 PM – 3:20 PM
WMC 3517, Burnaby
D303 Tu 3:30 PM – 4:20 PM
WMC 3517, Burnaby
D304 Tu 3:30 PM – 4:20 PM
BLU 10901, Burnaby
D305 Tu 4:30 PM – 5:20 PM
WMC 2533, Burnaby
E100 Chris Zatzick
We 4:30 PM – 6:20 PM
SSCC 9002, Burnaby
E101 We 6:30 PM – 7:20 PM
AQ 5009, Burnaby
E102 We 6:30 PM – 7:20 PM
AQ 5014, Burnaby
E103 We 6:30 PM – 7:20 PM
AQ 5004, Burnaby
E104 We 7:30 PM – 8:20 PM
AQ 5004, Burnaby

Computing Science

Students complete all 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, e.g. Python. The students will be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode; data types and control structures; fundamental algorithms; recursion; reading and writing files; measuring performance of algorithms; debugging tools; basic terminal navigation using shell commands. 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, We, Fr 9:30 AM – 10:20 AM
AQ 3181, Burnaby
D300 Diana Cukierman
Mo, We, Fr 1:30 PM – 2:20 PM
SSCB 9200, Burnaby
D400 Toby Donaldson
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SRYE 1002, Surrey
SRYE 1002, Surrey
OL01 Mo, We, Fr 4:30 PM – 5:20 PM
Distance Education
CMPT 125 - Introduction to Computing Science and Programming II (3)

A rigorous introduction to computing science and computer programming, suitable for students who already have some background in computing science and programming. Intended for students who will major in computing science or a related program. Topics include: memory management; fundamental algorithms; formally analyzing the running time of algorithms; abstract data types and elementary data structures; object-oriented programming and software design; specification and program correctness; reading and writing files; debugging tools; shell commands. Prerequisite: CMPT 120 or CMPT 130, with a minimum grade of C-. Students with credit for CMPT 126, 129, 135 or CMPT 200 or higher may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Igor Shinkar
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
AQ 3182, Burnaby
AQ 3181, Burnaby
D101 Igor Shinkar
Th 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D102 Igor Shinkar
Th 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D103 Igor Shinkar
Th 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D104 Igor Shinkar
Th 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D105 Igor Shinkar
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D106 Igor Shinkar
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D107 Igor Shinkar
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
D108 Igor Shinkar
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
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, CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252), all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 David Mitchell
Mo, We, Fr 1:30 PM – 2:20 PM
WMC 3520, Burnaby
D101 David Mitchell
Tu 8:30 AM – 9:20 AM
ASB 9838, Burnaby
D102 David Mitchell
Tu 8:30 AM – 9:20 AM
ASB 9838, Burnaby
D103 David Mitchell
Tu 9:30 AM – 10:20 AM
ASB 9838, Burnaby
D104 David Mitchell
Tu 9:30 AM – 10:20 AM
ASB 9838, Burnaby
D105 David Mitchell
Tu 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D106 David Mitchell
Tu 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D107 David Mitchell
Tu 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D108 David Mitchell
Tu 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D200 Anne Lavergne
Tu 2:30 PM – 4:20 PM
Fr 2:30 PM – 3:20 PM
SRYE 2016, Surrey
SRYE 2016, Surrey
D201 Anne Lavergne
Mo 2:30 PM – 3:20 PM
SRYE 4024, Surrey
D202 Anne Lavergne
Mo 2:30 PM – 3:20 PM
SRYE 4013, Surrey
D203 Anne Lavergne
Mo 4:30 PM – 5:20 PM
SRYE 4024, Surrey
D204 Anne Lavergne
Mo 4:30 PM – 5:20 PM
SRYE 4013, Surrey
D205 Anne Lavergne
Mo 5:30 PM – 6:20 PM
SRYE 4024, Surrey
CMPT 276 - Introduction to Software Engineering (3)

An overview of various techniques used for software development and software project management. Major tasks and phases in modern software development, including requirements, analysis, documentation, design, implementation, testing,and maintenance. Project management issues are also introduced. Students complete a team project using an iterative development process. Prerequisite: One W course, CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and (MATH 151 or MATH 150), all with a minimum grade of C-. MATH 154 or MATH 157 with at least a B+ may be substituted for MATH 151 or MATH 150. Students with credit for CMPT 275 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Saba Alimadadi Jani
Mo, We, Fr 10:30 AM – 11:20 AM
AQ 3149, Burnaby
D200 Rob Cameron
Mo 5:30 PM – 8:20 PM
AQ 3149, Burnaby
D300 Brian Fraser
Mo, We, Fr 1:30 PM – 2:20 PM
SRYE 3016, Surrey
CMPT 295 - Introduction to Computer Systems (3)

The curriculum introduces students to topics in computer architecture that are considered fundamental to an understanding of the digital systems underpinnings of computer systems. Prerequisite: Either (MACM 101 and (CMPT 125 or CMPT 135)) or (MATH 151 and CMPT 102 for students in an Applied Physics program), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Alaa Alameldeen
Arrvindh Shriraman
Mo 4:30 PM – 5:20 PM
Th 4:30 PM – 6:20 PM
SWH 10081, Burnaby
SWH 10081, Burnaby
D101 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D102 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D103 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D104 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D105 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D106 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D107 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D108 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D109 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D110 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby
D111 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby
D112 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby

Mathematics and Computing Science

Students complete all of

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 Andrei Bulatov
Mo 11:30 AM – 12:20 PM
We, Fr 11:30 AM – 12:20 PM
SWH 10081, Burnaby
SSCB 9201, Burnaby
D101 Andrei Bulatov
Fr 12:30 PM – 1:20 PM
AQ 5030, Burnaby
D102 Andrei Bulatov
Fr 12:30 PM – 1:20 PM
BLU 10901, Burnaby
D103 Andrei Bulatov
Fr 1:30 PM – 2:20 PM
BLU 10901, Burnaby
D104 Andrei Bulatov
Fr 1:30 PM – 2:20 PM
WMC 2531, Burnaby
D105 Andrei Bulatov
Fr 2:30 PM – 3:20 PM
AQ 5006, Burnaby
D106 Andrei Bulatov
Fr 2:30 PM – 3:20 PM
WMC 3517, Burnaby
D107 Andrei Bulatov
Fr 3:30 PM – 4:20 PM
WMC 2531, Burnaby
D108 Andrei Bulatov
Fr 3:30 PM – 4:20 PM
AQ 5009, Burnaby
D109 Andrei Bulatov
Fr 10:30 AM – 11:20 AM
AQ 5035, Burnaby
D200 Thomas Shermer
We 3:30 PM – 4:20 PM
Fr 2:30 PM – 4:20 PM
SRYE 1002, Surrey
SRYE 1002, Surrey
D201 Thomas Shermer
Tu 2:30 PM – 3:20 PM
SRYC 3240, Surrey
D202 Thomas Shermer
Tu 2:30 PM – 3:20 PM
SRYC 3250, Surrey
D203 Thomas Shermer
Tu 3:30 PM – 4:20 PM
SRYC 3240, Surrey
D204 Thomas Shermer
Tu 3:30 PM – 4:20 PM
SRYC 3250, Surrey
D205 Thomas Shermer
Tu 4:30 PM – 5:20 PM
SRYC 3240, Surrey
D206 Thomas Shermer
Tu 4:30 PM – 5:20 PM
SRYC 5060, Surrey
D207 Thomas Shermer
Tu 5:30 PM – 6:20 PM
SRYC 5060, Surrey
D208 Thomas Shermer
Tu 5:30 PM – 6:20 PM
SRYC 3040, 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 Matthew DeVos
Mo, We, Fr 12:30 PM – 1:20 PM
SSCC 9002, Burnaby
D200 Mahsa Faizrahnemoon
Mo, We, Fr 12:30 PM – 1:20 PM
SWH 10081, Burnaby
OP02 TBD
MACM 203 - Computing with Linear Algebra (2)

Using a mathematical software package for doing calculations in linear algebra. Development of computer models that analyze and illustrate applications of linear algebra. All calculations and experiments will be done in the Matlab software package. Topics include: large-scale matrix calculations, experiments with cellular automata, indexing, searching and ranking pages on the internet, population models, data fitting and optimization, image analysis, and cryptography. Prerequisite: One of CMPT 102, 120, 126, 128 or 130 and one of MATH 150, 151, 154 or 157 and one of MATH 232 or 240. MATH 232 or 240 can be taken as corequisite. Students in excess of 80 units may not take MACM 203 for further credit. Quantitative.

MACM 204 - Computing with Calculus (2)

Using a mathematical software package for doing computations from calculus. Development of computer models that analyze and illustrate applications of calculus. All calculations and experiments will be done in the Maple software package. Topics include: graphing functions and data, preparing visual aids for illustrating mathematical concepts, integration, Taylor series, numerical approximation methods, 3D visualization of curves and surfaces, multi-dimensional optimization, differential equations and disease spread models. Prerequisite: One of CMPT 102, 120, 126, 128 or 130 and MATH 251. MATH 251 can be taken as a corequisite. Students in excess of 80 units may not take MACM 204 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Michael Monagan
Tu 2:30 PM – 3:20 PM
AQ 3150, Burnaby
D101 Michael Monagan
We 2:30 PM – 3:20 PM
AQ 3148.2, Burnaby
D102 Michael Monagan
We 3:30 PM – 4:20 PM
AQ 3148.1, Burnaby
D103 Michael Monagan
We 4:30 PM – 5:20 PM
AQ 3148.1, Burnaby

Data Science

Students complete

DATA 180 - Undergraduate Seminar in Data Science (1)

A seminar primarily for students undertaking a major or an honours program in Data Science. Prerequisite: Major or honours in Data Science or permission of the program director. Students with credit for DATA (or MSSC) 480 cannot receive credit for DATA (or MSSC) 180.

Section Instructor Day/Time Location
E100 Jiguo Cao
Tu 6:30 PM – 8:20 PM
SWH 10041, Burnaby

Mathematics

Students complete 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
D100 Sophie Burrill
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9201, Burnaby
D101 Tu 8:30 AM – 9:20 AM
WMC 2503, Burnaby
D102 Tu 9:30 AM – 10:20 AM
WMC 2532, Burnaby
D103 Tu 10:30 AM – 11:20 AM
WMC 2503, Burnaby
D104 We 2:30 PM – 3:20 PM
WMC 2810, Burnaby
D105 We 3:30 PM – 4:20 PM
WMC 2810, Burnaby
D200 Jamie Mulholland
Mo, We, Fr 8:30 AM – 9:20 AM
RCB IMAGTH, Burnaby
D201 Tu 8:30 AM – 9:20 AM
AQ 5039, Burnaby
D202 Tu 1:30 PM – 2:20 PM
BLU 10921, Burnaby
D203 Tu 2:30 PM – 3:20 PM
AQ 5037, Burnaby
D204 Fr 2:30 PM – 3:20 PM
RCB 5120, Burnaby
D205 Fr 3:30 PM – 4:20 PM
RCB 5120, Burnaby
D400 Natalia Kouzniak
Mo, We, Fr 9:30 AM – 10:20 AM
SRYE 1002, Surrey
D401 Natalia Kouzniak
Th 12:30 PM – 1:20 PM
SRYC 2740, Surrey
D402 Natalia Kouzniak
Th 2:30 PM – 3:20 PM
SRYC 2740, Surrey
D403 Natalia Kouzniak
Th 1:30 PM – 2:20 PM
SRYC 2740, Surrey
OP01 TBD
OP02 TBD
OP03 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.

Section Instructor Day/Time Location
D100 Sophie Burrill
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9201, Burnaby
D200 Jamie Mulholland
Mo, We, Fr 8:30 AM – 9:20 AM
RCB IMAGTH, Burnaby
D400 Natalia Kouzniak
Mo, We, Fr 9:30 AM – 10:20 AM
SRYE 1002, Surrey
OP01 TBD
OP02 TBD
OP04 TBD
MATH 154 - Mathematics for the Life Sciences I (3)

Designed for students specializing in the life sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications, integration, and differential equations; mathematical models of biological processes and their implementation and analysis using software. 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 Ailene MacPherson
Mo, We, Fr 8:30 AM – 9:20 AM
SSCC 9001, Burnaby
D400 Ladislav Stacho
Mo, We, Fr 9:30 AM – 10:20 AM
SRYC 5280, Surrey
OP01 TBD
OP02 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; introduction to functions of several variables with emphasis on partial derivatives and extrema. 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 Imin Chen
Mo, We, Fr 11:30 AM – 12:20 PM
SSCC 9001, Burnaby
D400 Roghayeh Ebrahim Nataj
Mo, We, Fr 12:30 PM – 1:20 PM
SRYC 5280, Surrey
OP01 TBD
OP02 TBD

and all 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, with a minimum grade of C-; 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 Michael Monagan
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9200, Burnaby
OP01 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, with a minimum grade of C-. Students with credit for MATH 208 may not take this course for further credit. Writing/Quantitative.

MATH 242 - Introduction to Analysis I (3)

Mathematical induction. Limits of real sequences and real functions. Continuity and its consequences. The mean value theorem. The fundamental theorem of calculus. Series. Prerequisite: MATH 152 with a minimum grade of C-; or MATH 155 or 158 with a grade of B. Quantitative.

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 with a minimum grade of C-; 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
D100 Jake Levinson
Mo, We, Fr 8:30 AM – 9:20 AM
WMC 3520, Burnaby
D200 Marni Julie Mishna
Mo, We, Fr 8:30 AM – 9:20 AM
WMC 2830, Burnaby
D400 Roghayeh Ebrahim Nataj
Mo, We, Fr 8:30 AM – 9:20 AM
SRYC 5280, Surrey
OP01 TBD
OP02 TBD
OP03 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, with a minimum grade of C-; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 11:30 AM – 12:20 PM
SSCB 9200, Burnaby
D400 Randall Pyke
Mo, We, Fr 1:30 PM – 2:20 PM
SRYC 2600, Surrey
OP01 TBD
OP02 Mo, We, Fr 1:30 PM – 2:20 PM
,
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, with a minimum grade of C-; 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 Jake Levinson
Mo, We, Fr 11:30 AM – 12:20 PM
SWH 10041, Burnaby
OP01 TBD

Statistics

Students complete all of

STAT 240 - Introduction to Data Science (3)

Introduction to modern tools and methods for data acquisition, management, and visualization capable of scaling to Big Data. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, and one of CMPT 102, CMPT 120, CMPT 125, CMPT 128, CMPT 129, CMPT 130, all with a minimum grade of C- or permission of the instructor. STAT 260 is also recommended. Quantitative.

STAT 260 - Introductory R for Data Science (2)

An introduction to the R programming language for data science. Exploring data: visualization, transformation and summaries. Data wrangling: reading, tidying, and data types. No prior computer programming experience required. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, ECON 233, or POL 201, with a grade of at least C- or permission of the instructor. Corequisite: STAT 261. Students who have taken STAT 341 or STAT 360 first may not then take this course for further credit.

Section Instructor Day/Time Location
D100 David Stenning
Tu 2:30 PM – 4:20 PM
SSCB 9200, Burnaby
STAT 261 - Laboratory for Introductory R for Data Science (1)

A hands-on application of the R programming language for data science. Using the R concepts covered in STAT 260, students will explore (visualize, transform, and summarize) and wrangle (read and tidy) data. No prior computer programming experience required. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, ECON 233, or POL 201, with a grade of at least C- or permission of the instructor. Corequisite: STAT 260. Students who have taken STAT 341 or STAT 360 first may not then take this course for further credit.

Section Instructor Day/Time Location
D010 David Stenning
Th 6:30 PM – 7:20 PM
AQ 3148.2, Burnaby
D100 David Stenning
Tu 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
D200 David Stenning
Tu 5:30 PM – 6:20 PM
AQ 3148.2, Burnaby
D300 David Stenning
Tu 6:30 PM – 7:20 PM
AQ 3148.2, Burnaby
D400 David Stenning
We 3:30 PM – 4:20 PM
AQ 3148.2, Burnaby
D500 David Stenning
We 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
D600 David Stenning
We 5:30 PM – 6:20 PM
AQ 3148.2, Burnaby
D700 David Stenning
Th 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
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, with a minimum grade of C-. 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
D100 Sonja Isberg
Mo, We, Fr 9:30 AM – 10:20 AM
SSCB 9201, Burnaby
OL01 Distance Education
OP01 TBD

* Recommended

Upper Division Requirements

Students complete a minimum of 50 units.

Business Administration

Students complete all of

BUS 343 - Introduction to Marketing (3)

The environment of marketing; relation of social sciences to marketing; evaluation of marketing theory and research; assessment of demand, consumer behaviour analysis; market institutions; method and mechanics of distribution in domestic, foreign and overseas markets; sales organization; advertising; new product development, publicity and promotion; marketing programs. Prerequisite: 45 units. Students with credit for COMM 343 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Pei-Shiuan Lin
Tu 8:30 AM – 10:20 AM
AQ 3181, Burnaby
D101 Tu 10:30 AM – 11:20 AM
RCB 7100, Burnaby
D102 Tu 10:30 AM – 11:20 AM
RCB 8105, Burnaby
D103 Tu 10:30 AM – 11:20 AM
RCB 8104, Burnaby
D104 Tu 11:30 AM – 12:20 PM
RCB 8104, Burnaby
D105 Tu 11:30 AM – 12:20 PM
RCB 6100, Burnaby
D106 Tu 11:30 AM – 12:20 PM
RCB 6122, Burnaby
D107 Tu 12:30 PM – 1:20 PM
RCB 6100, Burnaby
D108 Tu 12:30 PM – 1:20 PM
RCB 6122, Burnaby
D109 Tu 12:30 PM – 1:20 PM
RCB 7105, Burnaby
D110 Tu 1:30 PM – 2:20 PM
RCB 7105, Burnaby
D111 Tu 1:30 PM – 2:20 PM
RCB 6100, Burnaby
D200 Pei-Shiuan Lin
Th 8:30 AM – 10:20 AM
SRYC 3090, Surrey
D201 Th 10:30 AM – 11:20 AM
SRYC 3260, Surrey
D202 Th 10:30 AM – 11:20 AM
SRYC 3010, Surrey
D203 Th 11:30 AM – 12:20 PM
SRYC 3260, Surrey
D204 Th 11:30 AM – 12:20 PM
SRYC 3010, Surrey
D205 Th 12:30 PM – 1:20 PM
SRYC 3010, Surrey
BUS 360W - Business Communication (4)

Helps students develop professional writing- and speaking-based communication strategies they can confidently adapt to a wide range of business situations. The course aims to raise their communication performance to a professionally acceptable level, rather than to memorize or theorize about communication knowledge: this is a “learn-by-doing” course. Students will improve their ability to conceptualize, analyze/evaluate, synthesize, and apply information to guide their thinking and finished products across various business contexts. As teamwork is a fundamental skill valued by employers, students will participate in a major team project to learn about and apply best practices for collaboration with respect to professional business communication. The primary means of instruction and learning is guided practice in both writing and presenting in response to realistic business contexts. Instruction and assessment focus on both the process of creating professional, finished products, as well as the quality of those products. Prerequisite: This course is open to students admitted prior to Fall 2014 to the business administration major, honours, or second degree program and who have 45 units, OR to students admitted Fall 2014 - Summer 2017 to the business administration major, honours, or second degree program and who have 45 units and BUS 130 or (BUS 201 or BUS 202) or BUS 301, with a minimum grade of C-, OR to students admitted Fall 2017 – Summer 2022 to the business administration major, honours, or second degree program and who have 45 units and BUS 130 or (BUS 201 or BUS 202) or BUS 301, and BUS 217W, both with a minimum grade of C-, OR to students admitted Fall 2022 onwards to the business administration major, honours, or second degree program, and who have 45 units; BUS 217W and (BUS 201 or BUS 202), both with a minimum grade of C-; and Corequisite: BUS 300, OR to business administration joint major or joint honours students with BUS 217W with a minimum grade of C- and 45 units, OR to business and economics joint major students with ECON 220W with a minimum grade of C- and 45 units, OR to mechatronic systems engineering and business administration double degree students with 45 units, OR to management systems science or actuarial science majors with 45 units OR to data science major with BUS 217W with a minimum grade of C- and 45 units. Students who have taken BUS 360 may not take this course for further credit. Writing.

Section Instructor Day/Time Location
D100 Leanne Barlow
Tu 2:30 PM – 5:20 PM
WMC 2507, Burnaby
D200 Darren Francis
We 9:30 AM – 12:20 PM
RCB 7100, Burnaby
D300 Kevin Stewart
Th 11:30 AM – 2:20 PM
WMC 3533, Burnaby
D400 Leanne Barlow
Tu 11:30 AM – 2:20 PM
WMC 2210, Burnaby
D500 Christian Venhuizen
Th 2:30 PM – 5:20 PM
SRYC 5100, Surrey
D600 Christian Venhuizen
We 2:30 PM – 5:20 PM
SRYC 5100, Surrey
D700 Leanne Barlow
Th 8:30 AM – 11:20 AM
WMC 2507, Burnaby
E100 Kevin Stewart
We 6:30 PM – 9:20 PM
WMC 3533, Burnaby
E200 Kevin Stewart
Tu 6:30 PM – 9:20 PM
WMC 2210, Burnaby

Computing Science

Students complete all of

CMPT 300 - Operating Systems I (3)

This course aims to give the student an understanding of what a modern operating system is, and the services it provides. It also discusses some basic issues in operating systems and provides solutions. Topics include multiprogramming, process management, memory management, and file systems. Prerequisite: CMPT 225 and (CMPT 295 or ENSC 254), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Hazra Imran
Mo 8:30 AM – 9:20 AM
Th 8:30 AM – 10:20 AM
AQ 3182, Burnaby
SSCK 9500, Burnaby
D200 Harinder Khangura
We 9:30 AM – 10:20 AM
Fr 8:30 AM – 10:20 AM
SRYE 3016, Surrey
SRYE 3016, Surrey
CMPT 307 - Data Structures and Algorithms (3)

Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms (greedy, divide & conquer, dynamic programming, network flows). Introduction to NP-completeness. Prerequisite: CMPT 225, (MACM 201 or CMPT 210), (MATH 150 or MATH 151), and (MATH 232 or MATH 240), all with a minimum grade of C-. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 150 or MATH 151.

Section Instructor Day/Time Location
D100 David Mitchell
Mo, We, Fr 9:30 AM – 10:20 AM
EDB 7618, Burnaby
CMPT 353 - Computational Data Science (3)

Basic concepts and programming tools for handling and processing data. Includes data acquisition, cleaning data sources, application of machine learning techniques and data analysis techniques, large-scale computation on a computing cluster. Prerequisite: CMPT 225 and (STAT 101, STAT 270, ENSC 280, or MSE 210), with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Gregory Baker
Tu 8:30 AM – 10:20 AM
Fr 8:30 AM – 9:20 AM
EDB 7618, Burnaby
AQ 3181, Burnaby
CMPT 354 - Database Systems I (3)

Logical representations of data records. Data models. Studies of some popular file and database systems. Document retrieval. Other related issues such as database administration, data dictionary and security. Prerequisite: CMPT 225 and (MACM 101 or (ENSC 251 and ENSC 252)), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Ke Wang
Mo 4:30 PM – 6:20 PM
We 5:30 PM – 6:20 PM
AQ 3182, Burnaby
AQ 3181, Burnaby
D200 John Edgar
Mo, We, Fr 1:30 PM – 2:20 PM
SRYE 1002, Surrey
CMPT 454 - Database Systems II (3)

An advanced course on database systems which covers crash recovery, concurrency control, transaction processing, distributed database systems as the core material and a set of selected topics based on the new developments and research interests, such as object-oriented data models and systems, extended relational systems, deductive database systems, and security and integrity. Prerequisite: CMPT 300 and 354, with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Tianzheng Wang
Mo 10:30 AM – 12:20 PM
We 10:30 AM – 11:20 AM
AQ 3159, Burnaby
BLU 9660, Burnaby

Mathematics and Computing Science

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 3181, Burnaby
D101 We 2:30 PM – 3:20 PM
WMC 2830, Burnaby
D102 We 3:30 PM – 4:20 PM
WMC 2830, Burnaby
D103 We 4:30 PM – 5:20 PM
WMC 2830, Burnaby
D104 Th 9:30 AM – 10:20 AM
WMC 2830, Burnaby
D105 Th 10:30 AM – 11:20 AM
WMC 2830, Burnaby
D106 Th 11:30 AM – 12:20 PM
WMC 2830, Burnaby

Mathematics

Students complete one 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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D400 Abraham Punnen
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SRYC 5280, Surrey
SRYC 5280, Surrey
D402 Th 3:30 PM – 4:20 PM
SRYC 2750, Surrey
D403 Th 4:30 PM – 5:20 PM
SRYC 2750, Surrey
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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Cedric Chauve
Tu 10:30 AM – 12:20 PM
Fr 10:30 AM – 11:20 AM
WMC 2202, Burnaby
WMC 2202, Burnaby
D101 Fr 2:30 PM – 3:20 PM
AQ 5008, Burnaby
D102 Fr 3:30 PM – 4:20 PM
AQ 5008, Burnaby

and one of

MACM 409 - Numerical Linear Algebra: Algorithms, Implementation and Applications (3)

Development of numerical methods for solving linear algebra problems at the heart of many scientific computing problems. Mathematical foundations for the use, implementation and analysis of the algorithms used for solving many optimization problems and differential equations. Prerequisite: MATH 251, MACM 316, programming experience. Quantitative.

MATH 320 - Introduction to Analysis II (3)

Sequences and series of functions, topology of sets in Euclidean space, introduction to metric spaces, functions of several variables. Prerequisite: MATH 242 and 251, with a minimum grade of C-. Quantitative.

MATH 340 - Algebra II: Rings and Fields (3)

The integers, fundamental theorem of arithmetic. Equivalence relations, modular arithmetic. Univariate polynomials, unique factorization. Rings and fields. Units, zero divisors, integral domains. Ideals, ring homomorphisms. Quotient rings, the ring isomorphism theorem. Chinese remainder theorem. Euclidean, principal ideal, and unique factorization domains. Field extensions, minimal polynomials. Classification of finite fields. Prerequisite: MATH 240 with a minimum grade of C- or MATH 232 with a grade of at least B. Students with credit for MATH 332 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Nils Bruin
Mo, We, Fr 11:30 AM – 12:20 PM
WMC 3260, Burnaby
D102 Tu 3:30 PM – 4:20 PM
WMC 2830, Burnaby
D103 Tu 4:30 PM – 5:20 PM
WMC 2830, Burnaby
D104 Tu 5:30 PM – 6:20 PM
WMC 2830, 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.

Section Instructor Day/Time Location
D100 Luis Goddyn
Mo, We, Fr 9:30 AM – 10:20 AM
AQ 5008, Burnaby
D101 Tu 12:30 PM – 1:20 PM
WMC 2830, Burnaby
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.

Section Instructor Day/Time Location
D100 Matthew DeVos
Mo 3:30 PM – 4:20 PM
We, Fr 3:30 PM – 4:20 PM
WMC 2503, Burnaby
WMC 3220, Burnaby
D101 Th 2:30 PM – 3:20 PM
BLU 10921, Burnaby
MATH 348 - Introduction to Probabilistic Models (3)

Review of the basics of probability, including sample space, random variables, expectation and conditioning. Applications of Markov chains, the exponential distribution and the Poisson process from science and industry. Applications may include inventory theory, queuing, forecasting, scheduling and simulation. Prerequisite: STAT 270 and (MATH 232 or MATH 240), all with a minimum grade of C-. Quantitative.

and

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 with a minimum grade of C-. Writing/Quantitative.

and one additional 400-level MATH course

Statistics

Students complete one of

ECON 333 - Statistical Analysis of Economic Data (4)

An introduction to the use and interpretation of statistical analysis in the context of data typical of economic applications. Prerequisite: ECON 103 with a minimum grade of C- or ECON 113 with a minimum grade of A-; ECON 105 with a minimum grade of C- or ECON 115 with a minimum grade of A-; ECON 233 or BUS (or BUEC) 232 or STAT 270, MATH 157, all with a minimum grade of C-; 60 units. Students with a minimum grade of A- in ECON 233, BUS (or BUEC) 232 or STAT 270 can take ECON 333 after 30 units. Students seeking permission to enroll based on their ECON 233, BUS (or BUEC) 232 or STAT 270 grade must contact the undergraduate advisor in economics. Students with credit for BUEC 333 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Dongwoo Kim
We 3:30 PM – 4:20 PM
Fr 2:30 PM – 4:20 PM
SSCC 9002, Burnaby
AQ 3182, Burnaby
D101 We 4:30 PM – 5:20 PM
AQ 5051, Burnaby
D102 We 4:30 PM – 5:20 PM
AQ 5050, Burnaby
D103 Th 2:30 PM – 3:20 PM
AQ 5048, Burnaby
D104 Fr 11:30 AM – 12:20 PM
AQ 5051, Burnaby
D105 Fr 12:30 PM – 1:20 PM
AQ 5036, Burnaby
D106 Fr 1:30 PM – 2:20 PM
AQ 5051, Burnaby
STAT 302 - Analysis of Experimental and Observational Data (3)

The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in observational and experimental studies. This course may not be used to satisfy the upper division requirements of the following programs: statistics major, statistics honours, actuarial science major, and actuarial science honours. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, with a minimum grade of C-. Students who have taken STAT 350 first may not then take the course for further credit. Quantitative.

Section Day/Time Location
OL01 Distance Education
STAT 305 - Introduction to Biostatistical Methods for Health Sciences (3)

Intermediate statistical techniques for the health sciences. Review of introductory concepts in statistics and probability including hypothesis testing, estimation and confidence intervals for means and proportions. Contingency tables and the analysis of multiple 2x2 tables. Correlation and regression. Multiple regression and model selection. Logistic regression and odds ratios. Basic concepts in survival analysis. This course may not be used to satisfy the upper division requirements of the following programs: statistics major, statistics honours, actuarial science major, and actuarial science honours. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, with a minimum grade of C-. Students who have taken STAT 350 first may not then take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Sonja Isberg
Mo 12:30 PM – 1:20 PM
Th 12:30 PM – 2:20 PM
SSCC 9001, Burnaby
SSCC 9001, Burnaby
OP01 TBD
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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Rachel Altman
Tu 12:30 PM – 2:20 PM
Fr 12:30 PM – 1:20 PM
SSCC 9000, Burnaby
SSCC 9000, Burnaby
D101 Rachel Altman
Tu 9:30 AM – 10:20 AM
AQ 5039, Burnaby
D102 Rachel Altman
Fr 9:30 AM – 10:20 AM
WMC 2522, Burnaby
D103 Rachel Altman
Fr 10:30 AM – 11:20 AM
WMC 2532, Burnaby

and both of

STAT 403 - Intermediate Sampling and Experimental Design (3)

A practical introduction to useful sampling techniques and intermediate level experimental designs. This course may not be used to satisfy the upper division requirements of the Statistics major or honours program. Prerequisite: STAT 302, 305 or 350 or ECON 333, all with a minimum grade of C-. Students with credit for STAT 410 or 430 may not take STAT 403 for further credit. Quantitative.

STAT 452 - Statistical Learning and Prediction (3)

An introduction to the essential modern supervised and unsupervised statistical learning methods. Topics include review of linear regression, classification, statistical error measurement, flexible regression and classification methods, clustering and dimension reduction. Prerequisite: STAT 302 or STAT 305 or STAT 350 or ECON 333 or equivalent, with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Haolun Shi
We 9:30 AM – 10:20 AM
Fr 8:30 AM – 10:20 AM
AQ 3182, Burnaby
AQ 3182, Burnaby
D101 Haolun Shi
We 11:30 AM – 12:20 PM
AQ 5037, Burnaby
D102 Haolun Shi
We 12:30 PM – 1:20 PM
AQ 5030, Burnaby
D103 Haolun Shi
We 1:30 PM – 2:20 PM
WMC 2503, Burnaby
D104 Haolun Shi
We 2:30 PM – 3:20 PM
WMC 2532, Burnaby
D105 Haolun Shi
We 3:30 PM – 4:20 PM
AQ 5016, Burnaby
D106 Haolun Shi
Mo 9:30 AM – 10:20 AM
AQ 5027, Burnaby

and one of

STAT 445 - Applied Multivariate Analysis (3)

Introduction to principal components, cluster analysis, and other commonly used multivariate techniques. Prerequisite: STAT 285 or STAT 302 or STAT 305 or ECON 333 or equivalent, with a minimum grade of C-. 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 ECON 333 or equivalent, with a minimum grade of C-. Students with credit for the former STAT 402 or 602 may not take this course for further credit. Quantitative.

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 ECON 333 or equivalent, with a minimum grade of C-. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.

Section Instructor Day/Time Location
E100 Gary Parker
Mo 5:30 PM – 6:20 PM
Th 4:30 PM – 6:20 PM
AQ 3181, Burnaby
AQ 3181, Burnaby
E101 Gary Parker
Mo 3:30 PM – 4:20 PM
AQ 5016, Burnaby
E102 Gary Parker
Mo 4:30 PM – 5:20 PM
AQ 5016, Burnaby
E103 Gary Parker
Mo 6:30 PM – 7:20 PM
AQ 5016, Burnaby

Open Concentration Requirements

Lower Division Requirements

Students complete a minimum of 55 units.

Business Administration

Students complete all of

BUS 200 - Business Fundamentals (3)

Explore the fundamentals of modern business and organizational management. Working with case studies, students will build upon the basics of revenue, profits, contribution and costs, as well as integrate advanced aspects of business models, innovation, competitive advantage, core competence, and strategic analysis. Breadth-Social Sciences.

Section Instructor Day/Time Location
D100 Sasha Ramnarine
Th 2:30 PM – 5:20 PM
AQ 3005, Burnaby
E100 Shannon Wong
We 5:30 PM – 8:20 PM
AQ 3005, Burnaby
BUS 217W - Critical Thinking in Business (3)

Examine and review today's global economy through critical analysis of differing perspectives. Develop and improve critical thinking and communication skills appropriate to the business environment. Prerequisite: BUS 201 with a minimum grade of C- and 15 units; OR 45 units and corequisite: BUS 202; OR business administration joint major, joint honours, or double degree students with 45 units; OR data science major with 15 units. Writing.

Section Instructor Day/Time Location
D100 Luana Carcano
We 2:30 PM – 5:20 PM
AQ 3154, Burnaby
D200 Matthew Martell
Tu 2:30 PM – 5:20 PM
SRYC 5240, Surrey
D300 Susan Christie-Bell
We 2:30 PM – 5:20 PM
RCB 8100, Burnaby
D400 Matthew Martell
Th 9:30 AM – 12:20 PM
WMC 2230, Burnaby
E100 Jerome Francis
We 5:30 PM – 8:20 PM
WMC 2230, Burnaby
E200 Michelle Corbett
Tu 5:30 PM – 8:20 PM
RCB 8100, Burnaby
BUS 251 - Financial Accounting I (3)

An introduction to financial accounting, including accounting terminology, understanding financial statements, analysis of a business entity using financial statements. Includes also time value of money and a critical review of the conventional accounting system. Prerequisite: 12 units. Quantitative.

Section Instructor Day/Time Location
D100 Susan Bubra
Th 12:30 PM – 2:20 PM
RCB IMAGTH, Burnaby
D101 Th 2:30 PM – 3:20 PM
BLU 10655, Burnaby
D102 Th 6:30 PM – 7:20 PM
WMC 2523, Burnaby
D103 Th 3:30 PM – 4:20 PM
BLU 10655, Burnaby
D104 Th 6:30 PM – 7:20 PM
WMC 3511, Burnaby
D105 Th 4:30 PM – 5:20 PM
WMC 3253, Burnaby
D106 Th 4:30 PM – 5:20 PM
WMC 3255, Burnaby
D107 Th 5:30 PM – 6:20 PM
WMC 3513, Burnaby
D108 Th 5:30 PM – 6:20 PM
WMC 3515, Burnaby
D200 Praise Ma
Fr 10:30 AM – 12:20 PM
SRYC 5240, Surrey
D201 Fr 12:30 PM – 1:20 PM
SRYC 5060, Surrey
D202 Fr 12:30 PM – 1:20 PM
SRYC 5320, Surrey
D203 Fr 1:30 PM – 2:20 PM
SRYC 5060, Surrey
D204 Fr 1:30 PM – 2:20 PM
SRYC 5320, Surrey
E100 Susan Bubra
Th 5:30 PM – 7:20 PM
RCB IMAGTH, Burnaby
E101 Th 7:30 PM – 8:20 PM
WMC 3253, Burnaby
E102 Th 7:30 PM – 8:20 PM
WMC 3250, Burnaby
E103 Th 7:30 PM – 8:20 PM
WMC 2507, Burnaby
E104 Th 8:30 PM – 9:20 PM
WMC 3513, Burnaby
BUS 272 - Behaviour in Organizations (3)

Theories, concepts and issues in the field of organizational behaviour with an emphasis on individual and team processes. Core topics include employee motivation and performance, stress management, communication, work perceptions and attitudes, decision-making, team dynamics, employee involvement and conflict management. Prerequisite: 12 units.

Section Instructor Day/Time Location
D100 Sam Thiara
Tu 10:30 AM – 12:20 PM
SSCC 9002, Burnaby
D101 Tu 12:30 PM – 1:20 PM
AQ 2122, Burnaby
D102 Tu 12:30 PM – 1:20 PM
WMC 3513, Burnaby
D103 Tu 1:30 PM – 2:20 PM
WMC 3515, Burnaby
D104 Tu 1:30 PM – 2:20 PM
AQ 5006, Burnaby
D105 Tu 2:30 PM – 3:20 PM
AQ 2122, Burnaby
D106 Tu 2:30 PM – 3:20 PM
WMC 2260, Burnaby
D107 Tu 3:30 PM – 4:20 PM
WMC 3513, Burnaby
D200 Sam Thiara
Th 10:30 AM – 12:20 PM
SRYC 3170, Surrey
D201 Th 12:30 PM – 1:20 PM
SRYC 5060, Surrey
D202 Th 12:30 PM – 1:20 PM
SRYC 5320, Surrey
D203 Th 1:30 PM – 2:20 PM
SRYC 5060, Surrey
D204 Th 1:30 PM – 2:20 PM
SRYC 5320, Surrey
D300 William Scott
Tu 12:30 PM – 2:20 PM
EDB 7618, Burnaby
D301 Tu 2:30 PM – 3:20 PM
WMC 3513, Burnaby
D302 Tu 2:30 PM – 3:20 PM
WMC 3517, Burnaby
D303 Tu 3:30 PM – 4:20 PM
WMC 3517, Burnaby
D304 Tu 3:30 PM – 4:20 PM
BLU 10901, Burnaby
D305 Tu 4:30 PM – 5:20 PM
WMC 2533, Burnaby
E100 Chris Zatzick
We 4:30 PM – 6:20 PM
SSCC 9002, Burnaby
E101 We 6:30 PM – 7:20 PM
AQ 5009, Burnaby
E102 We 6:30 PM – 7:20 PM
AQ 5014, Burnaby
E103 We 6:30 PM – 7:20 PM
AQ 5004, Burnaby
E104 We 7:30 PM – 8:20 PM
AQ 5004, Burnaby

Computing Science

Students complete all 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, e.g. Python. The students will be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode; data types and control structures; fundamental algorithms; recursion; reading and writing files; measuring performance of algorithms; debugging tools; basic terminal navigation using shell commands. 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, We, Fr 9:30 AM – 10:20 AM
AQ 3181, Burnaby
D300 Diana Cukierman
Mo, We, Fr 1:30 PM – 2:20 PM
SSCB 9200, Burnaby
D400 Toby Donaldson
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SRYE 1002, Surrey
SRYE 1002, Surrey
OL01 Mo, We, Fr 4:30 PM – 5:20 PM
Distance Education
CMPT 125 - Introduction to Computing Science and Programming II (3)

A rigorous introduction to computing science and computer programming, suitable for students who already have some background in computing science and programming. Intended for students who will major in computing science or a related program. Topics include: memory management; fundamental algorithms; formally analyzing the running time of algorithms; abstract data types and elementary data structures; object-oriented programming and software design; specification and program correctness; reading and writing files; debugging tools; shell commands. Prerequisite: CMPT 120 or CMPT 130, with a minimum grade of C-. Students with credit for CMPT 126, 129, 135 or CMPT 200 or higher may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Igor Shinkar
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
AQ 3182, Burnaby
AQ 3181, Burnaby
D101 Igor Shinkar
Th 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D102 Igor Shinkar
Th 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D103 Igor Shinkar
Th 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D104 Igor Shinkar
Th 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D105 Igor Shinkar
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D106 Igor Shinkar
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D107 Igor Shinkar
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
D108 Igor Shinkar
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
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, CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252), all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 David Mitchell
Mo, We, Fr 1:30 PM – 2:20 PM
WMC 3520, Burnaby
D101 David Mitchell
Tu 8:30 AM – 9:20 AM
ASB 9838, Burnaby
D102 David Mitchell
Tu 8:30 AM – 9:20 AM
ASB 9838, Burnaby
D103 David Mitchell
Tu 9:30 AM – 10:20 AM
ASB 9838, Burnaby
D104 David Mitchell
Tu 9:30 AM – 10:20 AM
ASB 9838, Burnaby
D105 David Mitchell
Tu 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D106 David Mitchell
Tu 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D107 David Mitchell
Tu 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D108 David Mitchell
Tu 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D200 Anne Lavergne
Tu 2:30 PM – 4:20 PM
Fr 2:30 PM – 3:20 PM
SRYE 2016, Surrey
SRYE 2016, Surrey
D201 Anne Lavergne
Mo 2:30 PM – 3:20 PM
SRYE 4024, Surrey
D202 Anne Lavergne
Mo 2:30 PM – 3:20 PM
SRYE 4013, Surrey
D203 Anne Lavergne
Mo 4:30 PM – 5:20 PM
SRYE 4024, Surrey
D204 Anne Lavergne
Mo 4:30 PM – 5:20 PM
SRYE 4013, Surrey
D205 Anne Lavergne
Mo 5:30 PM – 6:20 PM
SRYE 4024, Surrey
CMPT 276 - Introduction to Software Engineering (3)

An overview of various techniques used for software development and software project management. Major tasks and phases in modern software development, including requirements, analysis, documentation, design, implementation, testing,and maintenance. Project management issues are also introduced. Students complete a team project using an iterative development process. Prerequisite: One W course, CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and (MATH 151 or MATH 150), all with a minimum grade of C-. MATH 154 or MATH 157 with at least a B+ may be substituted for MATH 151 or MATH 150. Students with credit for CMPT 275 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Saba Alimadadi Jani
Mo, We, Fr 10:30 AM – 11:20 AM
AQ 3149, Burnaby
D200 Rob Cameron
Mo 5:30 PM – 8:20 PM
AQ 3149, Burnaby
D300 Brian Fraser
Mo, We, Fr 1:30 PM – 2:20 PM
SRYE 3016, Surrey
CMPT 295 - Introduction to Computer Systems (3)

The curriculum introduces students to topics in computer architecture that are considered fundamental to an understanding of the digital systems underpinnings of computer systems. Prerequisite: Either (MACM 101 and (CMPT 125 or CMPT 135)) or (MATH 151 and CMPT 102 for students in an Applied Physics program), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Alaa Alameldeen
Arrvindh Shriraman
Mo 4:30 PM – 5:20 PM
Th 4:30 PM – 6:20 PM
SWH 10081, Burnaby
SWH 10081, Burnaby
D101 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D102 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D103 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D104 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D105 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D106 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D107 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D108 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D109 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D110 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby
D111 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby
D112 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby

Mathematics and Computing Science

Students complete both of

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 Andrei Bulatov
Mo 11:30 AM – 12:20 PM
We, Fr 11:30 AM – 12:20 PM
SWH 10081, Burnaby
SSCB 9201, Burnaby
D101 Andrei Bulatov
Fr 12:30 PM – 1:20 PM
AQ 5030, Burnaby
D102 Andrei Bulatov
Fr 12:30 PM – 1:20 PM
BLU 10901, Burnaby
D103 Andrei Bulatov
Fr 1:30 PM – 2:20 PM
BLU 10901, Burnaby
D104 Andrei Bulatov
Fr 1:30 PM – 2:20 PM
WMC 2531, Burnaby
D105 Andrei Bulatov
Fr 2:30 PM – 3:20 PM
AQ 5006, Burnaby
D106 Andrei Bulatov
Fr 2:30 PM – 3:20 PM
WMC 3517, Burnaby
D107 Andrei Bulatov
Fr 3:30 PM – 4:20 PM
WMC 2531, Burnaby
D108 Andrei Bulatov
Fr 3:30 PM – 4:20 PM
AQ 5009, Burnaby
D109 Andrei Bulatov
Fr 10:30 AM – 11:20 AM
AQ 5035, Burnaby
D200 Thomas Shermer
We 3:30 PM – 4:20 PM
Fr 2:30 PM – 4:20 PM
SRYE 1002, Surrey
SRYE 1002, Surrey
D201 Thomas Shermer
Tu 2:30 PM – 3:20 PM
SRYC 3240, Surrey
D202 Thomas Shermer
Tu 2:30 PM – 3:20 PM
SRYC 3250, Surrey
D203 Thomas Shermer
Tu 3:30 PM – 4:20 PM
SRYC 3240, Surrey
D204 Thomas Shermer
Tu 3:30 PM – 4:20 PM
SRYC 3250, Surrey
D205 Thomas Shermer
Tu 4:30 PM – 5:20 PM
SRYC 3240, Surrey
D206 Thomas Shermer
Tu 4:30 PM – 5:20 PM
SRYC 5060, Surrey
D207 Thomas Shermer
Tu 5:30 PM – 6:20 PM
SRYC 5060, Surrey
D208 Thomas Shermer
Tu 5:30 PM – 6:20 PM
SRYC 3040, 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 Matthew DeVos
Mo, We, Fr 12:30 PM – 1:20 PM
SSCC 9002, Burnaby
D200 Mahsa Faizrahnemoon
Mo, We, Fr 12:30 PM – 1:20 PM
SWH 10081, Burnaby
OP02 TBD

Data Science

Students complete

DATA 180 - Undergraduate Seminar in Data Science (1)

A seminar primarily for students undertaking a major or an honours program in Data Science. Prerequisite: Major or honours in Data Science or permission of the program director. Students with credit for DATA (or MSSC) 480 cannot receive credit for DATA (or MSSC) 180.

Section Instructor Day/Time Location
E100 Jiguo Cao
Tu 6:30 PM – 8:20 PM
SWH 10041, Burnaby

Mathematics

Students complete 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
D100 Sophie Burrill
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9201, Burnaby
D101 Tu 8:30 AM – 9:20 AM
WMC 2503, Burnaby
D102 Tu 9:30 AM – 10:20 AM
WMC 2532, Burnaby
D103 Tu 10:30 AM – 11:20 AM
WMC 2503, Burnaby
D104 We 2:30 PM – 3:20 PM
WMC 2810, Burnaby
D105 We 3:30 PM – 4:20 PM
WMC 2810, Burnaby
D200 Jamie Mulholland
Mo, We, Fr 8:30 AM – 9:20 AM
RCB IMAGTH, Burnaby
D201 Tu 8:30 AM – 9:20 AM
AQ 5039, Burnaby
D202 Tu 1:30 PM – 2:20 PM
BLU 10921, Burnaby
D203 Tu 2:30 PM – 3:20 PM
AQ 5037, Burnaby
D204 Fr 2:30 PM – 3:20 PM
RCB 5120, Burnaby
D205 Fr 3:30 PM – 4:20 PM
RCB 5120, Burnaby
D400 Natalia Kouzniak
Mo, We, Fr 9:30 AM – 10:20 AM
SRYE 1002, Surrey
D401 Natalia Kouzniak
Th 12:30 PM – 1:20 PM
SRYC 2740, Surrey
D402 Natalia Kouzniak
Th 2:30 PM – 3:20 PM
SRYC 2740, Surrey
D403 Natalia Kouzniak
Th 1:30 PM – 2:20 PM
SRYC 2740, Surrey
OP01 TBD
OP02 TBD
OP03 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.

Section Instructor Day/Time Location
D100 Sophie Burrill
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9201, Burnaby
D200 Jamie Mulholland
Mo, We, Fr 8:30 AM – 9:20 AM
RCB IMAGTH, Burnaby
D400 Natalia Kouzniak
Mo, We, Fr 9:30 AM – 10:20 AM
SRYE 1002, Surrey
OP01 TBD
OP02 TBD
OP04 TBD
MATH 154 - Mathematics for the Life Sciences I (3)

Designed for students specializing in the life sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications, integration, and differential equations; mathematical models of biological processes and their implementation and analysis using software. 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 Ailene MacPherson
Mo, We, Fr 8:30 AM – 9:20 AM
SSCC 9001, Burnaby
D400 Ladislav Stacho
Mo, We, Fr 9:30 AM – 10:20 AM
SRYC 5280, Surrey
OP01 TBD
OP02 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; introduction to functions of several variables with emphasis on partial derivatives and extrema. 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 Imin Chen
Mo, We, Fr 11:30 AM – 12:20 PM
SSCC 9001, Burnaby
D400 Roghayeh Ebrahim Nataj
Mo, We, Fr 12:30 PM – 1:20 PM
SRYC 5280, Surrey
OP01 TBD
OP02 TBD

and both 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, with a minimum grade of C-; 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 Michael Monagan
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9200, Burnaby
OP01 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, with a minimum grade of C-. Students with credit for MATH 208 may not take this course for further credit. Writing/Quantitative.

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, with a minimum grade of C-; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 11:30 AM – 12:20 PM
SSCB 9200, Burnaby
D400 Randall Pyke
Mo, We, Fr 1:30 PM – 2:20 PM
SRYC 2600, Surrey
OP01 TBD
OP02 Mo, We, Fr 1:30 PM – 2:20 PM
,
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, with a minimum grade of C-; 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 Jake Levinson
Mo, We, Fr 11:30 AM – 12:20 PM
SWH 10041, Burnaby
OP01 TBD

Statistics

Students complete all of

STAT 240 - Introduction to Data Science (3)

Introduction to modern tools and methods for data acquisition, management, and visualization capable of scaling to Big Data. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, and one of CMPT 102, CMPT 120, CMPT 125, CMPT 128, CMPT 129, CMPT 130, all with a minimum grade of C- or permission of the instructor. STAT 260 is also recommended. Quantitative.

STAT 260 - Introductory R for Data Science (2)

An introduction to the R programming language for data science. Exploring data: visualization, transformation and summaries. Data wrangling: reading, tidying, and data types. No prior computer programming experience required. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, ECON 233, or POL 201, with a grade of at least C- or permission of the instructor. Corequisite: STAT 261. Students who have taken STAT 341 or STAT 360 first may not then take this course for further credit.

Section Instructor Day/Time Location
D100 David Stenning
Tu 2:30 PM – 4:20 PM
SSCB 9200, Burnaby
STAT 261 - Laboratory for Introductory R for Data Science (1)

A hands-on application of the R programming language for data science. Using the R concepts covered in STAT 260, students will explore (visualize, transform, and summarize) and wrangle (read and tidy) data. No prior computer programming experience required. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, ECON 233, or POL 201, with a grade of at least C- or permission of the instructor. Corequisite: STAT 260. Students who have taken STAT 341 or STAT 360 first may not then take this course for further credit.

Section Instructor Day/Time Location
D010 David Stenning
Th 6:30 PM – 7:20 PM
AQ 3148.2, Burnaby
D100 David Stenning
Tu 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
D200 David Stenning
Tu 5:30 PM – 6:20 PM
AQ 3148.2, Burnaby
D300 David Stenning
Tu 6:30 PM – 7:20 PM
AQ 3148.2, Burnaby
D400 David Stenning
We 3:30 PM – 4:20 PM
AQ 3148.2, Burnaby
D500 David Stenning
We 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
D600 David Stenning
We 5:30 PM – 6:20 PM
AQ 3148.2, Burnaby
D700 David Stenning
Th 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby

and one of

BUS 232 - Business Statistics (3)

An introduction to business statistics (descriptive and inferential statistics) with a heavy emphasis on applications and the use of EXCEL. Students will be required to use statistical applications to solve business problems. Corequisite: MATH 150, MATH 151, MATH 154, or MATH 157, with a minimum grade of C-; 15 units. Students with credit for BUEC 232 or ECON 233 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Negar Ganjouhaghighi
We 2:30 PM – 5:20 PM
SSCB 9201, Burnaby
D200 Negar Ganjouhaghighi
Th 2:30 PM – 5:20 PM
SRYC 3090, Surrey
E100 Mohammad Ghotboddini
Mo 6:00 PM – 8:50 PM
WMC 3520, Burnaby
OP01 Mo 12:30 PM – 4:20 PM
WMC 2303, Burnaby
OP02 Tu 9:30 AM – 1:20 PM
WMC 2303, Burnaby
OP03 We 12:30 PM – 2:20 PM
WMC 2303, Burnaby
OP04 Th 12:30 PM – 2:20 PM
SRYC 3050, Surrey
OP05 Fr 2:30 PM – 4:20 PM
SRYC 3050, Surrey
OP06 Mo 4:30 PM – 5:50 PM
WMC 2303, Burnaby
OP07 Tu 4:30 PM – 6:20 PM
WMC 2303, Burnaby
OP08 We 4:30 PM – 6:20 PM
WMC 2303, Burnaby
OP09 Th 12:30 PM – 2:20 PM
WMC 2303, Burnaby
OP10 Fr 12:30 PM – 2:50 PM
WMC 2303, Burnaby
STAT 201 - Statistics for the Life Sciences (3)

Research methodology and associated statistical analysis techniques for students with training in the life sciences. Intended to be particularly accessible to students who are not specializing in Statistics. Prerequisite: Recommended: 30 units. Students cannot obtain credit for STAT 201 if they already have credit for - or are taking concurrently - STAT 101, 203, 205, 285, or any upper division STAT course. Quantitative.

Section Instructor Day/Time Location
D100 Wei Lin
Tu 12:30 PM – 2:20 PM
Fr 12:30 PM – 1:20 PM
SSCC 9001, Burnaby
SSCC 9001, Burnaby
OL01 Distance Education
OP01 TBD
STAT 203 - Introduction to Statistics for the Social Sciences (3)

Descriptive and inferential statistics aimed at students in the social sciences. Scales of measurement. Descriptive statistics. Measures of association. Hypothesis tests and confidence intervals. Students in Sociology and Anthropology are expected to take SA 255 before this course. Intended to be particularly accessible to students who are not specializing in Statistics. Prerequisite: Recommended: 30 units including a research methods course such as SA 255, CRIM 220, POL 200W, or equivalent. Students cannot obtain credit for STAT 203 if they already have credit for - or are taking concurrently - STAT 101, 201, 205, 285, or any upper division STAT course. Quantitative.

Section Instructor Day/Time Location
D900 Scott Pai
Mo 12:30 PM – 1:20 PM
Th 12:30 PM – 2:20 PM
SRYE 1002, Surrey
SRYE 1002, Surrey
OL01 Distance Education
OP09 TBD
STAT 205 - Introduction to Statistics (3)

The collection, description, analysis and summary of data, including the concepts of frequency distribution, parameter estimation and hypothesis testing. Intended to be particularly accessible to students who are not specializing in Statistics. Prerequisite: Recommended: 30 units. Students cannot obtain credit for STAT 205 if they already have credit for - or are taking concurrently - STAT 101, 201, 203, 285, or any upper division STAT course. Quantitative.

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, with a minimum grade of C-. 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
D100 Sonja Isberg
Mo, We, Fr 9:30 AM – 10:20 AM
SSCB 9201, Burnaby
OL01 Distance Education
OP01 TBD

* Recommended

Upper Division Requirements

Students complete a minimum of 52 units.

Business Administration

Students complete all of

BUS 343 - Introduction to Marketing (3)

The environment of marketing; relation of social sciences to marketing; evaluation of marketing theory and research; assessment of demand, consumer behaviour analysis; market institutions; method and mechanics of distribution in domestic, foreign and overseas markets; sales organization; advertising; new product development, publicity and promotion; marketing programs. Prerequisite: 45 units. Students with credit for COMM 343 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Pei-Shiuan Lin
Tu 8:30 AM – 10:20 AM
AQ 3181, Burnaby
D101 Tu 10:30 AM – 11:20 AM
RCB 7100, Burnaby
D102 Tu 10:30 AM – 11:20 AM
RCB 8105, Burnaby
D103 Tu 10:30 AM – 11:20 AM
RCB 8104, Burnaby
D104 Tu 11:30 AM – 12:20 PM
RCB 8104, Burnaby
D105 Tu 11:30 AM – 12:20 PM
RCB 6100, Burnaby
D106 Tu 11:30 AM – 12:20 PM
RCB 6122, Burnaby
D107 Tu 12:30 PM – 1:20 PM
RCB 6100, Burnaby
D108 Tu 12:30 PM – 1:20 PM
RCB 6122, Burnaby
D109 Tu 12:30 PM – 1:20 PM
RCB 7105, Burnaby
D110 Tu 1:30 PM – 2:20 PM
RCB 7105, Burnaby
D111 Tu 1:30 PM – 2:20 PM
RCB 6100, Burnaby
D200 Pei-Shiuan Lin
Th 8:30 AM – 10:20 AM
SRYC 3090, Surrey
D201 Th 10:30 AM – 11:20 AM
SRYC 3260, Surrey
D202 Th 10:30 AM – 11:20 AM
SRYC 3010, Surrey
D203 Th 11:30 AM – 12:20 PM
SRYC 3260, Surrey
D204 Th 11:30 AM – 12:20 PM
SRYC 3010, Surrey
D205 Th 12:30 PM – 1:20 PM
SRYC 3010, Surrey
BUS 360W - Business Communication (4)

Helps students develop professional writing- and speaking-based communication strategies they can confidently adapt to a wide range of business situations. The course aims to raise their communication performance to a professionally acceptable level, rather than to memorize or theorize about communication knowledge: this is a “learn-by-doing” course. Students will improve their ability to conceptualize, analyze/evaluate, synthesize, and apply information to guide their thinking and finished products across various business contexts. As teamwork is a fundamental skill valued by employers, students will participate in a major team project to learn about and apply best practices for collaboration with respect to professional business communication. The primary means of instruction and learning is guided practice in both writing and presenting in response to realistic business contexts. Instruction and assessment focus on both the process of creating professional, finished products, as well as the quality of those products. Prerequisite: This course is open to students admitted prior to Fall 2014 to the business administration major, honours, or second degree program and who have 45 units, OR to students admitted Fall 2014 - Summer 2017 to the business administration major, honours, or second degree program and who have 45 units and BUS 130 or (BUS 201 or BUS 202) or BUS 301, with a minimum grade of C-, OR to students admitted Fall 2017 – Summer 2022 to the business administration major, honours, or second degree program and who have 45 units and BUS 130 or (BUS 201 or BUS 202) or BUS 301, and BUS 217W, both with a minimum grade of C-, OR to students admitted Fall 2022 onwards to the business administration major, honours, or second degree program, and who have 45 units; BUS 217W and (BUS 201 or BUS 202), both with a minimum grade of C-; and Corequisite: BUS 300, OR to business administration joint major or joint honours students with BUS 217W with a minimum grade of C- and 45 units, OR to business and economics joint major students with ECON 220W with a minimum grade of C- and 45 units, OR to mechatronic systems engineering and business administration double degree students with 45 units, OR to management systems science or actuarial science majors with 45 units OR to data science major with BUS 217W with a minimum grade of C- and 45 units. Students who have taken BUS 360 may not take this course for further credit. Writing.

Section Instructor Day/Time Location
D100 Leanne Barlow
Tu 2:30 PM – 5:20 PM
WMC 2507, Burnaby
D200 Darren Francis
We 9:30 AM – 12:20 PM
RCB 7100, Burnaby
D300 Kevin Stewart
Th 11:30 AM – 2:20 PM
WMC 3533, Burnaby
D400 Leanne Barlow
Tu 11:30 AM – 2:20 PM
WMC 2210, Burnaby
D500 Christian Venhuizen
Th 2:30 PM – 5:20 PM
SRYC 5100, Surrey
D600 Christian Venhuizen
We 2:30 PM – 5:20 PM
SRYC 5100, Surrey
D700 Leanne Barlow
Th 8:30 AM – 11:20 AM
WMC 2507, Burnaby
E100 Kevin Stewart
We 6:30 PM – 9:20 PM
WMC 3533, Burnaby
E200 Kevin Stewart
Tu 6:30 PM – 9:20 PM
WMC 2210, Burnaby
BUS 439 - Analytics Project (3) *

Examines complex, real-world decision making issues using an evidence-based approach that employs decision making strategies involving statistics, data management, analytics, and decision theory. Through a major decision making project within the community, students will experience first-hand the process of consultation, data acquisition, analysis, and recommendation. The data in the project will be proprietary to the community partners and students thus need to sign a non-disclosure agreement. A non-disclosure agreement template is attached to the course outline. The results of the project will remain the intellectual property of the students; notwithstanding, those results will be shared with the data provider. Students also have an option to complete a project with non-proprietary data. Prerequisite: BUS 345 or BUS 440, BUS 360W, BUS 437 or BUS 441, BUS 445, BUS 462, and BUS 464, all with a minimum grade of C-; 90 units; OR Data Science majors with BUS 360W, BUS 445, CMPT 354, all with a minimum grade of C- and 90 units.

Section Instructor Day/Time Location
D100 Jason Ho
Tu 11:30 AM – 2:20 PM
WMC 2305, Burnaby
BUS 445 - Customer Analytics (3) **

Exposes students to the art of using analytic tools from across the spectrum of data mining and modeling to provide powerful competitive advantage in business. Students will learn to recognize when a method should or should not be used, what data is required, and how to use the software tools. Areas covered include database marketing, geospatial marketing and fundamental strategic and tactical decisions such as segmentation, targeting and allocating resources to the marketing mix. Prerequisite: BUS 343, 336, 360W, all with a minimum grade of C-, 60 units; OR Data Science majors with BUS 343, 360W, both with a minimum grade of C-, and 60 units.

Section Instructor Day/Time Location
D100 Miremad Soleymanian
Th 11:30 AM – 2:20 PM
WMC 2305, Burnaby
D200 Miremad Soleymanian
Fr 2:30 PM – 5:20 PM
WMC 2305, Burnaby

*For this course, Data Science students are eligible for a prerequisite waiver for BUS 345, 437, 445, 462, 464, 90 units. Students should consult with their program advisor.

**For this course, Data Science students are eligible for a prerequisite waiver for BUS 336. Students should consult with their program advisor.

Computing Science

Students complete all of

CMPT 300 - Operating Systems I (3)

This course aims to give the student an understanding of what a modern operating system is, and the services it provides. It also discusses some basic issues in operating systems and provides solutions. Topics include multiprogramming, process management, memory management, and file systems. Prerequisite: CMPT 225 and (CMPT 295 or ENSC 254), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Hazra Imran
Mo 8:30 AM – 9:20 AM
Th 8:30 AM – 10:20 AM
AQ 3182, Burnaby
SSCK 9500, Burnaby
D200 Harinder Khangura
We 9:30 AM – 10:20 AM
Fr 8:30 AM – 10:20 AM
SRYE 3016, Surrey
SRYE 3016, Surrey
CMPT 307 - Data Structures and Algorithms (3)

Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms (greedy, divide & conquer, dynamic programming, network flows). Introduction to NP-completeness. Prerequisite: CMPT 225, (MACM 201 or CMPT 210), (MATH 150 or MATH 151), and (MATH 232 or MATH 240), all with a minimum grade of C-. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 150 or MATH 151.

Section Instructor Day/Time Location
D100 David Mitchell
Mo, We, Fr 9:30 AM – 10:20 AM
EDB 7618, Burnaby
CMPT 353 - Computational Data Science (3)

Basic concepts and programming tools for handling and processing data. Includes data acquisition, cleaning data sources, application of machine learning techniques and data analysis techniques, large-scale computation on a computing cluster. Prerequisite: CMPT 225 and (STAT 101, STAT 270, ENSC 280, or MSE 210), with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Gregory Baker
Tu 8:30 AM – 10:20 AM
Fr 8:30 AM – 9:20 AM
EDB 7618, Burnaby
AQ 3181, Burnaby
CMPT 354 - Database Systems I (3)

Logical representations of data records. Data models. Studies of some popular file and database systems. Document retrieval. Other related issues such as database administration, data dictionary and security. Prerequisite: CMPT 225 and (MACM 101 or (ENSC 251 and ENSC 252)), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Ke Wang
Mo 4:30 PM – 6:20 PM
We 5:30 PM – 6:20 PM
AQ 3182, Burnaby
AQ 3181, Burnaby
D200 John Edgar
Mo, We, Fr 1:30 PM – 2:20 PM
SRYE 1002, Surrey
CMPT 454 - Database Systems II (3)

An advanced course on database systems which covers crash recovery, concurrency control, transaction processing, distributed database systems as the core material and a set of selected topics based on the new developments and research interests, such as object-oriented data models and systems, extended relational systems, deductive database systems, and security and integrity. Prerequisite: CMPT 300 and 354, with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Tianzheng Wang
Mo 10:30 AM – 12:20 PM
We 10:30 AM – 11:20 AM
AQ 3159, Burnaby
BLU 9660, Burnaby

Mathematics

Students complete one 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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D400 Abraham Punnen
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SRYC 5280, Surrey
SRYC 5280, Surrey
D402 Th 3:30 PM – 4:20 PM
SRYC 2750, Surrey
D403 Th 4:30 PM – 5:20 PM
SRYC 2750, Surrey
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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Cedric Chauve
Tu 10:30 AM – 12:20 PM
Fr 10:30 AM – 11:20 AM
WMC 2202, Burnaby
WMC 2202, Burnaby
D101 Fr 2:30 PM – 3:20 PM
AQ 5008, Burnaby
D102 Fr 3:30 PM – 4:20 PM
AQ 5008, Burnaby

Statistics

Students complete one of

ECON 333 - Statistical Analysis of Economic Data (4)

An introduction to the use and interpretation of statistical analysis in the context of data typical of economic applications. Prerequisite: ECON 103 with a minimum grade of C- or ECON 113 with a minimum grade of A-; ECON 105 with a minimum grade of C- or ECON 115 with a minimum grade of A-; ECON 233 or BUS (or BUEC) 232 or STAT 270, MATH 157, all with a minimum grade of C-; 60 units. Students with a minimum grade of A- in ECON 233, BUS (or BUEC) 232 or STAT 270 can take ECON 333 after 30 units. Students seeking permission to enroll based on their ECON 233, BUS (or BUEC) 232 or STAT 270 grade must contact the undergraduate advisor in economics. Students with credit for BUEC 333 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Dongwoo Kim
We 3:30 PM – 4:20 PM
Fr 2:30 PM – 4:20 PM
SSCC 9002, Burnaby
AQ 3182, Burnaby
D101 We 4:30 PM – 5:20 PM
AQ 5051, Burnaby
D102 We 4:30 PM – 5:20 PM
AQ 5050, Burnaby
D103 Th 2:30 PM – 3:20 PM
AQ 5048, Burnaby
D104 Fr 11:30 AM – 12:20 PM
AQ 5051, Burnaby
D105 Fr 12:30 PM – 1:20 PM
AQ 5036, Burnaby
D106 Fr 1:30 PM – 2:20 PM
AQ 5051, Burnaby
STAT 302 - Analysis of Experimental and Observational Data (3)

The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in observational and experimental studies. This course may not be used to satisfy the upper division requirements of the following programs: statistics major, statistics honours, actuarial science major, and actuarial science honours. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, with a minimum grade of C-. Students who have taken STAT 350 first may not then take the course for further credit. Quantitative.

Section Day/Time Location
OL01 Distance Education
STAT 305 - Introduction to Biostatistical Methods for Health Sciences (3)

Intermediate statistical techniques for the health sciences. Review of introductory concepts in statistics and probability including hypothesis testing, estimation and confidence intervals for means and proportions. Contingency tables and the analysis of multiple 2x2 tables. Correlation and regression. Multiple regression and model selection. Logistic regression and odds ratios. Basic concepts in survival analysis. This course may not be used to satisfy the upper division requirements of the following programs: statistics major, statistics honours, actuarial science major, and actuarial science honours. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, with a minimum grade of C-. Students who have taken STAT 350 first may not then take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Sonja Isberg
Mo 12:30 PM – 1:20 PM
Th 12:30 PM – 2:20 PM
SSCC 9001, Burnaby
SSCC 9001, Burnaby
OP01 TBD
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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Rachel Altman
Tu 12:30 PM – 2:20 PM
Fr 12:30 PM – 1:20 PM
SSCC 9000, Burnaby
SSCC 9000, Burnaby
D101 Rachel Altman
Tu 9:30 AM – 10:20 AM
AQ 5039, Burnaby
D102 Rachel Altman
Fr 9:30 AM – 10:20 AM
WMC 2522, Burnaby
D103 Rachel Altman
Fr 10:30 AM – 11:20 AM
WMC 2532, Burnaby

and both of

STAT 403 - Intermediate Sampling and Experimental Design (3)

A practical introduction to useful sampling techniques and intermediate level experimental designs. This course may not be used to satisfy the upper division requirements of the Statistics major or honours program. Prerequisite: STAT 302, 305 or 350 or ECON 333, all with a minimum grade of C-. Students with credit for STAT 410 or 430 may not take STAT 403 for further credit. Quantitative.

STAT 452 - Statistical Learning and Prediction (3)

An introduction to the essential modern supervised and unsupervised statistical learning methods. Topics include review of linear regression, classification, statistical error measurement, flexible regression and classification methods, clustering and dimension reduction. Prerequisite: STAT 302 or STAT 305 or STAT 350 or ECON 333 or equivalent, with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Haolun Shi
We 9:30 AM – 10:20 AM
Fr 8:30 AM – 10:20 AM
AQ 3182, Burnaby
AQ 3182, Burnaby
D101 Haolun Shi
We 11:30 AM – 12:20 PM
AQ 5037, Burnaby
D102 Haolun Shi
We 12:30 PM – 1:20 PM
AQ 5030, Burnaby
D103 Haolun Shi
We 1:30 PM – 2:20 PM
WMC 2503, Burnaby
D104 Haolun Shi
We 2:30 PM – 3:20 PM
WMC 2532, Burnaby
D105 Haolun Shi
We 3:30 PM – 4:20 PM
AQ 5016, Burnaby
D106 Haolun Shi
Mo 9:30 AM – 10:20 AM
AQ 5027, Burnaby

and one of

STAT 445 - Applied Multivariate Analysis (3)

Introduction to principal components, cluster analysis, and other commonly used multivariate techniques. Prerequisite: STAT 285 or STAT 302 or STAT 305 or ECON 333 or equivalent, with a minimum grade of C-. 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 ECON 333 or equivalent, with a minimum grade of C-. Students with credit for the former STAT 402 or 602 may not take this course for further credit. Quantitative.

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 ECON 333 or equivalent, with a minimum grade of C-. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.

Section Instructor Day/Time Location
E100 Gary Parker
Mo 5:30 PM – 6:20 PM
Th 4:30 PM – 6:20 PM
AQ 3181, Burnaby
AQ 3181, Burnaby
E101 Gary Parker
Mo 3:30 PM – 4:20 PM
AQ 5016, Burnaby
E102 Gary Parker
Mo 4:30 PM – 5:20 PM
AQ 5016, Burnaby
E103 Gary Parker
Mo 6:30 PM – 7:20 PM
AQ 5016, Burnaby

Students must complete 9 additional units from this list

BUS 345 - Marketing Research (3)

A course in the management of marketing research. The basics of the design, conduct, and analysis of marketing research studies. Prerequisite: BUS 343, 336, both with a minimum grade of C-; 45 units; OR Data Science majors with BUS 343 with a minimum grade of C- and 45 units. Students with credit for BUS 442 may not complete this course for further credit.

Section Instructor Day/Time Location
D100 Emily Treen
Mo 9:30 AM – 12:20 PM
SWH 10061, Burnaby
D200 Emily Treen
Mo 2:30 PM – 5:20 PM
SWH 10051, Burnaby
BUS 362 - Business Process Analysis (4)

Prepares students to model, analyze and propose improvements to business processes. In the major project, students analyze a process within an organization and use current techniques and tools to propose changes and a supporting information system. Prerequisite: BUS 237 with a minimum grade of C-; 45 units; OR Data Science majors with 45 units. Students with credit for BUS 394 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Drew Parker
Mo 10:30 AM – 12:20 PM
WMC 3210, Burnaby
D101 Mo 12:30 PM – 2:20 PM
WMC 2301, Burnaby
D102 Mo 12:30 PM – 2:20 PM
WMC 2305, Burnaby
D103 Mo 2:30 PM – 4:20 PM
WMC 2301, Burnaby
BUS 437 - Decision Analysis in Business (3)

A seminar in the use of Bayesian techniques in business decisions. Prerequisite: BUS 336, 360W, both with a minimum grade of C-; 60 units; OR Data Science majors with BUS 360W with a minimum grade of C- and 60 units.

Section Instructor Day/Time Location
D100 Srinivas Krishnamoorthy
We 2:30 PM – 5:20 PM
WMC 2507, Burnaby
BUS 440 - Simulation in Management Decision-making (4)

Development and use of simulation models as an aid in making complex management decisions. Hands on use of business related tools for computer simulation. Issues related to design and validation of simulation models, the assessment of input data, and the interpretation and use of simulation output. Prerequisite: BUS 336, 360W, both with a minimum grade of C-, 60 units; OR Data Science majors with BUS 360W with a minimum grade of C-, 60 units.

Section Instructor Day/Time Location
E100 Mohammad Ghotboddini
Th 6:00 PM – 9:50 PM
WMC 2305, Burnaby
CMPT 308 - Computability and Complexity (3)

Formal models of computation such as automata and Turing machines. Decidability and undecidability. Recursion Theorem. Connections between computability and logic (Gödel’s Incompleteness). Time and space complexity classes. NP-completeness. Prerequisite: (MACM 201 or CMPT 210) with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Valentine Kabanets
Mo 12:30 PM – 1:20 PM
Th 12:30 PM – 2:20 PM
SSCK 9500, Burnaby
SSCK 9500, Burnaby
CMPT 310 - Introduction to Artificial Intelligence (3)

A survey of modern approaches for artificial intelligence (AI). Provides an introduction to a variety of AI topics and prepares students for upper-level courses. Topics include: problem solving with search; adversarial game playing; probability and Bayesian networks; machine learning; and applications such as robotics, visual computing and natural language. Prerequisite: CMPT 225 and (MACM 101 or (ENSC 251 and ENSC 252)), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Hazra Imran
Mo 10:30 AM – 11:20 AM
Th 10:30 AM – 12:20 PM
AQ 3181, Burnaby
SWH 10081, Burnaby
CMPT 322W - Professional Responsibility and Ethics (3)

The theory and practice of computer ethics. The basis for ethical decision-making and the methodology for reaching ethical decisions concerning computing matters will be studied. Writing as a means to understand and reason about complex ethical issues will be emphasized. Prerequisite: Three CMPT units, 30 total units, and any lower division W course. Students with credit for CMPT 322 may not take this course for further credit. Writing.

CMPT 373 - Software Development Methods (3)

Survey of modern software development methodology. Several software development process models will be examined, as will the general principles behind such models. Provides experience with different programming paradigms and their advantages and disadvantages during software development. Prerequisite: CMPT 276 or 275, with a minimum grade of C-.

Section Instructor Day/Time Location
D100 William Sumner
Mo 2:30 PM – 3:20 PM
Th 2:30 PM – 4:20 PM
SRYE 3016, Surrey
SRYE 3016, Surrey
CMPT 376W - Technical Writing and Group Dynamics (3)

Covers professional writing in computing science, including format conventions and technical reports. Attention is paid to group dynamics, including team leadership, dispute resolution, cognitive bias, professional ethics and collaborative writing. Research methods are also discussed. The use of LaTeX and various version control tools are emphasized. Prerequisite: CMPT 105W and (CMPT 275 or CMPT 276), with a minimum grade of C-. Students with credit for CMPT 376 may not take this course for further credit. Writing.

Section Instructor Day/Time Location
D100 John Edgar
Mo, We, Fr 9:30 AM – 10:20 AM
SRYE 2016, Surrey
CMPT 405 - Design and Analysis of Computing Algorithms (3)

Models of computation, methods of algorithm design; complexity of algorithms; algorithms on graphs, NP-completeness, approximation algorithms, selected topics. Prerequisite: CMPT 307 with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Qianping Gu
Mo 8:30 AM – 10:20 AM
We 8:30 AM – 9:20 AM
WMC 3260, Burnaby
SWH 10041, Burnaby
CMPT 417 - Intelligent Systems (3)

Intelligent Systems using modern constraint programming and heuristic search methods. A survey of this rapidly advancing technology as applied to scheduling, planning, design and configuration. An introduction to constraint programming, heuristic search, constructive (backtrack) search, iterative improvement (local) search, mixed-initiative systems and combinatorial optimization. Prerequisite: CMPT 225 with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Hang Ma
We 3:30 PM – 4:20 PM
Fr 2:30 PM – 4:20 PM
AQ 3153, Burnaby
AQ 3153, Burnaby
CMPT 419 - Special Topics in Artificial Intelligence (3)

Current topics in artificial intelligence depending on faculty and student interest.

CMPT 470 - Web-based Information Systems (3)

This course examines: two-tier/multi-tier client/server architectures; the architecture of a Web-based information system; web servers/browser; programming/scripting tools for clients and servers; database access; transport of programming objects; messaging systems; security; and applications (such as e-commerce and on-line learning). Prerequisite: (CMPT 275 or CMPT 276) and CMPT 354, with a minimum grade of C-.

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 3181, Burnaby
D101 We 2:30 PM – 3:20 PM
WMC 2830, Burnaby
D102 We 3:30 PM – 4:20 PM
WMC 2830, Burnaby
D103 We 4:30 PM – 5:20 PM
WMC 2830, Burnaby
D104 Th 9:30 AM – 10:20 AM
WMC 2830, Burnaby
D105 Th 10:30 AM – 11:20 AM
WMC 2830, Burnaby
D106 Th 11:30 AM – 12:20 PM
WMC 2830, 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.

Section Instructor Day/Time Location
D100 Luis Goddyn
Mo, We, Fr 9:30 AM – 10:20 AM
AQ 5008, Burnaby
D101 Tu 12:30 PM – 1:20 PM
WMC 2830, Burnaby
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.

Section Instructor Day/Time Location
D100 Matthew DeVos
Mo 3:30 PM – 4:20 PM
We, Fr 3:30 PM – 4:20 PM
WMC 2503, Burnaby
WMC 3220, Burnaby
D101 Th 2:30 PM – 3:20 PM
BLU 10921, 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 ECON 333, with a minimum grade of C-. Students with credit for STAT 340 may not take STAT 342 for further credit.

Section Instructor Day/Time Location
D100 Haolun Shi
Th 12:30 PM – 2:20 PM
WMC 3260, Burnaby
D101 Haolun Shi
Mo 2:30 PM – 3:20 PM
BLU 10031, Burnaby
D102 Haolun Shi
Mo 3:30 PM – 4:20 PM
AQ 5006, Burnaby
D103 Haolun Shi
Fr 1:30 PM – 2:20 PM
AQ 5016, Burnaby
D105 Haolun Shi
Fr 3:30 PM – 4:20 PM
AQ 5016, Burnaby
STAT 445 - Applied Multivariate Analysis (3)

Introduction to principal components, cluster analysis, and other commonly used multivariate techniques. Prerequisite: STAT 285 or STAT 302 or STAT 305 or ECON 333 or equivalent, with a minimum grade of C-. 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 ECON 333 or equivalent, with a minimum grade of C-. Students with credit for the former STAT 402 or 602 may not take this course for further credit. Quantitative.

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 ECON 333 or equivalent, with a minimum grade of C-. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.

Section Instructor Day/Time Location
E100 Gary Parker
Mo 5:30 PM – 6:20 PM
Th 4:30 PM – 6:20 PM
AQ 3181, Burnaby
AQ 3181, Burnaby
E101 Gary Parker
Mo 3:30 PM – 4:20 PM
AQ 5016, Burnaby
E102 Gary Parker
Mo 4:30 PM – 5:20 PM
AQ 5016, Burnaby
E103 Gary Parker
Mo 6:30 PM – 7:20 PM
AQ 5016, Burnaby

Statistics Concentration Requirements

Lower Division Requirements

Students complete a minimum of 61 units.

Business Administration

Students complete all of

BUS 200 - Business Fundamentals (3)

Explore the fundamentals of modern business and organizational management. Working with case studies, students will build upon the basics of revenue, profits, contribution and costs, as well as integrate advanced aspects of business models, innovation, competitive advantage, core competence, and strategic analysis. Breadth-Social Sciences.

Section Instructor Day/Time Location
D100 Sasha Ramnarine
Th 2:30 PM – 5:20 PM
AQ 3005, Burnaby
E100 Shannon Wong
We 5:30 PM – 8:20 PM
AQ 3005, Burnaby
BUS 217W - Critical Thinking in Business (3)

Examine and review today's global economy through critical analysis of differing perspectives. Develop and improve critical thinking and communication skills appropriate to the business environment. Prerequisite: BUS 201 with a minimum grade of C- and 15 units; OR 45 units and corequisite: BUS 202; OR business administration joint major, joint honours, or double degree students with 45 units; OR data science major with 15 units. Writing.

Section Instructor Day/Time Location
D100 Luana Carcano
We 2:30 PM – 5:20 PM
AQ 3154, Burnaby
D200 Matthew Martell
Tu 2:30 PM – 5:20 PM
SRYC 5240, Surrey
D300 Susan Christie-Bell
We 2:30 PM – 5:20 PM
RCB 8100, Burnaby
D400 Matthew Martell
Th 9:30 AM – 12:20 PM
WMC 2230, Burnaby
E100 Jerome Francis
We 5:30 PM – 8:20 PM
WMC 2230, Burnaby
E200 Michelle Corbett
Tu 5:30 PM – 8:20 PM
RCB 8100, Burnaby
BUS 251 - Financial Accounting I (3)

An introduction to financial accounting, including accounting terminology, understanding financial statements, analysis of a business entity using financial statements. Includes also time value of money and a critical review of the conventional accounting system. Prerequisite: 12 units. Quantitative.

Section Instructor Day/Time Location
D100 Susan Bubra
Th 12:30 PM – 2:20 PM
RCB IMAGTH, Burnaby
D101 Th 2:30 PM – 3:20 PM
BLU 10655, Burnaby
D102 Th 6:30 PM – 7:20 PM
WMC 2523, Burnaby
D103 Th 3:30 PM – 4:20 PM
BLU 10655, Burnaby
D104 Th 6:30 PM – 7:20 PM
WMC 3511, Burnaby
D105 Th 4:30 PM – 5:20 PM
WMC 3253, Burnaby
D106 Th 4:30 PM – 5:20 PM
WMC 3255, Burnaby
D107 Th 5:30 PM – 6:20 PM
WMC 3513, Burnaby
D108 Th 5:30 PM – 6:20 PM
WMC 3515, Burnaby
D200 Praise Ma
Fr 10:30 AM – 12:20 PM
SRYC 5240, Surrey
D201 Fr 12:30 PM – 1:20 PM
SRYC 5060, Surrey
D202 Fr 12:30 PM – 1:20 PM
SRYC 5320, Surrey
D203 Fr 1:30 PM – 2:20 PM
SRYC 5060, Surrey
D204 Fr 1:30 PM – 2:20 PM
SRYC 5320, Surrey
E100 Susan Bubra
Th 5:30 PM – 7:20 PM
RCB IMAGTH, Burnaby
E101 Th 7:30 PM – 8:20 PM
WMC 3253, Burnaby
E102 Th 7:30 PM – 8:20 PM
WMC 3250, Burnaby
E103 Th 7:30 PM – 8:20 PM
WMC 2507, Burnaby
E104 Th 8:30 PM – 9:20 PM
WMC 3513, Burnaby
BUS 272 - Behaviour in Organizations (3)

Theories, concepts and issues in the field of organizational behaviour with an emphasis on individual and team processes. Core topics include employee motivation and performance, stress management, communication, work perceptions and attitudes, decision-making, team dynamics, employee involvement and conflict management. Prerequisite: 12 units.

Section Instructor Day/Time Location
D100 Sam Thiara
Tu 10:30 AM – 12:20 PM
SSCC 9002, Burnaby
D101 Tu 12:30 PM – 1:20 PM
AQ 2122, Burnaby
D102 Tu 12:30 PM – 1:20 PM
WMC 3513, Burnaby
D103 Tu 1:30 PM – 2:20 PM
WMC 3515, Burnaby
D104 Tu 1:30 PM – 2:20 PM
AQ 5006, Burnaby
D105 Tu 2:30 PM – 3:20 PM
AQ 2122, Burnaby
D106 Tu 2:30 PM – 3:20 PM
WMC 2260, Burnaby
D107 Tu 3:30 PM – 4:20 PM
WMC 3513, Burnaby
D200 Sam Thiara
Th 10:30 AM – 12:20 PM
SRYC 3170, Surrey
D201 Th 12:30 PM – 1:20 PM
SRYC 5060, Surrey
D202 Th 12:30 PM – 1:20 PM
SRYC 5320, Surrey
D203 Th 1:30 PM – 2:20 PM
SRYC 5060, Surrey
D204 Th 1:30 PM – 2:20 PM
SRYC 5320, Surrey
D300 William Scott
Tu 12:30 PM – 2:20 PM
EDB 7618, Burnaby
D301 Tu 2:30 PM – 3:20 PM
WMC 3513, Burnaby
D302 Tu 2:30 PM – 3:20 PM
WMC 3517, Burnaby
D303 Tu 3:30 PM – 4:20 PM
WMC 3517, Burnaby
D304 Tu 3:30 PM – 4:20 PM
BLU 10901, Burnaby
D305 Tu 4:30 PM – 5:20 PM
WMC 2533, Burnaby
E100 Chris Zatzick
We 4:30 PM – 6:20 PM
SSCC 9002, Burnaby
E101 We 6:30 PM – 7:20 PM
AQ 5009, Burnaby
E102 We 6:30 PM – 7:20 PM
AQ 5014, Burnaby
E103 We 6:30 PM – 7:20 PM
AQ 5004, Burnaby
E104 We 7:30 PM – 8:20 PM
AQ 5004, Burnaby

Computing Science

Students complete all 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, e.g. Python. The students will be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode; data types and control structures; fundamental algorithms; recursion; reading and writing files; measuring performance of algorithms; debugging tools; basic terminal navigation using shell commands. 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, We, Fr 9:30 AM – 10:20 AM
AQ 3181, Burnaby
D300 Diana Cukierman
Mo, We, Fr 1:30 PM – 2:20 PM
SSCB 9200, Burnaby
D400 Toby Donaldson
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SRYE 1002, Surrey
SRYE 1002, Surrey
OL01 Mo, We, Fr 4:30 PM – 5:20 PM
Distance Education
CMPT 125 - Introduction to Computing Science and Programming II (3)

A rigorous introduction to computing science and computer programming, suitable for students who already have some background in computing science and programming. Intended for students who will major in computing science or a related program. Topics include: memory management; fundamental algorithms; formally analyzing the running time of algorithms; abstract data types and elementary data structures; object-oriented programming and software design; specification and program correctness; reading and writing files; debugging tools; shell commands. Prerequisite: CMPT 120 or CMPT 130, with a minimum grade of C-. Students with credit for CMPT 126, 129, 135 or CMPT 200 or higher may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Igor Shinkar
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
AQ 3182, Burnaby
AQ 3181, Burnaby
D101 Igor Shinkar
Th 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D102 Igor Shinkar
Th 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D103 Igor Shinkar
Th 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D104 Igor Shinkar
Th 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D105 Igor Shinkar
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D106 Igor Shinkar
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D107 Igor Shinkar
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
D108 Igor Shinkar
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
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, CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252), all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 David Mitchell
Mo, We, Fr 1:30 PM – 2:20 PM
WMC 3520, Burnaby
D101 David Mitchell
Tu 8:30 AM – 9:20 AM
ASB 9838, Burnaby
D102 David Mitchell
Tu 8:30 AM – 9:20 AM
ASB 9838, Burnaby
D103 David Mitchell
Tu 9:30 AM – 10:20 AM
ASB 9838, Burnaby
D104 David Mitchell
Tu 9:30 AM – 10:20 AM
ASB 9838, Burnaby
D105 David Mitchell
Tu 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D106 David Mitchell
Tu 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D107 David Mitchell
Tu 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D108 David Mitchell
Tu 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D200 Anne Lavergne
Tu 2:30 PM – 4:20 PM
Fr 2:30 PM – 3:20 PM
SRYE 2016, Surrey
SRYE 2016, Surrey
D201 Anne Lavergne
Mo 2:30 PM – 3:20 PM
SRYE 4024, Surrey
D202 Anne Lavergne
Mo 2:30 PM – 3:20 PM
SRYE 4013, Surrey
D203 Anne Lavergne
Mo 4:30 PM – 5:20 PM
SRYE 4024, Surrey
D204 Anne Lavergne
Mo 4:30 PM – 5:20 PM
SRYE 4013, Surrey
D205 Anne Lavergne
Mo 5:30 PM – 6:20 PM
SRYE 4024, Surrey
CMPT 276 - Introduction to Software Engineering (3)

An overview of various techniques used for software development and software project management. Major tasks and phases in modern software development, including requirements, analysis, documentation, design, implementation, testing,and maintenance. Project management issues are also introduced. Students complete a team project using an iterative development process. Prerequisite: One W course, CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and (MATH 151 or MATH 150), all with a minimum grade of C-. MATH 154 or MATH 157 with at least a B+ may be substituted for MATH 151 or MATH 150. Students with credit for CMPT 275 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Saba Alimadadi Jani
Mo, We, Fr 10:30 AM – 11:20 AM
AQ 3149, Burnaby
D200 Rob Cameron
Mo 5:30 PM – 8:20 PM
AQ 3149, Burnaby
D300 Brian Fraser
Mo, We, Fr 1:30 PM – 2:20 PM
SRYE 3016, Surrey
CMPT 295 - Introduction to Computer Systems (3)

The curriculum introduces students to topics in computer architecture that are considered fundamental to an understanding of the digital systems underpinnings of computer systems. Prerequisite: Either (MACM 101 and (CMPT 125 or CMPT 135)) or (MATH 151 and CMPT 102 for students in an Applied Physics program), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Alaa Alameldeen
Arrvindh Shriraman
Mo 4:30 PM – 5:20 PM
Th 4:30 PM – 6:20 PM
SWH 10081, Burnaby
SWH 10081, Burnaby
D101 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D102 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D103 Alaa Alameldeen
Arrvindh Shriraman
Tu 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D104 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D105 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D106 Alaa Alameldeen
Arrvindh Shriraman
Tu 4:30 PM – 5:20 PM
ASB 9838, Burnaby
D107 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D108 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D109 Alaa Alameldeen
Arrvindh Shriraman
Tu 5:30 PM – 6:20 PM
ASB 9838, Burnaby
D110 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby
D111 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby
D112 Alaa Alameldeen
Arrvindh Shriraman
Tu 6:30 PM – 7:20 PM
ASB 9838, Burnaby

Mathematics and Computing Science

Students complete both of

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 Andrei Bulatov
Mo 11:30 AM – 12:20 PM
We, Fr 11:30 AM – 12:20 PM
SWH 10081, Burnaby
SSCB 9201, Burnaby
D101 Andrei Bulatov
Fr 12:30 PM – 1:20 PM
AQ 5030, Burnaby
D102 Andrei Bulatov
Fr 12:30 PM – 1:20 PM
BLU 10901, Burnaby
D103 Andrei Bulatov
Fr 1:30 PM – 2:20 PM
BLU 10901, Burnaby
D104 Andrei Bulatov
Fr 1:30 PM – 2:20 PM
WMC 2531, Burnaby
D105 Andrei Bulatov
Fr 2:30 PM – 3:20 PM
AQ 5006, Burnaby
D106 Andrei Bulatov
Fr 2:30 PM – 3:20 PM
WMC 3517, Burnaby
D107 Andrei Bulatov
Fr 3:30 PM – 4:20 PM
WMC 2531, Burnaby
D108 Andrei Bulatov
Fr 3:30 PM – 4:20 PM
AQ 5009, Burnaby
D109 Andrei Bulatov
Fr 10:30 AM – 11:20 AM
AQ 5035, Burnaby
D200 Thomas Shermer
We 3:30 PM – 4:20 PM
Fr 2:30 PM – 4:20 PM
SRYE 1002, Surrey
SRYE 1002, Surrey
D201 Thomas Shermer
Tu 2:30 PM – 3:20 PM
SRYC 3240, Surrey
D202 Thomas Shermer
Tu 2:30 PM – 3:20 PM
SRYC 3250, Surrey
D203 Thomas Shermer
Tu 3:30 PM – 4:20 PM
SRYC 3240, Surrey
D204 Thomas Shermer
Tu 3:30 PM – 4:20 PM
SRYC 3250, Surrey
D205 Thomas Shermer
Tu 4:30 PM – 5:20 PM
SRYC 3240, Surrey
D206 Thomas Shermer
Tu 4:30 PM – 5:20 PM
SRYC 5060, Surrey
D207 Thomas Shermer
Tu 5:30 PM – 6:20 PM
SRYC 5060, Surrey
D208 Thomas Shermer
Tu 5:30 PM – 6:20 PM
SRYC 3040, 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 Matthew DeVos
Mo, We, Fr 12:30 PM – 1:20 PM
SSCC 9002, Burnaby
D200 Mahsa Faizrahnemoon
Mo, We, Fr 12:30 PM – 1:20 PM
SWH 10081, Burnaby
OP02 TBD

Data Science

Students complete

DATA 180 - Undergraduate Seminar in Data Science (1)

A seminar primarily for students undertaking a major or an honours program in Data Science. Prerequisite: Major or honours in Data Science or permission of the program director. Students with credit for DATA (or MSSC) 480 cannot receive credit for DATA (or MSSC) 180.

Section Instructor Day/Time Location
E100 Jiguo Cao
Tu 6:30 PM – 8:20 PM
SWH 10041, Burnaby

Mathematics

Students complete 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
D100 Sophie Burrill
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9201, Burnaby
D101 Tu 8:30 AM – 9:20 AM
WMC 2503, Burnaby
D102 Tu 9:30 AM – 10:20 AM
WMC 2532, Burnaby
D103 Tu 10:30 AM – 11:20 AM
WMC 2503, Burnaby
D104 We 2:30 PM – 3:20 PM
WMC 2810, Burnaby
D105 We 3:30 PM – 4:20 PM
WMC 2810, Burnaby
D200 Jamie Mulholland
Mo, We, Fr 8:30 AM – 9:20 AM
RCB IMAGTH, Burnaby
D201 Tu 8:30 AM – 9:20 AM
AQ 5039, Burnaby
D202 Tu 1:30 PM – 2:20 PM
BLU 10921, Burnaby
D203 Tu 2:30 PM – 3:20 PM
AQ 5037, Burnaby
D204 Fr 2:30 PM – 3:20 PM
RCB 5120, Burnaby
D205 Fr 3:30 PM – 4:20 PM
RCB 5120, Burnaby
D400 Natalia Kouzniak
Mo, We, Fr 9:30 AM – 10:20 AM
SRYE 1002, Surrey
D401 Natalia Kouzniak
Th 12:30 PM – 1:20 PM
SRYC 2740, Surrey
D402 Natalia Kouzniak
Th 2:30 PM – 3:20 PM
SRYC 2740, Surrey
D403 Natalia Kouzniak
Th 1:30 PM – 2:20 PM
SRYC 2740, Surrey
OP01 TBD
OP02 TBD
OP03 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.

Section Instructor Day/Time Location
D100 Sophie Burrill
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9201, Burnaby
D200 Jamie Mulholland
Mo, We, Fr 8:30 AM – 9:20 AM
RCB IMAGTH, Burnaby
D400 Natalia Kouzniak
Mo, We, Fr 9:30 AM – 10:20 AM
SRYE 1002, Surrey
OP01 TBD
OP02 TBD
OP04 TBD
MATH 154 - Mathematics for the Life Sciences I (3)

Designed for students specializing in the life sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications, integration, and differential equations; mathematical models of biological processes and their implementation and analysis using software. 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 Ailene MacPherson
Mo, We, Fr 8:30 AM – 9:20 AM
SSCC 9001, Burnaby
D400 Ladislav Stacho
Mo, We, Fr 9:30 AM – 10:20 AM
SRYC 5280, Surrey
OP01 TBD
OP02 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; introduction to functions of several variables with emphasis on partial derivatives and extrema. 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 Imin Chen
Mo, We, Fr 11:30 AM – 12:20 PM
SSCC 9001, Burnaby
D400 Roghayeh Ebrahim Nataj
Mo, We, Fr 12:30 PM – 1:20 PM
SRYC 5280, Surrey
OP01 TBD
OP02 TBD

and all 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, with a minimum grade of C-; 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 Michael Monagan
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9200, Burnaby
OP01 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, with a minimum grade of C-. Students with credit for MATH 208 may not take this course for further credit. Writing/Quantitative.

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 with a minimum grade of C-; 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
D100 Jake Levinson
Mo, We, Fr 8:30 AM – 9:20 AM
WMC 3520, Burnaby
D200 Marni Julie Mishna
Mo, We, Fr 8:30 AM – 9:20 AM
WMC 2830, Burnaby
D400 Roghayeh Ebrahim Nataj
Mo, We, Fr 8:30 AM – 9:20 AM
SRYC 5280, Surrey
OP01 TBD
OP02 TBD
OP03 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, with a minimum grade of C-; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 11:30 AM – 12:20 PM
SSCB 9200, Burnaby
D400 Randall Pyke
Mo, We, Fr 1:30 PM – 2:20 PM
SRYC 2600, Surrey
OP01 TBD
OP02 Mo, We, Fr 1:30 PM – 2:20 PM
,
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, with a minimum grade of C-; 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 Jake Levinson
Mo, We, Fr 11:30 AM – 12:20 PM
SWH 10041, Burnaby
OP01 TBD

Statistics

Students complete all of

STAT 240 - Introduction to Data Science (3)

Introduction to modern tools and methods for data acquisition, management, and visualization capable of scaling to Big Data. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, and one of CMPT 102, CMPT 120, CMPT 125, CMPT 128, CMPT 129, CMPT 130, all with a minimum grade of C- or permission of the instructor. STAT 260 is also recommended. Quantitative.

STAT 260 - Introductory R for Data Science (2)

An introduction to the R programming language for data science. Exploring data: visualization, transformation and summaries. Data wrangling: reading, tidying, and data types. No prior computer programming experience required. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, ECON 233, or POL 201, with a grade of at least C- or permission of the instructor. Corequisite: STAT 261. Students who have taken STAT 341 or STAT 360 first may not then take this course for further credit.

Section Instructor Day/Time Location
D100 David Stenning
Tu 2:30 PM – 4:20 PM
SSCB 9200, Burnaby
STAT 261 - Laboratory for Introductory R for Data Science (1)

A hands-on application of the R programming language for data science. Using the R concepts covered in STAT 260, students will explore (visualize, transform, and summarize) and wrangle (read and tidy) data. No prior computer programming experience required. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, ECON 233, or POL 201, with a grade of at least C- or permission of the instructor. Corequisite: STAT 260. Students who have taken STAT 341 or STAT 360 first may not then take this course for further credit.

Section Instructor Day/Time Location
D010 David Stenning
Th 6:30 PM – 7:20 PM
AQ 3148.2, Burnaby
D100 David Stenning
Tu 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
D200 David Stenning
Tu 5:30 PM – 6:20 PM
AQ 3148.2, Burnaby
D300 David Stenning
Tu 6:30 PM – 7:20 PM
AQ 3148.2, Burnaby
D400 David Stenning
We 3:30 PM – 4:20 PM
AQ 3148.2, Burnaby
D500 David Stenning
We 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
D600 David Stenning
We 5:30 PM – 6:20 PM
AQ 3148.2, Burnaby
D700 David Stenning
Th 4:30 PM – 5:20 PM
AQ 3148.2, Burnaby
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, with a minimum grade of C-. 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
D100 Sonja Isberg
Mo, We, Fr 9:30 AM – 10:20 AM
SSCB 9201, Burnaby
OL01 Distance Education
OP01 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 and one of MATH 152, MATH 155, or MATH 158, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 David Stenning
Mo 12:30 PM – 2:20 PM
We 12:30 PM – 1:20 PM
AQ 3003, Burnaby
AQ 3003, Burnaby
D101 David Stenning
Fr 1:30 PM – 2:20 PM
AQ 5007, Burnaby
D102 David Stenning
Fr 2:30 PM – 3:20 PM
AQ 5007, Burnaby

* Recommended

Upper Division Requirements

Students complete a minimum of 49 units.

Business Administration

Students complete all of

BUS 343 - Introduction to Marketing (3)

The environment of marketing; relation of social sciences to marketing; evaluation of marketing theory and research; assessment of demand, consumer behaviour analysis; market institutions; method and mechanics of distribution in domestic, foreign and overseas markets; sales organization; advertising; new product development, publicity and promotion; marketing programs. Prerequisite: 45 units. Students with credit for COMM 343 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Pei-Shiuan Lin
Tu 8:30 AM – 10:20 AM
AQ 3181, Burnaby
D101 Tu 10:30 AM – 11:20 AM
RCB 7100, Burnaby
D102 Tu 10:30 AM – 11:20 AM
RCB 8105, Burnaby
D103 Tu 10:30 AM – 11:20 AM
RCB 8104, Burnaby
D104 Tu 11:30 AM – 12:20 PM
RCB 8104, Burnaby
D105 Tu 11:30 AM – 12:20 PM
RCB 6100, Burnaby
D106 Tu 11:30 AM – 12:20 PM
RCB 6122, Burnaby
D107 Tu 12:30 PM – 1:20 PM
RCB 6100, Burnaby
D108 Tu 12:30 PM – 1:20 PM
RCB 6122, Burnaby
D109 Tu 12:30 PM – 1:20 PM
RCB 7105, Burnaby
D110 Tu 1:30 PM – 2:20 PM
RCB 7105, Burnaby
D111 Tu 1:30 PM – 2:20 PM
RCB 6100, Burnaby
D200 Pei-Shiuan Lin
Th 8:30 AM – 10:20 AM
SRYC 3090, Surrey
D201 Th 10:30 AM – 11:20 AM
SRYC 3260, Surrey
D202 Th 10:30 AM – 11:20 AM
SRYC 3010, Surrey
D203 Th 11:30 AM – 12:20 PM
SRYC 3260, Surrey
D204 Th 11:30 AM – 12:20 PM
SRYC 3010, Surrey
D205 Th 12:30 PM – 1:20 PM
SRYC 3010, Surrey
BUS 360W - Business Communication (4)

Helps students develop professional writing- and speaking-based communication strategies they can confidently adapt to a wide range of business situations. The course aims to raise their communication performance to a professionally acceptable level, rather than to memorize or theorize about communication knowledge: this is a “learn-by-doing” course. Students will improve their ability to conceptualize, analyze/evaluate, synthesize, and apply information to guide their thinking and finished products across various business contexts. As teamwork is a fundamental skill valued by employers, students will participate in a major team project to learn about and apply best practices for collaboration with respect to professional business communication. The primary means of instruction and learning is guided practice in both writing and presenting in response to realistic business contexts. Instruction and assessment focus on both the process of creating professional, finished products, as well as the quality of those products. Prerequisite: This course is open to students admitted prior to Fall 2014 to the business administration major, honours, or second degree program and who have 45 units, OR to students admitted Fall 2014 - Summer 2017 to the business administration major, honours, or second degree program and who have 45 units and BUS 130 or (BUS 201 or BUS 202) or BUS 301, with a minimum grade of C-, OR to students admitted Fall 2017 – Summer 2022 to the business administration major, honours, or second degree program and who have 45 units and BUS 130 or (BUS 201 or BUS 202) or BUS 301, and BUS 217W, both with a minimum grade of C-, OR to students admitted Fall 2022 onwards to the business administration major, honours, or second degree program, and who have 45 units; BUS 217W and (BUS 201 or BUS 202), both with a minimum grade of C-; and Corequisite: BUS 300, OR to business administration joint major or joint honours students with BUS 217W with a minimum grade of C- and 45 units, OR to business and economics joint major students with ECON 220W with a minimum grade of C- and 45 units, OR to mechatronic systems engineering and business administration double degree students with 45 units, OR to management systems science or actuarial science majors with 45 units OR to data science major with BUS 217W with a minimum grade of C- and 45 units. Students who have taken BUS 360 may not take this course for further credit. Writing.

Section Instructor Day/Time Location
D100 Leanne Barlow
Tu 2:30 PM – 5:20 PM
WMC 2507, Burnaby
D200 Darren Francis
We 9:30 AM – 12:20 PM
RCB 7100, Burnaby
D300 Kevin Stewart
Th 11:30 AM – 2:20 PM
WMC 3533, Burnaby
D400 Leanne Barlow
Tu 11:30 AM – 2:20 PM
WMC 2210, Burnaby
D500 Christian Venhuizen
Th 2:30 PM – 5:20 PM
SRYC 5100, Surrey
D600 Christian Venhuizen
We 2:30 PM – 5:20 PM
SRYC 5100, Surrey
D700 Leanne Barlow
Th 8:30 AM – 11:20 AM
WMC 2507, Burnaby
E100 Kevin Stewart
We 6:30 PM – 9:20 PM
WMC 3533, Burnaby
E200 Kevin Stewart
Tu 6:30 PM – 9:20 PM
WMC 2210, Burnaby
BUS 439 - Analytics Project (3) *

Examines complex, real-world decision making issues using an evidence-based approach that employs decision making strategies involving statistics, data management, analytics, and decision theory. Through a major decision making project within the community, students will experience first-hand the process of consultation, data acquisition, analysis, and recommendation. The data in the project will be proprietary to the community partners and students thus need to sign a non-disclosure agreement. A non-disclosure agreement template is attached to the course outline. The results of the project will remain the intellectual property of the students; notwithstanding, those results will be shared with the data provider. Students also have an option to complete a project with non-proprietary data. Prerequisite: BUS 345 or BUS 440, BUS 360W, BUS 437 or BUS 441, BUS 445, BUS 462, and BUS 464, all with a minimum grade of C-; 90 units; OR Data Science majors with BUS 360W, BUS 445, CMPT 354, all with a minimum grade of C- and 90 units.

Section Instructor Day/Time Location
D100 Jason Ho
Tu 11:30 AM – 2:20 PM
WMC 2305, Burnaby
BUS 445 - Customer Analytics (3) **

Exposes students to the art of using analytic tools from across the spectrum of data mining and modeling to provide powerful competitive advantage in business. Students will learn to recognize when a method should or should not be used, what data is required, and how to use the software tools. Areas covered include database marketing, geospatial marketing and fundamental strategic and tactical decisions such as segmentation, targeting and allocating resources to the marketing mix. Prerequisite: BUS 343, 336, 360W, all with a minimum grade of C-, 60 units; OR Data Science majors with BUS 343, 360W, both with a minimum grade of C-, and 60 units.

Section Instructor Day/Time Location
D100 Miremad Soleymanian
Th 11:30 AM – 2:20 PM
WMC 2305, Burnaby
D200 Miremad Soleymanian
Fr 2:30 PM – 5:20 PM
WMC 2305, Burnaby

*For this course, Data Science students are eligible for a prerequisite waiver for BUS 345, 437, 445, 462, 464, 90 units. Students should consult with their program advisor.

**For this course, Data Science students are eligible for a prerequisite waiver for BUS 336. Students should consult with their program advisor.

Computing Science

Students complete all of

CMPT 300 - Operating Systems I (3)

This course aims to give the student an understanding of what a modern operating system is, and the services it provides. It also discusses some basic issues in operating systems and provides solutions. Topics include multiprogramming, process management, memory management, and file systems. Prerequisite: CMPT 225 and (CMPT 295 or ENSC 254), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Hazra Imran
Mo 8:30 AM – 9:20 AM
Th 8:30 AM – 10:20 AM
AQ 3182, Burnaby
SSCK 9500, Burnaby
D200 Harinder Khangura
We 9:30 AM – 10:20 AM
Fr 8:30 AM – 10:20 AM
SRYE 3016, Surrey
SRYE 3016, Surrey
CMPT 307 - Data Structures and Algorithms (3)

Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms (greedy, divide & conquer, dynamic programming, network flows). Introduction to NP-completeness. Prerequisite: CMPT 225, (MACM 201 or CMPT 210), (MATH 150 or MATH 151), and (MATH 232 or MATH 240), all with a minimum grade of C-. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 150 or MATH 151.

Section Instructor Day/Time Location
D100 David Mitchell
Mo, We, Fr 9:30 AM – 10:20 AM
EDB 7618, Burnaby
CMPT 353 - Computational Data Science (3)

Basic concepts and programming tools for handling and processing data. Includes data acquisition, cleaning data sources, application of machine learning techniques and data analysis techniques, large-scale computation on a computing cluster. Prerequisite: CMPT 225 and (STAT 101, STAT 270, ENSC 280, or MSE 210), with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Gregory Baker
Tu 8:30 AM – 10:20 AM
Fr 8:30 AM – 9:20 AM
EDB 7618, Burnaby
AQ 3181, Burnaby
CMPT 354 - Database Systems I (3)

Logical representations of data records. Data models. Studies of some popular file and database systems. Document retrieval. Other related issues such as database administration, data dictionary and security. Prerequisite: CMPT 225 and (MACM 101 or (ENSC 251 and ENSC 252)), all with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Ke Wang
Mo 4:30 PM – 6:20 PM
We 5:30 PM – 6:20 PM
AQ 3182, Burnaby
AQ 3181, Burnaby
D200 John Edgar
Mo, We, Fr 1:30 PM – 2:20 PM
SRYE 1002, Surrey
CMPT 454 - Database Systems II (3)

An advanced course on database systems which covers crash recovery, concurrency control, transaction processing, distributed database systems as the core material and a set of selected topics based on the new developments and research interests, such as object-oriented data models and systems, extended relational systems, deductive database systems, and security and integrity. Prerequisite: CMPT 300 and 354, with a minimum grade of C-.

Section Instructor Day/Time Location
D100 Tianzheng Wang
Mo 10:30 AM – 12:20 PM
We 10:30 AM – 11:20 AM
AQ 3159, Burnaby
BLU 9660, Burnaby

Mathematics

Students complete one 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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D400 Abraham Punnen
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SRYC 5280, Surrey
SRYC 5280, Surrey
D402 Th 3:30 PM – 4:20 PM
SRYC 2750, Surrey
D403 Th 4:30 PM – 5:20 PM
SRYC 2750, Surrey
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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Cedric Chauve
Tu 10:30 AM – 12:20 PM
Fr 10:30 AM – 11:20 AM
WMC 2202, Burnaby
WMC 2202, Burnaby
D101 Fr 2:30 PM – 3:20 PM
AQ 5008, Burnaby
D102 Fr 3:30 PM – 4:20 PM
AQ 5008, Burnaby

Statistics

Students complete all of

STAT 330 - Introduction to Mathematical Statistics (3)

Review of probability and distributions. Multivariate distributions. Distributions of functions of random variables. Limiting distributions. Inference. Sufficient statistics for the exponential family. Maximum likelihood. Bayes estimation, Fisher information, limiting distributions of MLEs. Likelihood ratio tests. Prerequisite: STAT 285, MATH 251, and one of MATH 232 or MATH 240, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Liangliang Wang
Mo 12:30 PM – 2:20 PM
We 12:30 PM – 1:20 PM
AQ 3005, Burnaby
AQ 3005, Burnaby
D101 Liangliang Wang
Mo 8:30 AM – 9:20 AM
AQ 5007, Burnaby
D102 Liangliang Wang
Mo 9:30 AM – 10:20 AM
AQ 5007, Burnaby
D103 Liangliang Wang
We 9:30 AM – 10:20 AM
AQ 5007, Burnaby
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, all with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Rachel Altman
Tu 12:30 PM – 2:20 PM
Fr 12:30 PM – 1:20 PM
SSCC 9000, Burnaby
SSCC 9000, Burnaby
D101 Rachel Altman
Tu 9:30 AM – 10:20 AM
AQ 5039, Burnaby
D102 Rachel Altman
Fr 9:30 AM – 10:20 AM
WMC 2522, Burnaby
D103 Rachel Altman
Fr 10:30 AM – 11:20 AM
WMC 2532, Burnaby
STAT 403 - Intermediate Sampling and Experimental Design (3)

A practical introduction to useful sampling techniques and intermediate level experimental designs. This course may not be used to satisfy the upper division requirements of the Statistics major or honours program. Prerequisite: STAT 302, 305 or 350 or ECON 333, all with a minimum grade of C-. Students with credit for STAT 410 or 430 may not take STAT 403 for further credit. Quantitative.

STAT 440 - Learning from Big Data (3)

A data-first discovery of advanced statistical methods. Focus will be on a series of forecasting and prediction competitions, each based on a large real-world dataset. Additionally, practical tools for statistical modeling in real-world environments will be explored. Prerequisite: 90 units including STAT 350 with a minimum grade of C- and one of STAT 341, STAT 260, or CMPT 225, with a minimum grade of C-, or instructor approval. STAT 240 is also recommended.

Section Instructor Day/Time Location
E100 Lloyd Elliott
Mo 4:30 PM – 5:20 PM
We 4:30 PM – 6:20 PM
BLU 10921, Burnaby
WMC 2532, Burnaby
STAT 450 - Statistical Theory (3)

Distribution theory, methods for constructing tests, estimators, and confidence intervals with special attention to likelihood methods. Properties of the procedures including large sample theory. Prerequisite: STAT 330 with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Boxin Tang
Mo 10:30 AM – 12:20 PM
We 10:30 AM – 11:20 AM
AQ 5039, Burnaby
AQ 5039, Burnaby
D101 Boxin Tang
We 8:30 AM – 9:20 AM
AQ 5039, Burnaby
STAT 452 - Statistical Learning and Prediction (3)

An introduction to the essential modern supervised and unsupervised statistical learning methods. Topics include review of linear regression, classification, statistical error measurement, flexible regression and classification methods, clustering and dimension reduction. Prerequisite: STAT 302 or STAT 305 or STAT 350 or ECON 333 or equivalent, with a minimum grade of C-. Quantitative.

Section Instructor Day/Time Location
D100 Haolun Shi
We 9:30 AM – 10:20 AM
Fr 8:30 AM – 10:20 AM
AQ 3182, Burnaby
AQ 3182, Burnaby
D101 Haolun Shi
We 11:30 AM – 12:20 PM
AQ 5037, Burnaby
D102 Haolun Shi
We 12:30 PM – 1:20 PM
AQ 5030, Burnaby
D103 Haolun Shi
We 1:30 PM – 2:20 PM
WMC 2503, Burnaby
D104 Haolun Shi
We 2:30 PM – 3:20 PM
WMC 2532, Burnaby
D105 Haolun Shi
We 3:30 PM – 4:20 PM
AQ 5016, Burnaby
D106 Haolun Shi
Mo 9:30 AM – 10:20 AM
AQ 5027, Burnaby

University Honours 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.

Double Majors and Minors

Students wishing to complete a second major or a minor in addition to a Data Science (DATA) major must satisfy all DATA requirements. At least 34 upper division units must be allocated exclusively to the DATA major.

This includes at least nine units from each of the lists under the sub-headings Business Administration, Computing Science, Mathematics and Statistics. Units used to satisfy DATA upper division requirements beyond these 34 can be applied simultaneously to the other major, minor or honours.