Please note:

To view the Spring 2024 Academic Calendar, go to www.sfu.ca/students/calendar/2024/spring.html.

Department of Statistics and Actuarial Science | Faculty of Science Simon Fraser University Calendar | Summer 2024

Actuarial Science Major

Bachelor of Science

The Department of Statistics and Actuarial Science offers a bachelor of science (BSc) program in actuarial science within the Faculty of Science.

Frequently asked questions about the program and contact information for the Undergraduate Advisor for the department can be found here. Students should seek advice early in their academic careers about program planning from the department's advisors.

Admission Requirements

Students may be admitted by direct entry on their university application, or by application to the Department of Statistics and Actuarial Science, after they have been admitted.

Visit this website to view admission requirements.

Courses for Further Credit

No student may complete, for further credit, any course offered by the Department of Statistics and Actuarial Science which is a prerequisite for a course the student has already completed with a grade of C- or higher without permission of the department.

Computing Recommendation

Some experience with a high-level programming language is recommended by the beginning of the second year.

Prerequisite Grade Requirement

Students must have a grade of C- or better in prerequisites for STAT courses. Students must have a grade of C or better in prerequisites for ACMA courses.

GPA Required for Continuation

To continue in the program, students must maintain at least a 2.25 grade point average in ACMA, CMPT, MACM, MATH, and STAT courses.

Graduation Requirement

Students are required to complete a minimum of 44 upper division units including a minimum of 28 units in the major subject or field and achieve a CGPA of 2.5 or better to graduate.

Program Requirements

Students complete 120 units, as specified below.

Graduation Grade Point Averages

Lower Division Requirements

Students complete all of

ACMA 101 - Introduction to Insurance (3)

General overview of universally useful concepts in insurance, pensions and financial management. Typical life, health and property & casualty insurance products; underwriting; pricing; reserving; regulation; social insurance; retirement plans and annuities; financial planning: mortgages, loans, wealth management. Corequisite: MATH 150, 151, 154 or 157. Quantitative/Breadth-Science.

ACMA 201 - Interest Theory and Applications (3)

Measurement of interest, present value. Equations of value. Annuities. Loans and amortization schedules. Bonds and other securities. Cash flows: yield rates, duration, convexity, immunization. Yield curves: spot rates, forward rates. Interest rate swaps. Covers part of the syllabus for Exam FM of the Society of Actuaries and Exam 2 of the Casualty Actuarial Society. Prerequisite: MATH 152 with a minimum grade of C; or MATH 155 or MATH 158, with a grade of at least B. Students with credit for ACMA 210 cannot take ACMA 201 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Cherie Ng
May 6 – Jun 17, 2024: Mon, Wed, Fri, 12:30–2:20 p.m.
Burnaby
OP01 TBD
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 Grant Mowbray
May 6 – Aug 2, 2024: Mon, 10:30 a.m.–12:20 p.m.
Burnaby
D101 May 6 – Aug 2, 2024: Mon, 12:30–1:20 p.m.
Burnaby
D102 May 6 – Aug 2, 2024: Mon, 12:30–1:20 p.m.
Burnaby
D103 May 6 – Aug 2, 2024: Mon, 12:30–1:20 p.m.
Burnaby
D104 May 6 – Aug 2, 2024: Mon, 1:30–2:20 p.m.
Burnaby
D105 May 6 – Aug 2, 2024: Mon, 1:30–2:20 p.m.
Burnaby
D106 May 6 – Aug 2, 2024: Mon, 1:30–2:20 p.m.
Burnaby
D107 May 6 – Aug 2, 2024: Mon, 2:30–3:20 p.m.
Burnaby
D108 May 6 – Aug 2, 2024: Mon, 2:30–3:20 p.m.
Burnaby
D200 Grant Mowbray
May 6 – Aug 2, 2024: Thu, 10:30 a.m.–12:20 p.m.
Surrey
D201 May 6 – Aug 2, 2024: Thu, 12:30–1:20 p.m.
Surrey
D202 May 6 – Aug 2, 2024: Thu, 12:30–1:20 p.m.
Surrey
D203 May 6 – Aug 2, 2024: Thu, 1:30–2:20 p.m.
Surrey
D204 May 6 – Aug 2, 2024: Thu, 1:30–2:20 p.m.
Surrey
BUS 254 - Managerial Accounting I (3)

Theory and methods of cost compilation for managerial planning, control and decision making; the use of budgets and analysis in planning and controlling operations, establishing supervisory and departmental responsibility, and various techniques of measuring results. Prerequisite: BUS 251 with a minimum grade of C-; 15 units. Quantitative.

Section Instructor Day/Time Location
D100 Weiming Liu
May 6 – Aug 2, 2024: Tue, 8:30–10:20 a.m.
Burnaby
D101 May 6 – Aug 2, 2024: Tue, 10:30–11:20 a.m.
Burnaby
D102 May 6 – Aug 2, 2024: Tue, 10:30–11:20 a.m.
Burnaby
D103 May 6 – Aug 2, 2024: Tue, 10:30–11:20 a.m.
Burnaby
D104 May 6 – Aug 2, 2024: Tue, 11:30 a.m.–12:20 p.m.
Burnaby
D105 May 6 – Aug 2, 2024: Tue, 11:30 a.m.–12:20 p.m.
Burnaby
D106 May 6 – Aug 2, 2024: Tue, 11:30 a.m.–12:20 p.m.
Burnaby
D200 Weiming Liu
May 6 – Aug 2, 2024: Thu, 8:30–10:20 a.m.
Surrey
D201 May 6 – Aug 2, 2024: Thu, 10:30–11:20 a.m.
Surrey
D202 May 6 – Aug 2, 2024: Thu, 10:30–11:20 a.m.
Surrey
D203 May 6 – Aug 2, 2024: Thu, 11:30 a.m.–12:20 p.m.
Surrey
D204 May 6 – Aug 2, 2024: Thu, 11:30 a.m.–12:20 p.m.
Surrey
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 Gregory Baker
May 6 – Aug 2, 2024: Mon, Wed, Fri, 10:30–11:20 a.m.
Burnaby
ECON 103 - Principles of Microeconomics (4)

The principal elements of theory concerning utility and value, price and costs, factor analysis, productivity, labor organization, competition and monopoly, and the theory of the firm. Students with credit for ECON 200 cannot take ECON 103 for further credit. Quantitative/Breadth-Soc.

Section Instructor Day/Time Location
D100 Gulriz Barkin
May 6 – Aug 2, 2024: Tue, 2:30–5:20 p.m.
Burnaby
D101 May 6 – Aug 2, 2024: Fri, 9:30–10:20 a.m.
Burnaby
D102 May 6 – Aug 2, 2024: Fri, 10:30–11:20 a.m.
Burnaby
D103 May 6 – Aug 2, 2024: Fri, 11:30 a.m.–12:20 p.m.
Burnaby
D104 May 6 – Aug 2, 2024: Fri, 12:30–1:20 p.m.
Burnaby
D105 May 6 – Aug 2, 2024: Fri, 1:30–2:20 p.m.
Burnaby
D106 May 6 – Aug 2, 2024: Thu, 12:30–1:20 p.m.
Burnaby
D107 May 6 – Aug 2, 2024: Thu, 1:30–2:20 p.m.
Burnaby
D108 May 6 – Aug 2, 2024: Thu, 2:30–3:20 p.m.
Burnaby
D110 May 6 – Aug 2, 2024: Thu, 9:30–10:20 a.m.
Burnaby
ECON 105 - Principles of Macroeconomics (4)

The principal elements of theory concerning money and income, distribution, social accounts, public finance, international trade, comparative systems, and development and growth. Students with credit for ECON 205 cannot take ECON 105 for further credit. Quantitative/Breadth-Soc.

Section Instructor Day/Time Location
D100 Brian Krauth
May 6 – Aug 2, 2024: Mon, 10:30 a.m.–12:20 p.m.
May 6 – Aug 2, 2024: Wed, 10:30–11:20 a.m.
Burnaby
Burnaby
D101 May 6 – Aug 2, 2024: Tue, 9:30–10:20 a.m.
Burnaby
D102 May 6 – Aug 2, 2024: Tue, 10:30–11:20 a.m.
Burnaby
D103 May 6 – Aug 2, 2024: Tue, 11:30 a.m.–12:20 p.m.
Burnaby
D104 May 6 – Aug 2, 2024: Tue, 12:30–1:20 p.m.
Burnaby
D105 May 6 – Aug 2, 2024: Tue, 3:30–4:20 p.m.
Burnaby
D107 May 6 – Aug 2, 2024: Wed, 9:30–10:20 a.m.
Burnaby
D108 May 6 – Aug 2, 2024: Mon, 2:30–3:20 p.m.
Burnaby
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 Stephen Choi
May 6 – Aug 2, 2024: Mon, Wed, Fri, 8:30–9:20 a.m.
Burnaby
OP01 TBD
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 Paul Tupper
May 6 – Aug 2, 2024: Mon, Wed, Fri, 1:30–2:20 p.m.
Burnaby
D200 Randall Pyke
May 6 – Aug 2, 2024: Mon, Wed, Fri, 9:30–10:20 a.m.
Surrey
OP01 TBD
OP02 TBD
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.

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.

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 Sessional
May 6 – Aug 2, 2024: Wed, 11:30 a.m.–12:20 p.m.
May 6 – Aug 2, 2024: Fri, 10:30 a.m.–12:20 p.m.
Burnaby
Burnaby
OL01 Gamage Perera
Online
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.

and one of

MATH 150 - Calculus I with Review (4)

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

Section Instructor Day/Time Location
D100 Mahsa Faizrahnemoon
May 6 – Aug 2, 2024: Mon, Wed, Fri, 1:30–2:20 p.m.
Burnaby
D101 May 6 – Aug 2, 2024: Tue, 8:30–9:20 a.m.
Burnaby
D102 May 6 – Aug 2, 2024: Tue, 9:30–10:20 a.m.
Burnaby
D103 May 6 – Aug 2, 2024: Tue, 10:30–11:20 a.m.
Burnaby
OP01 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.

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 Justin Chan
May 6 – Aug 2, 2024: Mon, Wed, Fri, 1:30–2:20 p.m.
Surrey
OP01 TBD
MATH 240 - Algebra I: Linear Algebra (3) *

Linear equations, matrices, determinants. Real and abstract vector spaces, subspaces and linear transformations; basis and change of basis. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. Applications. Subject is presented with an abstract emphasis and includes proofs of the basic theorems. Prerequisite: MATH 150 or 151 or MACM 101, 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 Imin Chen
May 6 – Aug 2, 2024: Mon, Wed, Fri, 11:30 a.m.–12:20 p.m.
Burnaby
D101 May 6 – Aug 2, 2024: Thu, 9:30–10:20 a.m.
Burnaby
D102 May 6 – Aug 2, 2024: Thu, 2:30–3:20 p.m.
Burnaby
D103 May 6 – Aug 2, 2024: Thu, 3:30–4:20 p.m.
Burnaby

and two ENGL or PHIL courses.

* Recommended

Upper Division Requirements

Students complete the following courses

all of

ACMA 301 - Long-Term Actuarial Mathematics I (3)

Life tables, basic survival models. Basic life insurance and annuities: present value random variables, premium calculations, reserves. Computer applications for pricing and reserving for life insurance portfolios. Covers part of the syllabus for Exam LTAM of the Society of Actuaries. Prerequisite: ACMA 201 (or 210), with a minimum grade of C. Corequisite: STAT 285. Students with credit for ACMA 320 cannot take ACMA 301 for further credit. Quantitative.

ACMA 340 - Financial Economics for Actuaries (3)

Option pricing models and their application to insurance and financial risks. Introduction to finance and derivatives. Option strategies and risk management. Binomial models. Black-Scholes-Merton model. Market-making, hedging, and option Greeks. Introduction to exotic options. Mean-variance portfolio theory and asset pricing models. Covers part of the syllabus for Exam 3F of the Casualty Actuarial Society. Prerequisite: ACMA 201 (or 210), with a minimum grade of C. Corequisite: STAT 285. Quantitative.

ACMA 355 - Loss Models I (3)

Severity models. Risk measures. Frequency models. Frequency and severity with coverage modifications: deductibles, policy limits, coinsurance. Parametric estimation: method of moments, MLE. Bayesian estimation. Model selection. Covers part of the syllabus for Exam STAM of the Society of Actuaries. Corequisite: STAT 330. Quantitative.

ACMA 401 - Long-Term Actuarial Mathematics II (3)

Advanced survival models. Multiple state models. Advanced premium calculations and reserves. Profit testing. Pension plans and retirement benefits. Computer applications for pricing, reserving and risk measurement of life insurance portfolios. Covers part of the syllabus for Exam LTAM of the Society of Actuaries. Prerequisite: ACMA 301 (or 320), with a minimum grade of C. Students with credit for ACMA 425 cannot take ACMA 401 for further credit. Quantitative.

ACMA 455 - Loss Models II (3)

Aggregate loss models. Credibility: models and estimation. Insurance and reinsurance coverages. Pricing and reserving for short-term insurance coverages. Covers part of the syllabus for Exam STAM of the Society of Actuaries. Prerequisite: ACMA 355 with a minimum grade of C. Quantitative.

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.

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.

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.

and one of

ACMA 465 - Demography and Mortality Models (3)

Measures of mortality and fertility: Crude rates, age-specific mortality rates, adjusted measures of mortality. Construction of life tables from census data. Stationary population theory: survivorship group, Lexis diagram. Stable population theory: Sharpe-Lotka theorem, growth rate, quasi-stable populations. Mortality models. Longevity risk. Prerequisite: ACMA 301 (or 320), with a minimum grade of C. Quantitative.

ACMA 470 - Property and Casualty Insurance (3)

Ratemaking: terminology, process, trend, ultimate losses, expense provisions, profit and contingencies, overall rate indications, classification rates, increased limits. Individual risk rating: prospective systems, retrospective rating, design. Loss Reserving: accounting concepts, definitions, principles, loss reserving process. Risk classification: relationship to other mechanisms, criteria for selecting rating variables, examples, efficiency, estimating class relativities. Covers part of the syllabus for Exam 5 of Casualty Actuarial Society. Quantitative.

ACMA 475 - Theory of Pension (3)

Overview of pension plans: design, funding, regulation, accounting standards. Pension funding methods: actuarial cost methods, terminal funding method. Individual actuarial cost methods: accrual benefit cost method, entry-age actuarial cost method, unit-credit method, individual-level-premium method, attainted-age-normal method. Group actuarial cost methods. Prerequisite: ACMA 301 (or 320), with a minimum grade of C. Corequisite: ACMA 401. Quantitative.

and three of

ACMA 360W - Actuarial Communication (3)

Guided experiences in written and oral communication of actuarial ideas and results to both expert and lay audiences. Prerequisite: ACMA 301 (or 320), with a minimum grade of C. Students who have taken STAT 300W first may not then take this course for further credit. Writing/Quantitative.

ACMA 395 - Special Topics in Actuarial Science (3)

Topics in areas of actuarial science not covered in the regular curriculum of the department. Prerequisite: Dependent on the topics covered.

ACMA 490 - Selected Topics in Actuarial Science (3)

The topics included in this course will vary from term to term depending on faculty availability and student interest. Prerequisite: Dependent on the topic covered.

BUS 312 - Introduction to Finance (3)

Role and function of financial managers, financial analysis, compound interest valuation and capital budgeting, management of current assets, introduction to financial instruments and institutions. Prerequisite: BUS 254 (or 324) with a minimum grade of C-; 45 units. Recommended: BUS 207, ECON 201, or ECON 301. Quantitative.

Section Instructor Day/Time Location
D100 Tara Immell
May 6 – Aug 2, 2024: Wed, 9:30 a.m.–12:20 p.m.
Burnaby
D200 Tara Immell
May 6 – Aug 2, 2024: Wed, 2:30–5:20 p.m.
Surrey
BUS 315 - Investments (3)

Investments from an individual and institutional point of view. Topics include: bond valuation and the term structure of interest rates, stock valuation, portfolio theory, asset pricing models, efficient markets and portfolio performance evaluation. Prerequisite: BUS 312, BUS 336 and BUS 207 or ECON 201 or ECON 301, all with a minimum grade of C-; 45 units. Quantitative.

Section Instructor Day/Time Location
D100 Greta Fesechko
May 6 – Aug 2, 2024: Thu, 2:30–5:20 p.m.
Burnaby
E100 Greta Fesechko
May 6 – Aug 2, 2024: Thu, 6:30–9:20 p.m.
Burnaby
ECON 302 - Microeconomic Theory II: Strategic Behavior (4)

Aspects of microeconomic theory concerned with strategic behavior, imperfect information, and market failure. Topics include game theory and oligopoly; uncertainty and insurance; asymmetric information and market power, externalities and public goods, together with related issues in welfare economics. Prerequisite: ECON 201 with a minimum grade of C-; 60 units. Quantitative.

Section Instructor Day/Time Location
D100 Gulriz Barkin
May 6 – Aug 2, 2024: Tue, 8:30–11:20 a.m.
Burnaby
D101 May 6 – Aug 2, 2024: Wed, 8:30–9:20 a.m.
Burnaby
D102 May 6 – Aug 2, 2024: Wed, 9:30–10:20 a.m.
Burnaby
D103 May 6 – Aug 2, 2024: Wed, 10:30–11:20 a.m.
Burnaby
D104 May 6 – Aug 2, 2024: Wed, 11:30 a.m.–12:20 p.m.
Burnaby
D105 May 6 – Aug 2, 2024: Thu, 12:30–1:20 p.m.
Burnaby
D106 May 6 – Aug 2, 2024: Thu, 1:30–2:20 p.m.
Burnaby
D107 May 6 – Aug 2, 2024: Thu, 2:30–3:20 p.m.
Burnaby
ECON 305 - Intermediate Macroeconomic Theory (4)

Concepts and methods of analysis of macroeconomic variables -- consumption, investment, government and foreign trade. Classical and Keynesian models compared; analysis of economic statics and dynamics. Prerequisite: ECON 201 with a minimum grade of C-; 60 units. Students with a minimum grade of A- in ECON 103 and 105 at Simon Fraser University at their first attempt can complete ECON 305 concurrently with ECON 201 after 30 units. Students seeking permission to enroll on this basis must contact the undergraduate advisor in economics. Quantitative.

Section Instructor Day/Time Location
D100 Yan Yan
May 6 – Aug 2, 2024: Fri, 9:30 a.m.–12:20 p.m.
Burnaby
D102 May 6 – Aug 2, 2024: Wed, 9:30–10:20 a.m.
Burnaby
D103 May 6 – Aug 2, 2024: Wed, 10:30–11:20 a.m.
Burnaby
D106 May 6 – Aug 2, 2024: Thu, 12:30–1:20 p.m.
Burnaby
MACM 316 - Numerical Analysis I (3)

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

Section Instructor Day/Time Location
D100 May 6 – Aug 2, 2024: Mon, Wed, Fri, 10:30–11:20 a.m.
Burnaby
D101 May 6 – Aug 2, 2024: Wed, 2:30–3:20 p.m.
Burnaby
D102 May 6 – Aug 2, 2024: Wed, 3:30–4:20 p.m.
Burnaby
D103 May 6 – Aug 2, 2024: Wed, 4:30–5:20 p.m.
Burnaby
D104 May 6 – Aug 2, 2024: Thu, 9:30–10:20 a.m.
Burnaby
D105 May 6 – Aug 2, 2024: Thu, 10:30–11:20 a.m.
Burnaby
D106 May 6 – Aug 2, 2024: Thu, 11:30 a.m.–12:20 p.m.
Burnaby
D107 May 6 – Aug 2, 2024: Wed, 4:30–5:20 p.m.
Burnaby
D108 May 6 – Aug 2, 2024: Wed, 2:30–3:20 p.m.
Burnaby
D109 May 6 – Aug 2, 2024: Wed, 5:30–6:20 p.m.
Burnaby
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.

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.

STAT 360 - Advanced R for Data Science (2)

Advanced R programming methods for data science. Tools for reproducible research. Version control. Data structures, subsetting, functions, environments, and debugging. Functional programming. Code performance: profiling, memory, integrating R and C++. Prerequisite: One of STAT 260 or STAT 341 and one of STAT 302, STAT 305, STAT 350, or ECON 333, all with a minimum grade of C-. CMPT 125 or CMPT 129 is also recommended. Corequisite: STAT 361.

STAT 380 - Introduction to Stochastic Processes (3)

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

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 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.

STAT 460 - Bayesian Statistics (3)

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

Certain elective courses are pre-approved courses for Validation by Educational Experience (VEE) units from the Society of Actuaries. Information is available here.

University Degree Requirements

Students must also satisfy University degree requirements for degree completion.

Writing, Quantitative, and Breadth Requirements

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

WQB Graduation Requirements

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

Requirement

Units

Notes
W - Writing

6

Must include at least one upper division course, taken at Simon Fraser University within the student's major subject; two courses (minimum three units each)

Q - Quantitative

6

Q courses may be lower or upper division; two courses (total six units or more)
B - Breadth

18

Designated Breadth

Must be outside the student's major subject, and may be lower or upper division:

Two courses (total six units or more) Social Sciences: B-Soc
Two courses (total six units or more) Humanities: B-Hum
Two courses (total six units or more) Sciences: B-Sci

6

Additional Breadth

Two courses (total six units or more) 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.