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Statistics Major
The department offers a bachelor of science (BSc) program in statistics within the Faculty of Science.
The program maintains a committee of advisors whose office hours are available at www.stat.sfu.ca/teaching/advising.html. Students should seek program planning advice early in their academic careers.
Admission Requirements
Students may be admitted by direct entry on their university application, or by application to the Department of Statistics, after they have been admitted.
Visit http://www.stat.sfu.ca/undergrad/undergrad_admission/undergrad_admission_stat.html 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 that is a prerequisite for a course that the student has already completed with a grade of C or higher without permission of the department.
Computing Recommendation
Experience with a high level programming language is recommended by the start of the second year.
Prerequisite Grade Requirement
Students must have a grade of C or better in prerequisites for STAT courses offered by the Department of Statistics and Actuarial Science.
GPA Required for Continuation
To continue in the program, students must maintain at least a 2.25 grade point average in MATH, STAT, MACM and ACMA courses (excluding ACMA 210 if doing so results in a higher GPA).
Graduation Grade Point Averages
Credit for Statistics Courses
There are three kinds of courses:
 Introductory course (STAT 100)
 Service courses (STAT 101, 201, 203, 302, 305, 403)
 Mainstream courses (STAT 240, 270, 285, 300W, 330, 341, 342, 350, 380, 410, 430, 440, 445, 450, 452, 460, 475, 485)
Accreditation of Courses
The Statistical Society of Canada has accredited certain courses within the department for partial fulfillment of the educational requirements for the associate statistician (AStat) designation. The list of accredited courses is available at https://ssc.ca/sites/ssc/files/data/Accredited/CoursesSFUsummary20150106.pdf. Please contact the department for details. Further information on the professional statistician (PStat) and associate statistician (AStat) designations is available at https://www.ssc.ca/en/accreditation.
Program Requirements
Students complete 120 units, including the lower division, upper division, and minor requirements specified below.
Lower Division Requirements
Students complete the following courses:
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 highlevel language and be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode, data types and control structures, fundamental algorithms, computability and complexity, computer architecture, and history of computing science. Treatment is informal and programming is presented as a problemsolving 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/BreadthScience.
Section  Instructor  Day/Time  Location 

D100 
Angelica Lim 
Mo, Fr 9:30 AM – 10:20 AM We 9:30 AM – 10:20 AM 
AQ 3181, Burnaby AQ 3182, Burnaby 
D101 
Angelica Lim 
Th 9:30 AM – 10:20 AM 
ASB 9838, Burnaby 
D102 
Angelica Lim 
Th 10:30 AM – 11:20 AM 
ASB 9838, Burnaby 
D103 
Angelica Lim 
Th 11:30 AM – 12:20 PM 
ASB 9838, Burnaby 
D104 
Angelica Lim 
Th 12:30 PM – 1:20 PM 
ASB 9838, Burnaby 
D105 
Angelica Lim 
Th 1:30 PM – 2:20 PM 
ASB 9838, Burnaby 
D106 
Angelica Lim 
Th 2:30 PM – 3:20 PM 
ASB 9838, Burnaby 
D107 
Angelica Lim 
Th 3:30 PM – 4:20 PM 
ASB 9838, Burnaby 
D108 
Angelica Lim 
Th 3:30 PM – 4:20 PM 
ASB 9838, Burnaby 
and one of*
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: fundamental algorithms; elements of empirical and theoretical algorithmics; abstract data types and elementary data structures; basic objectoriented programming and software design; computation and computability; specification and program correctness; and history of computing science. Prerequisite: CMPT 120. Corequisite: CMPT 127. Students with credit for CMPT 126, 129, 135 or CMPT 200 or higher may not take for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Bobby Chan 
Mo, We, Fr 2:30 PM – 3:20 PM 
AQ 3182, Burnaby 
A rigorous introduction to computing science and computer programming, suitable for students who already have substantial programming background. Topics include: fundamental algorithms and problem solving; abstract data types and elementary data structures; basic objectoriented programming and software design; elements of empirical and theoretical algorithmics; computation and computability; specification and program correctness; and history of computing science. Prerequisite: CMPT 120. Students with credit for CMPT 125, 128, 130, 135 or higher may not take CMPT 126 for further credit. Quantitative/BreadthScience.
A second course in computing science and programming intended for students studying mathematics, statistics or actuarial science and suitable for students who already have some background in computing science and programming. Topics include: a review of the basic elements of programming: use and implementation of elementary data structures and algorithms; fundamental algorithms and problem solving; basic objectoriented programming and software design; computation and computabiiity and specification and program correctness. Prerequisite: CMPT 102 or CMPT 120. Students with credit for CMPT 125 or 135 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Brad Bart 
Mo, We 1:30 PM – 2:20 PM Fr 1:30 PM – 2:20 PM 
WMC 3260, Burnaby WMC 3210, Burnaby 
D101 
Brad Bart 
Th 12:30 PM – 1:20 PM 
ASB 9838, Burnaby 
D102 
Brad Bart 
Th 1:30 PM – 2:20 PM 
ASB 9838, Burnaby 
D103 
Brad Bart 
Th 2:30 PM – 3:20 PM 
ASB 9838, Burnaby 
D104 
Brad Bart 
Th 3:30 PM – 4:20 PM 
ASB 9838, Burnaby 
and one of
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: PreCalculus 12 (or equivalent) with a grade of at least B+, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 151, 154 or 157 may not take MATH 150 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

C100  Distance Education  
D100 
Yusuf Tuncer 
Mo, Tu, We, Fr 8:30 AM – 9:20 AM 
WMC 3520, Burnaby 
D200 
Justine Gauthier 
Mo, We, Fr 11:30 AM – 12:20 PM We 1:30 PM – 2:20 PM 
SUR 2750, Surrey SUR 2750, Surrey 
OP01 

TBD  
OP02 

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

D100 
Ladislav Stacho 
Mo 8:30 AM – 9:20 AM We, Fr 8:30 AM – 9:20 AM 
SSCB 9200, Burnaby SSCB 9200, Burnaby 
OP01 

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

D100 
Luis Goddyn 
Mo, Fr 11:30 AM – 12:20 PM We 11:30 AM – 12:20 PM 
SWH 10081, Burnaby DFA 300, Burnaby 
D200 
Natalia Kouzniak 
Mo, We, Fr 12:30 PM – 1:20 PM 
SUR 3090, Surrey 
OP01 

TBD  
OP02 

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

D100 
Brenda Davison 
Mo, We, Fr 8:30 AM – 9:20 AM 
SSCC 9001, Burnaby 
D200 
Sepehr Foroushani 
Mo, We, Fr 11:30 AM – 12:20 PM 
SUR 5280, Surrey 
D300 
Jamie Mulholland 
Mo, We, Fr 8:30 AM – 9:20 AM 
WMC 2810, Burnaby 
OP01 

TBD  
OP02 

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

D100 
Petr Lisonek 
Mo, We, Fr 8:30 AM – 9:20 AM 
RCB IMAGTH, Burnaby 
D200 
Natalia Kouzniak 
Mo, We, Fr 9:30 AM – 10:20 AM 
SUR 5280, Surrey 
OP01 

TBD  
OP02 

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

E100 
Michael Monagan 
Mo 4:30 PM – 5:20 PM We 4:30 PM – 6:20 PM 
SSCC 9001, Burnaby SSCC 9001, Burnaby 
OP01 

TBD 
and
A seminar primarily for students undertaking a major or an honors program in Statistics. Visiting speakers share experience relevant to Statistics students and provide useful education and career advice. Prerequisite: Enrollment, or intended enrollment, in either the Statistics or Actuarial Science major or honors, or permission of the instructor. Students with credit for MSSC 180 may not take this course for further credit.
and one of
Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 make not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Cedric Chauve 
Mo, We, Fr 11:30 AM – 12:20 PM 
SSCC 9001, Burnaby 
D200 
Randall Pyke 
Mo, We, Fr 2:30 PM – 3:20 PM 
SUR 3090, Surrey 
OP01 

TBD  
OP02 

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

D100 
Simone Brugiapaglia 
Mo, We, Fr 11:30 AM – 12:20 PM 
BLU 10921, Burnaby 
OP01 

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

E100 
Steven Ruuth 
Mo, We 4:30 PM – 5:50 PM 
WMC 3520, Burnaby 
OP01 

TBD 
Introduction to modern tools and methods for data acquisition, management, and visualization capable of scaling to Big Data. Prerequisite: CMPT 120 and one of STAT 101, STAT 201, STAT 203, or STAT 270, or permission of the instructor. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
David Campbell 
Mo 10:30 AM – 12:20 PM 
AQ 3154, Burnaby 
D101 
David Campbell 
Mo 6:30 PM – 7:20 PM 
AQ 3148.1, Burnaby 
D102 
David Campbell 
Mo 4:30 PM – 5:20 PM 
AQ 3148.1, Burnaby 
D103 
David Campbell 
Mo 5:30 PM – 6:20 PM 
AQ 3148.1, Burnaby 
D104 
David Campbell 
Mo 3:30 PM – 4:20 PM 
AQ 3148.1, Burnaby 
Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158. Students wishing an intuitive appreciation of a broad range of statistical strategies may wish to take STAT 100 first. Quantitative.
Section  Instructor  Day/Time  Location 

C100  Distance Education  
D100 
Boxin Tang 
Mo 9:30 AM – 10:20 AM We, Fr 9:30 AM – 10:20 AM 
SSCB 9201, Burnaby SWH 10081, Burnaby 
D900 
Maryam DehghaniEstarki 
Tu 8:30 AM – 10:20 AM Th 8:30 AM – 9:20 AM 
SUR 3170, Surrey SUR 3170, Surrey 
OP01 

TBD  
OP09 

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

D100 
Liangliang Wang 
Mo 2:30 PM – 4:20 PM We 2:30 PM – 3:20 PM 
BLU 10021, Burnaby BLU 10011, Burnaby 
D101 
Liangliang Wang 
Mo 8:30 AM – 9:20 AM 
AQ 5008, Burnaby 
D102 
Liangliang Wang 
Mo 9:30 AM – 10:20 AM 
AQ 5008, Burnaby 
D104 
Liangliang Wang 
We 12:30 PM – 1:20 PM 
AQ 5007, Burnaby 
* Students are strongly encouraged to complete this requirement in their first year.
** recommended
Upper Division Requirements
Students complete all of
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. Quantitative.
Introduces the R statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. Students with credit for STAT 340 may not take STAT 341 for further credit.
Section  Instructor  Day/Time  Location 

D100 
Brad McNeney 
Th 12:30 PM – 2:20 PM 
EDB 7618, Burnaby 
D101 
Brad McNeney 
Fr 12:30 PM – 1:20 PM 
SECB 1014, Burnaby 
D102 
Brad McNeney 
Fr 1:30 PM – 2:20 PM 
SECB 1014, Burnaby 
D103 
Brad McNeney 
We 12:30 PM – 1:20 PM 
SECB 1014, Burnaby 
D104 
Brad McNeney 
We 1:30 PM – 2:20 PM 
SECB 1014, Burnaby 
Introduces the SAS statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333. Students with credit for STAT 340 may not take STAT 342 for further credit.
Theory and application of linear regression. Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model diagnostics. Introduction to weighted least squares and generalized linear models. Prerequisite: STAT 285, MATH 251, and one of MATH 232 or MATH 240. Quantitative.
Section  Instructor  Day/Time  Location 

E200 
Gamage Perera 
Mo 6:00 PM – 7:50 PM We 5:30 PM – 6:20 PM 
SUR 5140, Surrey SUR 5140, Surrey 
E201 
Gamage Perera 
We 8:30 AM – 9:20 AM 
SUR 2710, Surrey 
E202 
Gamage Perera 
We 9:30 AM – 10:20 AM 
SUR 2710, Surrey 
and 12 units in 400level STAT courses (excluding STAT 403)
and 9 units in additional upper division ACMA, MACM, MATH or STAT courses (excluding STAT 302, 305, 403). The following are recommended.
A presentation of the problems commonly arising in numerical analysis and scientific computing and the basic methods for their solutions. Prerequisite: MATH 152 or 155 or 158, and MATH 232 or 240, and computing experience. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Brenda Davison 
Mo, We, Fr 12:30 PM – 1:20 PM 
AQ 3182, Burnaby 
D101 

We 2:30 PM – 3:20 PM 
AQ 5016, Burnaby 
D102 

We 3:30 PM – 4:20 PM 
AQ 5016, Burnaby 
D103 

We 4:30 PM – 5:20 PM 
AQ 5016, Burnaby 
D104 

Th 9:30 AM – 10:20 AM 
AQ 5018, Burnaby 
D105 

Th 10:30 AM – 11:20 AM 
AQ 5030, Burnaby 
D106 

Th 11:30 AM – 12:20 PM 
RCB 6125, Burnaby 
D107 

We 5:30 PM – 6:20 PM 
AQ 5016, Burnaby 
Guided experiences in written and oral communication of statistical ideas and results with both scientific and lay audiences. Prerequisite: Admission to the major or honours programs in statistics or actuarial science at SFU. STAT 350 or 9 units of upper division STAT/ACMA courses and permission of the instructor; prior completion of a lower division W course. Writing.
Section  Instructor  Day/Time  Location 

D100 
Jack Davis 
Mo 2:30 PM – 4:20 PM We 2:30 PM – 3:20 PM 
AQ 5030, Burnaby RCB 6125, Burnaby 
D200 
Sessional 
Mo 2:30 PM – 4:20 PM We 2:30 PM – 3:20 PM 
AQ 5049, Burnaby AQ 5038, Burnaby 
Review of discrete and continuous probability models and relationships between them. Exploration of conditioning and conditional expectation. Markov chains. Random walks. Continuous time processes. Poisson process. Markov processes. Gaussian processes. Prerequisite: STAT 330, or all of: STAT 285, MATH 208, and MATH 251. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Richard Lockhart 
Mo, We, Fr 9:30 AM – 10:20 AM 
AQ 5016, Burnaby 
D101 
Richard Lockhart 
Fr 10:30 AM – 11:20 AM 
AQ 5009, Burnaby 
D102 
Richard Lockhart 
Fr 11:30 AM – 12:20 PM 
AQ 5009, Burnaby 
An introduction to the major sample survey designs and their mathematical justification. Associated statistical analyses. Prerequisite: STAT 350. Quantitative.
Section  Instructor  Day/Time  Location 

E100 
Jack Davis 
Mo 4:30 PM – 6:20 PM We 4:30 PM – 5:20 PM 
RCB 8100, Burnaby AQ 4150, Burnaby 
E101 
Michael Davis 
We 3:30 PM – 4:20 PM 
AQ 5036, Burnaby 
E102 
Michael Davis 
We 5:30 PM – 6:20 PM 
AQ 5027, Burnaby 
A datafirst discovery of advanced statistical methods. Focus will be on a series of forecasting and prediction competitions, each based on a large realworld dataset. Additionally, practical tools for statistical modeling in realworld environments will be explored. Prerequisite: 90 units including STAT 350 and one of STAT 341 or CMPT 225, or instructor approval. STAT 240 is also recommended.
Introduction to principal components, cluster analysis, and other commonly used multivariate techniques. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Liangliang Wang 
Tu 4:30 PM – 6:20 PM Th 4:30 PM – 5:20 PM 
BLU 9660, Burnaby BLU 9660, Burnaby 
D101 
Liangliang Wang 
Mo 1:30 PM – 2:20 PM 
AQ 4140, Burnaby 
D102 
Liangliang Wang 
Mo 2:30 PM – 3:20 PM 
AQ 5050, Burnaby 
D103 
Liangliang Wang 
Mo 3:30 PM – 4:20 PM 
AQ 5050, Burnaby 
D104 
Liangliang Wang 
We 1:30 PM – 2:20 PM 
AQ 5036, Burnaby 
D105 
Liangliang Wang 
We 2:30 PM – 3:20 PM 
AQ 5050, Burnaby 
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. Quantitative.
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 equivalent. Quantitative.
Introduction to standard methodology for analyzing categorical data including chisquared tests for two and multiway contingency tables, logistic regression, and loglinear (Poisson) regression. Prerequisite: STAT 302 or STAT 305 or STAT 350 or BUEC 333 or equivalent. Students with credit for the former STAT 402 or 602 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Joan Hu 
Tu 10:30 AM – 11:20 AM Th 9:30 AM – 11:20 AM 
AQ 3005, Burnaby AQ 3005, Burnaby 
D101 
Joan Hu 
We 9:30 AM – 10:20 AM 
AQ 4125, Burnaby 
D102 
Joan Hu 
We 3:30 PM – 4:20 PM 
AQ 5028, Burnaby 
D103 
Joan Hu 
We 4:30 PM – 5:20 PM 
AQ 5038, Burnaby 
D104 
Joan Hu 
We 5:30 PM – 6:20 PM 
AQ 5015, Burnaby 
Introduction to linear time series analysis including moving average, autoregressive and ARIMA models, estimation, data analysis, forecasting errors and confidence intervals, conditional and unconditional models, and seasonal models. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.
Topics in areas of probability and statistics not covered in the regular undergraduate curriculum of the department. Prerequisite: Dependent on the topic covered.
Independent reading or research on consultation with the supervising instructor. Prerequisite: Written permission of the department undergraduate studies committee.
* STAT 450 and at least one of STAT 410 or 430 are recommended for students who wish to seek accreditation with the Statistical Society of Canada.
Minor Program Requirement
Students must complete a minor in a discipline other than statistics or 12 upper division units outside of MATH, MACM, or STAT courses.
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 universitywide 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: BSoc 6 units Humanities: BHum 6 units Sciences: BSci 
6 
Additional Breadth  6 units outside the student’s major subject (may or may not be Bdesignated 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.