Please note:

To view the Spring 2019 Academic Calendar go to www.sfu.ca/students/calendar/2019/spring.html

Statistics and Actuarial Science Simon Fraser University Calendar | Summer 2019

Statistics Honours

Bachelor of Science

The department offers a bachelor of science (BSc) honours program in statistics within the Faculty of Science.

The program maintains a committee of advisors whose office hours are available at the general office and at www.stat.sfu.ca/teaching/advising.html. Students should seek advice early in their academic careers about program planning from the department's advisors.

Admission Requirements

Students may be admitted 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 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 course.

GPA Required for Continuation

To continue in the program, students must maintain at least a 3.00 grade point average (GPA) in MATH, STAT, MACM and ACMA courses (excluding ACMA 210 if doing so results in a higher GPA).

Graduation Grade Point Averages

See required GPA for graduation from the Statistics honours program.

Credit for Statistics Courses

There are three kinds of STAT 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/default/files/imce/pdf/accreditation-course-list-simon-fraser.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 132 units, including the lower division, upper division, and additional upper division requirements specified below.

Lower Division Requirements

Students complete the following courses:

One of*

CMPT 102 - Introduction to Scientific Computer Programming (3)

A programming course which will provide the science student with a working knowledge of a scientific programming language and an introduction to computing concepts, structured programming, and modular design. The student will also gain knowledge in the use of programming environments including the use of numerical algorithm packages. Corequisite: MATH 152 or 155 (or 158). Students with credit for CMPT 120, 128, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129 or 135 first may not then take this course for further credit. Quantitative.

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

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

Section Instructor Day/Time Location
D100 Anne Lavergne
Mo, We, Fr 9:30 AM – 10:20 AM
AQ 3181, Burnaby
D101 Anne Lavergne
We 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D102 Anne Lavergne
We 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D103 Anne Lavergne
We 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D104 Anne Lavergne
We 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D105 Anne Lavergne
We 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D106 Anne Lavergne
We 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D107 Anne Lavergne
We 1:30 PM – 2:20 PM
ASB 9838, Burnaby
D108 Anne Lavergne
We 1:30 PM – 2:20 PM
ASB 9838, Burnaby

and one of*

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: fundamental algorithms; elements of empirical and theoretical algorithmics; abstract data types and elementary data structures; basic object-oriented 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 9:30 AM – 10:20 AM
AQ 3182, Burnaby
CMPT 129 - Introduction to Computing Science and Programming for Mathematics and Statistics (3)

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

and one of

MATH 150 - Calculus I with Review (4)

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

Section Instructor Day/Time Location
C100 Distance Education
D100 Randall Pyke
Mo 1:30 PM – 2:20 PM
Tu, We, Fr 1:30 PM – 2:20 PM
EDB 7618, Burnaby
AQ 3005, 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.

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

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

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 Randall Pyke
Mo, We, Fr 11:30 AM – 12:20 PM
RCB IMAGTH, Burnaby
OP01
TBD

and one of

MATH 152 - Calculus II (3)

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

Section Instructor Day/Time Location
D100 Vijay Singh
Mo, We, Fr 8:30 AM – 9:20 AM
SSCB 9200, Burnaby
OP01
TBD
MATH 155 - Calculus II for the Biological Sciences (3)

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

Section Instructor Day/Time Location
D100 Mahdieh Malekian
Mo, We, Fr 8:30 AM – 9:20 AM
AQ 3181, Burnaby
OPO1
TBD
MATH 158 - Calculus II for the Social Sciences (3)

Designed for students specializing in business or the social sciences. Topics include: theory of integration, integration techniques, applications of integration; functions of several variables with emphasis on double and triple integrals and their applications; introduction to differential equations with emphasis on some special first-order equations and their applications; 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.

and

STAT 180 - Career Development Seminar for Statistics and Actuarial Science (1)

A seminar primarily for students undertaking a major or an honours program in Statistics. Visiting speakers share experience relevant to Statistics students and provide useful education and career advice. Prerequisite: Enrollment, or intended enrollment, in the Statistics or Actuarial Science major or honours programs, or STAT 270, or permission of the instructor. Students with credit for MSSC 180 or DATA 180 may not take this course for further credit.

and one of

MATH 232 - Applied Linear Algebra (3)

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

Section Instructor Day/Time Location
D100 Randall Pyke
Mo, We, Fr 2:30 PM – 3:20 PM
SUR 2600, 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; 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 Ralf Wittenberg
Mo, Fr 11:30 AM – 12:20 PM
We 11:30 AM – 12:20 PM
SWH 10041, Burnaby
WMC 3260, Burnaby
OPO1
TBD

and all of

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; 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; 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 Ralf Wittenberg
Mo, We, Fr 1:30 PM – 2:20 PM
SSCC 9001, Burnaby
OP01
TBD
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: Any STAT course (except STAT 100) or BUEC 232, and one of CMPT 102, CMPT 120, CMPT 125, CMPT 128, CMPT 129, CMPT 130, or permission of the instructor. 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. 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 Tim Swartz
We 11:30 AM – 12:20 PM
Fr 10:30 AM – 12:20 PM
AQ 3182, Burnaby
AQ 3182, Burnaby
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. Quantitative.

* Students are strongly encouraged to complete this requirement in their first year.

** Recommended. Students with prior computing experience may be able to challenge CMPT 120.

*** CMPT 127 is a corequisite.

**** Recommended.

Upper Division Requirements

Students complete all of

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. Quantitative.

MATH 322 - Complex Variables (3)

Functions of a complex variable, differentiability, contour integrals, Cauchy's theorem, Taylor and Laurent expansions, method of residues. Prerequisite: MATH 251. Students with credit for MATH 424 may not take this course for further credit. 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. Quantitative.

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

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

STAT 342 - Introduction to Statistical Computing and Exploratory Data Analysis - SAS (2)

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

STAT 350 - Linear Models in Applied Statistics (3)

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

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. Quantitative.

STAT 410 - Statistical Analysis of Sample Surveys (3)

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

STAT 430 - Statistical Design and Analysis of Experiments (3)

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

STAT 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. Quantitative.

STAT 460 - Bayesian Statistics (3)

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

STAT 475 - Applied Discrete Data Analysis (3)

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

and 9 units in additional upper division ACMA, MACM, MATH or STAT courses (excluding STAT 302, 305, 403). The following are recommended.

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 Benjamin Adcock
Mo, We, Fr 10:30 AM – 11:20 AM
RCB IMAGTH, Burnaby
D101
Mo 2:30 PM – 3:20 PM
WMC 2830, Burnaby
D102
Mo 3:30 PM – 4:20 PM
WMC 2830, Burnaby
D103
Tu 10:30 AM – 11:20 AM
WMC 2830, Burnaby
D104
Tu 11:30 AM – 12:20 PM
WMC 2830, Burnaby
D105
Tu 9:30 AM – 10:20 AM
WMC 2830, Burnaby
D106
Tu 1:30 PM – 2:20 PM
WMC 2830, Burnaby
D107
Mo 4:30 PM – 5:20 PM
WMC 2830, Burnaby
D108
Mo 5:30 PM – 6:20 PM
WMC 2830, Burnaby
D109
Mo 11:30 AM – 12:20 PM
WMC 2830, Burnaby
STAT 300W - Statistics Communication (3)

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. 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 Michael Davis
Tu 10:30 AM – 11:20 AM
Th 9:30 AM – 11:20 AM
RCB 6125, Burnaby
WMC 2503, Burnaby
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 and one of STAT 341 or CMPT 225, 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 BUEC 333 or equivalent. 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 BUEC 333 or equivalent. 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 BUEC 333 or equivalent. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.

STAT 490 - Selected Topics in Probability and Statistics (3)

Topics in areas of probability and statistics not covered in the regular undergraduate curriculum of the department. Prerequisite: Dependent on the topic covered.

STAT 495 - Directed Studies in Probability and Statistics (3)

Independent reading or research on consultation with the supervising instructor. This course can be repeated for credit. Prerequisite: Written permission of the department undergraduate studies committee.

Additional Upper Division Requirements

Students must complete 17 additional upper division units to satisfy university requirements. Any upper division courses other than STAT 302, STAT 305, or STAT 403 may be used to complete these units.

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.