Master of Science in Statistics (MSc)
Established in 1983, the Department of Statistics at UBC is internationally renowned for its excellence in research and the high calibre of its faculty members. Our programs offers students different options for pursuing their interests and professional goals. We currently have programs at both the Masters and PhD levels. At the MSc level we offer a MSc in Statistics and a MSc in Statistics with a Biostatistics option (in collaboration with the School of Population and Public Health). Students can choose to do a thesis, a final project or an 8-month full-time Co-op placement (internship) outside the Department.
With appropriately selected courses during their MSc program, our students can prepare themselves for a successful career in biostatistics, bioinformatics / genomics, data mining, statistical computing, among others.
What makes the program unique?
The Department is renowned in Canada for its research excellence and its leadership in the research community. Students are engaged through both courses and research, and develop a strong set of skills, both applied and theoretical. The Department has always valued data driven research, consulting and collaboration, and has long held communication and computing skills as crucial for success. These values are apparent not only in individual faculty’s research programs but also in our undergraduate and graduate curriculum.
Graduate students participate actively in our research, teaching and consulting activities, and enjoy a wide variety of opportunities for interaction with other researchers and students on- and off-campus. These opportunities are facilitated by the involvement of our faculty members in various collaborative and interdisciplinary research projects. In addition, our graduate students run their own statistical consulting service, which provides them with professional (paid) experience even before they finish their program.
We require a statement of interest, as well as a CV.
TOEFL (ibT) Overall Score Requirement
IELTS Overall Score Requirement
Supervisor commitment required prior to application?
Prerequisites / Course Requirements
The department's Admissions Committee has outlined the following requirements, along with other desired courses and skills. Note that meeting the minimum requirements does not guarantee admission. Note also that an applicant missing a course or two but with other strong attributes, such as work experience as a statistician, will be seriously considered.
required: calculus (differentiation, integration, multivariable calculus) as obtained in UBC MATH 100, 200, 253
required: linear algebra, as obtained in UBC MATH 221
In addition, the student should have some ability in constructing proofs, for instance concerning continuity and limits, such as acquired in UBC MATH 200.
required: an intoductory course including axioms of probability, various common distributions, multivariate distributions and some limit theorems, as obtained through UBC MATH/STAT 302 or via the text Introduction to Probability and Its Applications, 2nd edition, by R.L. Scheaffer.
recommended but not required: stochastic processes, as obtained through UBC MATH 303
required: familiarity with R
recommended but not required: experience in coding such as C/C+ or Python
required: an introductory course in statistical methods, such as UBC STAT 200 or via the text Statistics Data and Models, Pearson Canada, 2015, by De Veaux Velleman and Bock
required: a course in statistical inference/mathematical statistics: theory of estimation and hypothesis testing, such as UBC STAT 305 or via the text Mathematical Statistics and Data Analysis, Wadsworth & Brooks/Cole, 1988, by John Rice
required: either a course in regression analysis or a course in the design of experiments/ANOVA. The regression course should cover the material in UBC STAT 306, with text Applied Linear Regression, Wiley, by S. Weisberg. The design/ANOVA course should cover the material in UBC STAT 404, with text Design and Analysis of Experiments, Wiley, latest edition, by D. Montgomery.
Deadline to submit online application. No changes can be made to the application after submission.Transcript Deadline
Deadline to upload scans of official transcripts through the applicant portal in support of a submitted application. Information for accessing the applicant portal will be provided after submitting an online application for admission.Referee Deadline
Deadline for the referees identified in the application for admission to submit references. See Letters of Reference for more information.
September 2019 Intake
Application Open Date01 October 2018
September 2020 Intake
Application Open Date07 October 2019
Tuition / Program Costs
|Fees||Canadian Citizen / Permanent Resident / Refugee / Diplomat||International|
|Installments per year||3||3|
|Tuition per installment||$1,632.61||$2,868.22|
|Tuition per year||$4,897.83||$8,604.66|
|Int. Tuition Award (ITA) per year (if eligible)||$3,200.00 (-)|
|Other Fees and Costs|
|Student Fees (yearly)||$930.14 (approx.)|
|Costs of living (yearly)||starting at $16,884.10 (check cost calculator)|
All fees for the year are subject to adjustment and UBC reserves the right to change any fees without notice at any time, including tuition and student fees. In case of a discrepancy between this webpage and the UBC Calendar, the UBC Calendar entry will be held to be correct.
Completion Rates & Times
This list shows faculty members with full supervisory privileges who are affiliated with this program. It is not a comprehensive list of all potential supervisors as faculty from other programs or faculty members without full supervisory privileges can request approvals to supervise graduate students in this program.
Bouchard-Cote, Alexandre (machine/statistical learning; mathematical side of the subject as well as in applications in linguistics and biology)
Brant, Rollin (Child health research)
Chen, Jiahua (finite mixture model, empirical likelihood, asymptotic theory, sample survey)
Cohen Freue, Gabriela (statistical genomics (focus in proteomics), robust estimation and inference, linear models with endogeneity )
Gustafson, Paul (Bayesian statistical methods, Causal inference, Evidence synthesis, Biostatistics and Epidemiology, Partial Identification)
Heckman, Nancy (functional data analysis, smoothing, splines)
Joe, Harry Sue Wah (dependence modelling, copula construction, non-normal time series, extreme value inference, parsimonous high-dimensional dependence )
Mostafavi, Sara (machine/statistical learning applied to disease genetics )
Nolde, Natalia (Multivariate extreme value theory, Risk assessment, Applications in finance, insurance, geosciences)
Petkau, A John (Development and application of statistical methodology for clinical trials of therapies in multiple sclerosis )
Salibian-Barrera, Matias (S-regression estimationg, robust statistics, functional principal component analysis, bootstrap estimators, rgam, clustering algorithm)
Welch, William (, Design of experiments, experiments with computer models, data mining, drug discovery, quality improvement)
Wu, Lang (Biostatistics)
Zamar, Ruben (Data mining and text mining, Modeling data quality, Development of new robust procedures, Statistical computing, Bioinformatics)