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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. Students completing our PhD program will be well-prepared for a job in industry, government or academia. During their program our students develop important professional skills that include: effective communication skills for both technical and non-technical audiences, creativity and originality, and grant writing skills, among others. They also acquire a broad knowledge of modern statistical methods, including computing and data management.
NEW PhD Track Admission Stream!. More information can be found here https://www.stat.ubc.ca/new-phd-track-admission-stream.
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. 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. 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 have recently introduced a highly innovative qualifying process – instead of writing an exam, first year PhD students register in a reading and research course where they work on research papers proposed by individual faculty members.
We also just recently introduced a new PhD Track stream. Effective now, we offer this stream for strong undergraduate students expecting to graduate in Spring 2025 interested in a PhD in Statistics. Admission under this new stream is in a MSc program but with guaranteed transition to PhD at the end of year one subject to satisfying program requirements. This track is intended for exceptional undergraduate students with demonstrated research potential. Students interested in the PhD track should identify one or more faculty members as potential research supervisors. You can find more information about this on our admissions page here https://www.stat.ubc.ca/graduate-admissions.
The Faculty of Graduate and Postdoctoral Studies establishes the minimum admission requirements common to all applicants, usually a minimum overall average in the B+ range (76% at UBC). The graduate program that you are applying to may have additional requirements. Please review the specific requirements for applicants with credentials from institutions in:
Each program may set higher academic minimum requirements. Please review the program website carefully to understand the program requirements. Meeting the minimum requirements does not guarantee admission as it is a competitive process.
Applicants from a university outside Canada in which English is not the primary language of instruction must provide results of an English language proficiency examination as part of their application. Tests must have been taken within the last 24 months at the time of submission of your application.
Minimum requirements for the two most common English language proficiency tests to apply to this program are listed below:
Overall score requirement: 100
Reading
22
Writing
21
Speaking
21
Listening
22
Overall score requirement: 7.5
Reading
6.5
Writing
6.5
Speaking
6.5
Listening
6.5
Some programs require additional test scores such as the Graduate Record Examination (GRE) or the Graduate Management Test (GMAT). The requirements for this program are:
The GRE is not required.
Successful PhD applicants typically have an MSc in Statistics or an MSc or PhD in Mathematics with strong evidence of interest in statistics. A student with only a Bachelors degree cannot usually be admitted to our PhD program, but rather must first enter the MSc program, either first completing the MSc or applying for transfer to the PhD after one year. If you have only had a few courses in statistics, your application to the PhD program will not be successful. For admission to the PhD program, the Admissions committee requires the following, in addition to the requirements for admission to the MSc program. a course in advanced statistical inference courses in rigorous mathematics at least 3 of the following courses at the graduate level: stochastic processes, advanced probability, mathematical statistics, linear models The above requirements are in addition to the minimum admission requirements of the Faculty of Graduate and Postdoctoral Studies. Please note that meeting our admission requirements does not guarantee admission. The following background will strengthen the application. courses in real analysis, and possibly measure theory, advanced probability (limit theorems, sigma fields); a broad range of courses in statistical methods (e.g., some topics among statistical computing, Bayesian statistics, generalized linear models, time series, multivariate statistics); undergraduate or graduate computer science courses; research or work experience relevant to statistics; solid programming experience (e.g., C, C++, Fortran, Python, R, SAS, Matlab).
We require a 2 page (maximum) statement of interest/research proposal, as well as a CV.
All applicants have to submit transcripts from all past post-secondary study. Document submission requirements depend on whether your institution of study is within Canada or outside of Canada.
A minimum of three references are required for application to graduate programs at UBC. References should be requested from individuals who are prepared to provide a report on your academic ability and qualifications.
Many programs require a statement of interest, sometimes called a "statement of intent", "description of research interests" or something similar.
Students in research-based programs usually require a faculty member to function as their thesis supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.
Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.
All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.
Faculty are conducting research in a variety of applied an theoretical areas, such as Bayesian Statistics, Bioinformatics, Biostatistics, Environmental and Spatial Statistics, Forest Products Stochastic Modeling, Modern multivariate and time series analysis, robust statistics, and Statistical learning. Further details can be found on our website: https://www.stat.ubc.ca/research-areas
During the first year of the program, students will complete Stat 548, the Qualifying Course. This directed reading course consists of reading and reporting on five papers under the supervision of different faculty members. This unique course allows students the opportunity to explore a diverse range of Statistical topics and work with different faculty members before committing to a supervisor and thesis research topic. The PhD Comprehensive Exam will take place by the end of the second year in the program. This exam lays the groundwork for the PhD thesis, which consists of independent original research. Students are expected to have completed all required courses before the Comprehensive Exam. Near the end of thesis completion, students present their work at the Department Seminar.
| Fees | Canadian Citizen / Permanent Resident / Refugee / Diplomat | International |
|---|---|---|
| Application Fee | $116.25 | $168.25 |
| Tuition * | ||
| Installments per year | 3 | 3 |
| Tuition per installment | $1,875.34 | $3,294.66 |
| Tuition per year (plus annual increase, usually 2%-5%) | $5,626.02 | $9,883.98 |
| Int. Tuition Award (ITA) per year (if eligible) | $3,200.00 (-) | |
| Other Fees and Costs | ||
| Student Fees (yearly) | $1,116.60 (approx.) | |
| Costs of living | Estimate your costs of living with our interactive tool in order to start developing a financial plan for your graduate studies. | |
Applicants to UBC have access to a variety of funding options, including merit-based (i.e. based on your academic performance) and need-based (i.e. based on your financial situation) opportunities.
PhD students in the Department of Statistics receive a minimum funding package of $24,000 for the first four years of the program. This funding comes in the form of teaching and/or research assistantships. Motivated students can often find additional sources of funding. Domestic students are expected to apply for NSERC PGSD scholarships.
All applicants are encouraged to review the awards listing to identify potential opportunities to fund their graduate education. The database lists merit-based scholarships and awards and allows for filtering by various criteria, such as domestic vs. international or degree level.
Many professors are able to provide Research Assistantships (GRA) from their research grants to support full-time graduate students studying under their supervision. The duties constitute part of the student's graduate degree requirements. A Graduate Research Assistantship is considered a form of fellowship for a period of graduate study and is therefore not covered by a collective agreement. Stipends vary widely, and are dependent on the field of study and the type of research grant from which the assistantship is being funded.
Graduate programs may have Teaching Assistantships available for registered full-time graduate students. Full teaching assistantships involve 12 hours work per week in preparation, lecturing, or laboratory instruction although many graduate programs offer partial TA appointments at less than 12 hours per week. Teaching assistantship rates are set by collective bargaining between the University and the Teaching Assistants' Union.
Academic Assistantships are employment opportunities to perform work that is relevant to the university or to an individual faculty member, but not to support the student’s graduate research and thesis. Wages are considered regular earnings and when paid monthly, include vacation pay.
Canadian and US applicants may qualify for governmental loans to finance their studies. Please review eligibility and types of loans.
All students may be able to access private sector or bank loans.
Many foreign governments provide support to their citizens in pursuing education abroad. International applicants should check the various governmental resources in their home country, such as the Department of Education, for available scholarships.
The possibility to pursue work to supplement income may depend on the demands the program has on students. It should be carefully weighed if work leads to prolonged program durations or whether work placements can be meaningfully embedded into a program.
International students enrolled as full-time students with a valid study permit can work on campus for unlimited hours and work off-campus for no more than 20 hours a week.
A good starting point to explore student jobs is the UBC Work Learn program or a Co-Op placement.
Students with taxable income in Canada may be able to claim federal or provincial tax credits.
Canadian residents with RRSP accounts may be able to use the Lifelong Learning Plan (LLP) which allows students to withdraw amounts from their registered retirement savings plan (RRSPs) to finance full-time training or education for themselves or their partner.
Please review Filing taxes in Canada on the student services website for more information.
Applicants have access to the cost estimator to develop a financial plan that takes into account various income sources and expenses.
31 students graduated between 2005 and 2013. Of these, career information was obtained for 29 alumni (based on research conducted between Feb-May 2016):
These statistics show data for the Doctor of Philosophy in Statistics (PhD). Data are separated for each degree program combination. You may view data for other degree options in the respective program profile.
| 2023 | 2022 | 2021 | 2020 | 2019 | |
|---|---|---|---|---|---|
| Applications | 67 | 72 | 97 | 77 | 63 |
| Offers | 14 | 9 | 16 | 8 | 11 |
| New Registrations | 5 | 5 | 8 | 7 | 6 |
| Total Enrolment | 39 | 37 | 39 | 32 | 27 |
Students in research-based programs usually require a faculty member to function as their thesis supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.
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.
| Year | Citation |
|---|---|
| 2024 | Dr. Zhang developed statistical methods to uncover hidden patterns in biological data. His research helped to unravel the underlying mechanism of complex diseases. In a study of pancreatic cancer, his method revealed seven gene programs related to cancer progression, which can aid researchers to develop more effective treatment strategies. |
| 2024 | Dr. Zhang developed a flexible statistical model with which the relations among multiple time series variables can be considered after modeling each individual time series. It is applied to macroeconomic variables with changing business cycles. |
| 2024 | Dr. Daly-Grafstein developed new statistical methods for studying cause-and-effect relationships. These methods require fewer assumptions about the nature of the data, making estimates more robust. They are applicable when conducting observational studies or when research data is partially missing. |
| 2023 | Dr. Pan investigated new conditional inference and prediction methods after fitting a joint distribution based on vine copulas, including prediction of an arbitrary variable given others, prediction of a right-censored response, and prediction of an ordinal or continuous response when some explanatory variables are nominal categorical. |
| 2023 | Dr. Flynn developed statistical methods of using structured networks of data to estimate the size of hidden or hard-to-reach populations, and created corresponding software for these techniques to readily be used by researchers across diverse fields. These methods were used to illuminate the true scope of the opioid epidemic in British Columbia. |
| 2023 | Can we find structure in complex systems, like social networks or the interactions between cell proteins? Dr. Briercliffe designed a class of statistical models for discovering hidden structure in networks.By harnessing probability theory, his research created practical tools that allow scientists to reveal order and structure in our complex world. |
| 2023 | Dr. Syed's work on non-reversible parallel tempering showed how parallel computing could improve the scalability of Monte Carlo methods and solve challenging statistic inference problems. He was awarded the Pierre Robillard award for the best PhD thesis in statistics and probability in Canada. |
| 2022 | Dr. Ju developed prediction methods that go beyond classical settings. Her proposals are built upon the idea of ensemble learning and use data that contain extreme or function-valued variables. The resulting algorithms provide computational tools for practitioners to deal with complex data seen in various applications. |
| 2022 | Dr. Christidis developed a new class of statistical algorithms designed to analyze data in high dimensions. He made theoretical and computational contributions to support his work. His methods were applied to study the relationship between genetic patterns and different types of diseases. |
| 2022 | Computer experiments are used as replacements for physical experiments in a wide variety of applications. Dr. Isberg's research addressed the analysis of large datasets arising from computer models, as well as the combination of multiple competing computer models. The work can be applied broadly in science and engineering, including climate models. |
Research interests of the faculty include biostatistics, environmetrics, mathematical modelling of biological systems, computational statistics, data mining, machine learning, theory of statistical inference, asymptotics, multivariate analysis, robustness, nonparametrics, design of experiments, smoothing, Bayesian methods, computational molecular biology, gene expression, and microarrays.
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