Doctor of Philosophy in Statistics (PhD)

Overview

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.

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. 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.

 

Program Enquiries

Still have questions after reviewing this page thoroughly?
Contact the program

Admission Information & Requirements

1) Check Eligibility

Minimum Academic Requirements

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.

English Language Test

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:

TOEFL: Test of English as a Foreign Language - internet-based

Overall score requirement: 100

Reading

22

Writing

21

Speaking

21

Listening

22

IELTS: International English Language Testing System

Overall score requirement: 7.5

Reading

6.5

Writing

6.5

Speaking

6.5

Listening

6.5

Other Test Scores

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.

Prior degree, course and other requirements

Course Requirements

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).

Document Requirements

We require a 2 page (maximum) statement of interest/research proposal, as well as a CV.

2) Meet Deadlines

Application open dates and deadlines for an upcoming intake have not yet been configured in the admissions system. Please check back later.

3) Prepare Application

Transcripts

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.

Letters of Reference

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.

Statement of Interest

Many programs require a statement of interest, sometimes called a "statement of intent", "description of research interests" or something similar.

Supervision

Students in research-based programs usually require a faculty member to function as their supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.

Instructions regarding supervisor contact for Doctor of Philosophy in Statistics (PhD)
The program will review research interests of applicants and recommend/match faculty members during the application/evaluation process. Applicants should not reach out to faculty members directly.

Citizenship Verification

Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.

4) Apply Online

All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.

Research Information

Research Focus

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

Program Components

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.

Tuition & Financial Support

Tuition

FeesCanadian Citizen / Permanent Resident / Refugee / DiplomatInternational
Application Fee$108.00$168.25
Tuition *
Installments per year33
Tuition per installment$1,732.53$3,043.77
Tuition per year
(plus annual increase, usually 2%-5%)
$5,197.59$9,131.31
Int. Tuition Award (ITA) per year (if eligible) $3,200.00 (-)
Other Fees and Costs
Student Fees (yearly)$1,052.34 (approx.)
Costs of living (yearly)starting at $17,126.20 (check cost calculator)
* Regular, full-time tuition. For on-leave, extension, continuing or part time (if applicable) fees see UBC Calendar.
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. Tuition fees are reviewed annually by the UBC Board of Governors. In recent years, tuition increases have been 2% for continuing domestic students and between 2% and 5% for continuing international students. New students may see higher increases in tuition. Admitted students who defer their admission are subject to the potentially higher tuition fees for incoming students effective at the later program start date. In case of a discrepancy between this webpage and the UBC Calendar, the UBC Calendar entry will be held to be correct.

Financial Support

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.

Program Funding Packages

PhD students in the Department of Statistics receive a minimum funding package of $22,000 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. 

Average Funding
Based on the criteria outlined below, 23 students within this program were included in this study because they received funding through UBC in the form of teaching, research/academic assistantships or internal or external awards averaging $33,943.
  • 13 students received Teaching Assistantships. Average TA funding based on 13 students was $11,772.
  • 17 students received Research/Academic Assistantships. Average RA/AA funding based on 17 students was $13,773.
  • 23 students received internal awards. Average internal award funding based on 23 students was $13,051.
  • 3 students received external awards. Average external award funding based on 3 students was $31,111.

Study Period: Sep 2019 to Aug 2020 - average funding for full-time PhD students enrolled in three terms per academic year in this program across years 1-4, the period covered by UBC's Minimum Funding Guarantee. Averages might mask variability in sources and amounts of funding received by individual students. Beyond year 4, funding packages become even more individualized.
Review methodology
Scholarships & awards (merit-based funding)

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.

Teaching Assistantships (GTA)

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.

Research Assistantships (GRA)

Many professors are able to provide Research Assistantships (GRA) from their research grants to support full-time graduate students studying under their direction. The duties usually constitute part of the student's graduate degree requirements. A Graduate Research Assistantship is a form of financial support for a period of graduate study and is, therefore, not covered by a collective agreement. Unlike other forms of fellowship support for graduate students, the amount of a GRA is neither fixed nor subject to a university-wide formula. The stipend amounts vary widely, and are dependent on the field of study and the type of research grant from which the assistantship is being funded. Some research projects also require targeted research assistance and thus hire graduate students on an hourly basis.

Financial aid (need-based funding)

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.

Foreign government scholarships

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.

Working while studying

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.

Tax credits and RRSP withdrawals

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.

Cost Calculator

Applicants have access to the cost calculator to develop a financial plan that takes into account various income sources and expenses.

Career Outcomes

31 students graduated between 2005 and 2013. Of these, career information was obtained for 29 alumni (based on research conducted between Feb-May 2016):


RI (Research-Intensive) Faculty: typically tenure-track faculty positions (equivalent of the North American Assistant Professor, Associate Professor, and Professor positions) in PhD-granting institutions
TI (Teaching-Intensive) Faculty: typically full-time faculty positions in colleges or in institutions not granting PhDs, and teaching faculty at PhD-granting institutions
Term Faculty: faculty in term appointments (e.g. sessional lecturers, visiting assistant professors, etc.)
Sample Employers in Higher Education
University of British Columbia (3)
Simon Fraser University (3)
Northern Illinois University (2)
University of Dhaka
Grant MacEwan University
University of Toronto
University of Saskatchewan
York University
Ecole des Hautes Etudes Commerciales de Montreal
West Virginia University
Sample Employers Outside Higher Education
Google (3)
Scotiabank
TransUnion
eBay
Genentech
AstraZeneca
Children's Hospital of Philadelphia
Eli Lilly and Company
Ghement Statistical Consulting Company Ltd.
Sample Job Titles Outside Higher Education
Senior Statistician (2)
Statistician
Senior Research Scientist
Data Scientist
Senior Consultant
Senior Statistical Scientist
Principal
Director Risk
Staff Data Scientist
Quantitative Analyst
PhD Career Outcome Survey
You may view the full report on career outcomes of UBC PhD graduates on outcomes.grad.ubc.ca.
Disclaimer
These data represent historical employment information and do not guarantee future employment prospects for graduates of this program. They are for informational purposes only. Data were collected through either alumni surveys or internet research.
Career Options

Our students are prepared for a successful career in industry, academia or the public sector. Former students looking for a job after graduation have been promptly offered employment in many different industries, universities and government agencies. Please view a list of alumni and their first positions after graduation on our website.

Enrolment, Duration & Other Stats

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.

Enrolment Data

 20202019201820172016
Applications7459704038
Offers811949
New registrations76645
Total enrolment3227272427

Completion Rates & Times

This program has a graduation rate of 84.21% based on 19 students admitted between 2007 - 2010. Based on 19 graduations between 2016 - 2019 the minimum time to completion is 3.83 years and the maximum time is 5.67 years with an average of 4.86 years of study. All calculations exclude leave times.
Disclaimer
Admissions data refer to all UBC Vancouver applications, offers, new registrants for each year, May to April [data updated: 22 April 2021]. Enrolment data are based on March 1 snapshots. Program completion data are only provided for datasets comprised of more than 4 individuals. Rates and times of completion depend on a number of variables (e.g. curriculum requirements, student funding), some of which may have changed in recent years for some programs [data updated: 29 October 2020].

Doctoral Citations

A doctoral citation summarizes the nature of the independent research, provides a high-level overview of the study, states the significance of the work and says who will benefit from the findings in clear, non-specialized language, so that members of a lay audience will understand it.
Year Citation
2018 Many practical problems are subject to order constraints, for example, combined physical and chemical therapies are usually at least as good as chemical therapy alone. Dr. Zhou developed methods to formally utilize order constraints for statistical inference. His methods enable scientists from various disciplines to make more efficient use of the available data resources.
2018 Dr. Chen examined both the design and analysis of computer experiments from a statistical perspective. He developed a new method to estimate the unknown parameters of a Gaussian process model. He also assessed the performance of some existing methods in sequential experimental design and provided insights into issues faced by practitioners.
2017 Using machine learning techniques, Dr. Zhang developed a method to group high-dimensional cases using hierarchical approaches. He also developed a predictive framework called Regression Phalanxes which selects subsets of features that work well together for prediction. This new framework outperforms current methods in a variety of applications.
2017 Identifying anomalies in multivariate data is important in many applications including fraud detection. Dr. Leung developed methods to identify individual and chunks of deviating data cells in a data set. He subsequently extended his method to serve as an initial step for estimating different statistical quantities.
2017 Dr. Liu developed statistical methods to predict and interpret high dimensional spatial tracks based on observations from multiple sources. His study has improved the tracking of endangered marine mammals and advanced our understanding of their behaviour. His methods can handle big data efficiently and solve other modern tracking problems.
2017 Dr. Luo developed statistical methods for analyzing epidemiological data for situations where the acquisition of genotype and the exposure to environment are independent. These methods can be applied to facilitate the understanding of the joint effect of genetic and environmental factors on human disease.
2017 Dr. Coia developed a flexible statistical approach for forecasting extreme events such as big floods and large insurance claims, by carefully garnering information from precursors. He also identified a new probabilistic model that can allow a varying level of risk. This research will allow us to better develop early warning systems for disasters.
2017 Dr. Lee studied statistical extremes involving several variables. He explored methods to investigate extreme value models with connections driven by hidden factors or proximity of sites. Examples in the environmental and financial areas include the annual maximum stream flows at various locations along a river, and extreme stock returns.
2016 Dr. Zhai works on disentangling history of human evolution and language evolution using statistical methods. He showed that the path of human migration can be discovered based on the genetic variation observed among current human populations.
2016 Dr. Casquilho Resende developed statistical models to better understand localized weather regimes in complex geographical regions. Her design strategy for monitoring networks provides critical data for both scientists and governmental agencies, contributing to the surveillance of environmental processes and further understanding Earth's climate.

Pages

Further Information

Specialization

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.

Faculty Overview

Academic Unit

Program Identifier

VGDPHD-XA

Classification

 
 
 
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