- Rohana Ambagaspitiya: Renewal Risk Processes, Statistics, Probability Theory and Stochastic Processes.
- Alexandru Badescu: Mathematical Finance, Actuarial Science
- Gemai Chen: Parametric & Non-parametric regression, Non-linear Time Series Modelling of Environmental Changes, Extreme-value Analysis, etc.
- Rob Deardon: Bayesian Statistics and Computation, Infectious Disease Epidemiology, Statistical Learning, etc.
- Alex de Leon: Assessment of Diagnostic Tests, Copula Models, Estimating Functions and Estimating Equations, Statistical Problems in Medicine, etc.
- Xuewen Lu: Big-data and High-dimensional Data Analysis, Biostatistics, Empirical Likelihood, Survival Analysis and Randomly Censored Data, etc.
- David Scollnik: Actuarial Science, Bayesian Statistics and Computation, Markov Chain Monte Carlo and Related Simulation Methods, Mathematical Finance.
- Deniz Sezer: Credit Risk and Finance, Super-processes, Markov Chain Mote Carlo Methods
- Hua Shen: Biostatistics, Analysis of Recurrent Events, Longitudinal Data Analysis, General Linear models, etc.
- Anatoliy Swishchuk: Financial Mathematics, Biomathematics, Random Evolutions and Their Applications, Stochastic Calculus
- Jingjing Wu: Minimum Distance Estimation, Non/semi-parametric Models, Regression/Logistic Regression Models, Biostatistics, etc.
- Qingrun Zhang: Machine learning, High-dimensional data mining, Biostatistics, Bioinformatics
The course requirements for a PhD degree are determined on an individual basis and must include eight courses in the student’s combined MSc and PhD program in addition to Statistics 600 seminar course which must be taken in the first or second year of the program.
Should maintain a minimum cumulative Grade Point Average (GPA) of 3.00 calculated on a four point scale at the end of each registration year and attain at least a B- on each course taken for credit.
Course selection for statistics program:
- Seminar: STAT 600 Research Seminar (this course is not one of the eight required courses).
- STAT 701
- STAT 721
- At least 3 courses from List C
List C courses
STAT 701 Theory of Probability I
STAT 721 Statistical Inference
STAT 631 Computational Statistics
STAT 633 Survival Models
STAT 635 Generalized Linear Models
STAT 641 Statistical Learning
STAT 603 Applied Statistics for Nursing Research
STAT 619 Bayesian Statistics
STAT 625 Multivariate Analysis
STAT 633 Survival Models
STAT 637 Non-linear Regression
STAT 601.20 Topics in Probability and Statistics (Nonparametric Statistics)
STAT 601.21 Topics in Probability and Statistics (Advanced Statistical Methods and Applications)
STAT 601.23 Topics in Probability and Statistics (Asymptotic Statistical Inference)
STAT 601.24 Topics in Probability and Statistics (Markov Processes)
STAT 601.25 Topics in Probability and Statistics (Longitudinal Data Analysis)
STAT 601.27 Topics in Probability and Statistics (Data Mining and Machine Learning with R)
STAT 601.28 Topics in Probability and Statistics (Deep Learning and Its Hands-on Practice)
STAT 601.29:Topics in Probability and Statistics (Infectious Disease Modelling)
Note: Descriptions of STAT 601 topic courses are available here
The PhD is a full-time degree with an expected completion time of four years. The maximum time allowed is six years.
- Supervisors will decide with their students on what courses the students have to take and what preliminary exams the students have to write.
- A supervisory committee must be established within three months after the program starts. The supervisory committee includes a supervisor (and a co-supervisor if there is one), and two supervisory committee members.
- The supervisory committee should meet with the student regularly to provide guidance through the program.
Written preliminary exams
Statistics doctorate students must pass two written preliminary examinations usually during the first year but no later than 18 months from the beginning of their doctoral programs. The material of the two preliminary exams will be based upon STAT 721 and STAT 701.
Written candidacy proposal and oral candidacy exam
- Program course work and examination requirements completed (prior to candidacy oral examination)
- Written proposal submitted to supervisory committee (recommended six months, minimum four months in advance of expected oral examination date)
- Reading list approved by the graduate program director (at least three months prior to scheduling oral examination)
- Written research proposal approved (at least two months prior to scheduling oral examination)
- The oral candidacy examination must be taken no later than 28 months from the start of the doctoral program. Prior to the oral examination, the student must have completed all the course work and the written preliminary examinations
- The oral candidacy exam must be scheduled at least four weeks before the intended date.
- The exam committee contains a supervisor, a co-supervisor (if it is applicable), supervisory committee members (usually two), and two examiners (outside of student’s program, within the department or within the university)
More information can be found under the following links:
Thesis and thesis oral examination
The student must complete a thesis on a topic to be agreed to by the student and their supervisor.
- After completion of the thesis, the student must pass a thesis oral examination
- A thesis oral exam committee contains a supervisor, a co-supervisor (if applicable), supervisory committee members (usually two), an examiner (outside of student’s program, within the department or within the university) and an external examiner (from outside of the university)
- The external examiner must be applied for approval from Faculty of Graduate Studies six weeks prior the intended examination date
- The exam must be scheduled at least four weeks prior to date of oral exam
- Examiners must have a copy of the thesis at least three weeks prior to the date of oral exam
- Final thesis oral examinations are open
More information can be found on the Faculty of Graduate Studies website under examinations.