![Mathematics 3 Building](/future-graduate-students/sites/default/files/styles/large/public/uploads/images/faculty-of-mathbanner-final.png?itok=ekT5Fm4a)
Mathematics 3 (M3) Building on Waterloo's Campus
Become a first-class independent researcher with the PhD in Statistics program. If you have completed a master’s or bachelor’s degree in statistics, actuarial science, mathematics, or other quantitative disciplines, this PhD will prepare you to enter a career in academia, research or private industry.
Programs in the Department of Statistics and Actuarial Science will give you top-notch qualifications for positions in business, industry, government agencies, research organizations, and academia. Our graduates are in demand and enjoy high degrees of job satisfaction.
Research areas include computational statistics, finance, industrial statistics, probability, and statistical theory and methods.
Research areas
- Computational Statistics
- Finance
- Industrial Statistics
- Probability
- Statistical Theory and Methods
Program overview
Department/School: Statistics and Actuarial Science
Faculty: Faculty of Mathematics
Admit term(s): Fall (September - December)
Delivery mode: On-campus
Program type: Doctoral, Research
Length of program: 48 months (full-time)
Registration option(s): Full-time, Part-time
Study option(s): Thesis
Application deadlines
- January 15 (for admission in September)
![Joy Jiang](/future-graduate-students/sites/default/files/styles/large/public/uploads/images/jan-21_0.jpeg?itok=RY1_8tO2)
I received my Ph.D. in Statistics at UWaterloo in 2018 (a shout out to my advisor Richard Cook!) and have received strong training in statistical theory and methodology. During the course of my PhD, my collaboration experiences with folks at the University of Toronto PsA clinic and the Statistical Consulting Centre at UWaterloo have helped tremendously in working with other researchers and team science projects post-graduation.
Supervisors
- Review the finding a supervisor resources
- Before applying to the program, students are strongly advised to establish contact with potential supervisors
Admission requirements
- A Master's degree in statistics, actuarial science, or mathematics, completed or expected. Note: graduates of other quantitative and mathematically oriented programs are also encouraged to apply; this includes, but is not restricted to, graduates of commerce, economics, engineering, finance, and any of the physical sciences. The department graduate committee will determine the suitability of each student’s background for success in this program.
- Students with an undergraduate degree in statistics, actuarial science, or mathematics may apply for admission directly to the PhD program. Successful applicants will have an outstanding academic record, and very strong letters of recommendation.
- At least an overall 78% average from a Canadian university (or its equivalent)
- An interview may be required
Degree requirements
- Review the degree requirements on the Graduate Studies Academic Calendar, including the courses that you can anticipate taking as part of completing the degree
- Check out Waterloo's institutional thesis repository - UWspace to see recent submissions from the Department of Statistics and Actuarial Science graduate students
Application materials
- Resume
- Supplementary information form (SIF)
- The SIF contains questions specific to your program, typically about why you want to enroll and your experience in that field. Review the application documents web page for more information about this requirement
- If a statement or letter is required by your program, review the writing your personal statement resources for helpful tips and tricks on completion
-
Transcript(s)
- References
- Three references are required; at least two academic
- Proof of English language proficiency, if applicable
- TOEFL 90 (writing 25, speaking 25), IELTS 7.0 (writing 6.5, speaking 6.5)
Tuition and fees
- Visit the graduate program tuition page on the Finance website to determine the tuition and incidental fees per term for your program
-
Review living costs and housing
-
Review the funding graduate school resources for graduate students