Statistics
Program Overview
Quick Facts
Domestic  International  

Application payment deadline  PhD: 15Nov2020 MSc:22Jan2021  PhD: 15Nov2020 MSc:22Jan2021 
Supporting documents deadline  PhD: 30Nov2020 MSc:31Jan2021  PhD: 30Nov2020 MSc:31Jan2021 
Minimum admission average  MSc: B+ average in Master’s
 PhD: MSc: B+ average in Master’s
 PhD:
Direct entry option from bachelor's to PhD?  PhD: Yes (minimum Aminus average in bachelor’s degree)  PhD: Yes (minimum Aminus average in bachelor’s degree) 
Is a supervisor identified before or after admission?  PhD: Before  PhD: Before 
If a supervisor is identified after admission (as per question above), is admission conditional upon securing a supervisor?  PhD: No  PhD: No 
Is a supervisor assigned by the graduate unit or secured by the applicant?  PhD: Graduate Unit  PhD: Graduate Unit 
Program length (fulltime only)  MSc: 3 sessions PhD:4 years; 5 years if entering directly from bachelor’s  MSc: 3 sessions PhD:4 years; 5 years if entering directly from bachelor’s 
Master of Science
Program Description
Students in the MSc program can conduct research in the fields of 1) Statistical Theory and Applications or 2) Probability. The program offers numerous courses in theoretical and applied aspects of Statistical Sciences, which prepare students for pursuing a PhD program or directly entering the data science workforce.
The MSc program can be taken on a fulltime or parttime basis. Program requirements are the same for the fulltime and parttime options.
Fields:
1) Statistical Theory and Applications;
2) Probability
Minimum Admission Requirements

Admission to the MSc program is competitive, and applicants are admitted under the General Regulations of the School of Graduate Studies. Admission requirements for the Statistical Theory and Applications field and the Probability field are identical. Successful applicants have:

An appropriate bachelor's degree from a recognized university in a related field such as statistics, actuarial science, mathematics, economics, engineering, or any discipline where there is a significant quantitative component. Studies must include significant exposure to statistics, computer science, and mathematics, including coursework in advanced calculus, computational methods, linear algebra, probability, and statistics.

An average grade equivalent to at least a University of Toronto midB in the final year or over senior courses.

Three letters of reference.

A curriculum vitae.


Applicants whose primary language is not English and who graduated from a university where the language of instruction and examination was not English must demonstrate proficiency in English. See General Regulations section 4.3 for requirements.
Program Requirements

Both the Statistical Theory and Applications field and the Probability field have the same program requirements. All programs must be approved by the Associate Chair for Graduate Studies.

Students must complete a total of 4.0 fullcourse equivalents (FCEs), of which 2.0 must be chosen from the list below:

STA 2101H Methods of Applied Statistics I

STA 2201H Methods of Applied Statistics II

STA 2111H Probability Theory I

STA 2211H Probability Theory II

STA 2112H Mathematical Statistics I

STA 2212H Mathematical Statistics II


The remaining 2.0 FCEs may be selected from:

any Department of Statistical Sciences 2000level course or higher

any 1000level course or higher in another graduate unit at the University of Toronto with sufficient statistical, computational, probabilistic, or mathematical content

one 0.5 FCE as a reading course

one 0.5 FCE as a research project

a maximum of 1.0 FCE from any STA 4500level modular course (each are 0.25 FCE).


All programs must be approved by the Associate Chair for Graduate Studies. Students must meet with the Associate Chair to ensure that their program meets the requirements and is of sufficient depth.

Parttime students are limited to taking 1.0 FCE during each session. In exceptional cases, the Associate Chair for Graduate Studies may approve 1.5 FCEs in a given session.
Program Length
3 sessions fulltime (typical registration sequence: F/W/S);
6 sessions parttime
Time Limit
3 years fulltime;
6 years parttime
Doctor of Philosophy
Program Description
Students in the PhD program can conduct research in the fields of 1) Statistical Theory and Applications or 2) Probability or 3) Actuarial Science and Mathematical Finance. The research conducted in the department is vast and covers a diverse set of areas in theoretical and applied aspects of Statistical Sciences. Students have the opportunity to work in multidisciplinary areas and team up with researchers in, for example, Biostatistics, Computer Science, Economics, Engineering, and the Rotman School of Management. The main purpose of the program is to prepare students for pursuing advanced research both in academia and in research institutes.
Applicants may enter the PhD program via one of two routes: 1) following completion of an appropriate master’s degree or 2) direct entry after completing an appropriate bachelor’s degree (excluding Actuarial Science and Mathematical Finance).
Fields:
1) Statistical Theory and Applications;
2) Probability
PhD Program
Minimum Admission Requirements

Admission to the PhD program is competitive, and applicants are admitted under the General Regulations of the School of Graduate Studies.

Applicants may be accepted with a master's degree in statistics from a recognized university with at least a B+ average. Applicants with degrees in biostatistics, computer science, economics, engineering, mathematics, physics, or any discipline where there is a significant quantitative component will be also be considered.

Three letters of recommendation.

A curriculum vitae.

A letter of intent or personal statement outlining goals for graduate studies.

Applicants whose primary language is not English and who graduated from a university where the language of instruction and examination was not English must demonstrate proficiency in English. See General Regulations section 4.3 for requirements.
Program Requirements
Course Requirements

During Year 1, students are required to complete the following 3.0 fullcourse equivalents (FCEs):

STA 2111H Probability Theory I

STA 2211H Probability Theory II

STA 2101H Methods of Applied Statistics I

STA 2201H Methods of Applied Statistics II

STA 3000Y Advanced Theory of Statistics

Comprehensive Examination Requirements

At the end of Year 1, students must attempt the following comprehensive examinations:

Probability

Theoretical Statistics

Applied Statistics
All three examinations must be passed by the end of Year 2.

Thesis Requirements
Conducting original research is the most important part of doctoral work. The thesis document must constitute significant and original contribution to the field. Students will have yearly meetings with a committee of no less than three faculty members to assess their progress. The completed thesis must be presented and defended within the Department of Statistical Sciences in addition to being presented and defended at the School of Graduate Studies.
Residency Requirements
Students must also satisfy a twoyear residency requirement, whereby students must be on campus fulltime and consequently in geographical proximity to be able to participate fully in the University activities associated with the program.
Program Length
4 years
Time Limit
6 years
PhD Program (DirectEntry)
Minimum Admission Requirements

Admission to the PhD program is competitive, and applicants are admitted under the General Regulations of the School of Graduate Studies.

Applicants may be accepted via direct entry with a bachelor's degree in statistics from a recognized university with at least an A– average. The department also encourages applicants from biostatistics, computer science, economics, engineering, mathematics, physics, or any discipline where there is a significant quantitative component.

Three letters of recommendation.

A curriculum vitae.

A letter of intent or personal statement outlining goals for graduate studies.

Applicants whose primary language is not English and who graduated from a university where the language of instruction and examination was not English must demonstrate proficiency in English. See General Regulations section 4.3 for requirements.
Program Requirements
Course Requirements

During Year 1, students are required to complete the following 3.0 fullcourse equivalents (FCEs):

STA 2111H Probability Theory I

STA 2211H Probability Theory II

STA 2101H Methods of Applied Statistics I

STA 2201H Methods of Applied Statistics II

STA 3000Y Advanced Theory of Statistics


Students must complete an additional 2.0 FCEs at the graduate level. The additional courses must be approved by the Associate Chair of Graduate Studies.
Comprehensive Examination Requirements

At the end of Year 1, students must attempt the following comprehensive examinations:

Probability

Theoretical Statistics

Applied Statistics
All three examinations must be passed by the end of Year 2.

Thesis Requirements
Conducting original research is the most important part of doctoral work. The thesis document must constitute significant and original contribution to the field. Students will have yearly meetings with a committee of no less than three faculty members to assess their progress. The completed thesis must be presented and defended within the Department of Statistical Sciences in addition to being presented and defended at the School of Graduate Studies.
Residency Requirements
Students must also satisfy a threeyear residency requirement, whereby students must be on campus fulltime and consequently in geographical proximity to be able to participate fully in the University activities associated with the program.
Program Length
5 years
Time Limit
7 years
Field: Actuarial Science and Mathematical Finance
PhD Program
Minimum Admission Requirements

Admission to the PhD program is competitive, and applicants are admitted under the General Regulations of the School of Graduate Studies.

Applicants may be accepted with a master's degree in statistics from a recognized university with at least a B+ average. Applicants with degrees in biostatistics, computer science, economics, engineering, mathematics, physics, or any discipline where there is a significant quantitative component will be also be considered.

Three letters of recommendation.

A curriculum vitae.

A letter of intent or personal statement outlining goals for graduate studies.

Applicants whose primary language is not English and who graduated from a university where the language of instruction and examination was not English must demonstrate proficiency in English. See General Regulations section 4.3 for requirements.
Program Requirements
Course Requirements

During Year 1, students must complete the following 3.0 fullcourse equivalents (FCEs):

All of:

STA 2111H Probability Theory I,

STA 2211H Probability Theory II, and

STA 2503H Applied Probability for Mathematical Finance


One of:

STA 4246H Research Topics in Mathematical Finance or

STA 2501H Mathematical Risk Theory


Either:

STA 3000Y Advanced Theory of Statistics or

STA 2101H Methods of Applied Statistics I and

STA 2201H Methods of Applied Statistics II.


Comprehensive Examination Requirements

At the end of Year 1, students must attempt the following comprehensive examinations:

Probability

Actuarial Science and Mathematical Finance

Theoretical Statistics or Applied Statistics
All three examinations must be passed by the end of Year 2.

Thesis Requirements
Conducting original research is the most important part of doctoral work. The thesis document must constitute significant and original contribution to the field. Students will have yearly meetings with a committee of no less than three faculty members to assess their progress. The completed thesis must be presented and defended within the Department of Statistical Sciences in addition to being presented and defended at the School of Graduate Studies.
Residency Requirements
Students must also satisfy a threeyear residency requirement, whereby students must be on campus fulltime and consequently in geographical proximity to be able to participate fully in the University activities associated with the program.
Program Length
5 years
Time Limit
7 years
“Toronto has become one of the major research centres for AI in North America.”
 Cedric Beaulac
 PhD Candidate, Statistical Sciences