Statistics
Program Overview
Statistical Sciences involves the study of random phenomena and encompasses a broad range of scientific, industrial, and social processes. As data become ubiquitous and easier to acquire, particularly on a massive scale, models for data are becoming increasingly complex. The past several decades have witnessed a vast impact of statistical methods on virtually every branch of knowledge and empirical investigation.
There are also opportunities for study and research in the fields of (a) Statistical Theory and Applications and (b) Probability, leading to the Master of Science and Doctor of Philosophy degrees, and (c) Actuarial Science and Mathematical Finance, leading to the Doctor of Philosophy degree. Please visit the departmental website for further details about the fields offered, the research being conducted, and the course offerings.
The department has substantial computing facilities available and operates a statistical consulting service for the University’s research community. Programs of study may involve association with other departments such as Astronomy & Astrophysics, Computer Science, Economics, Engineering, Environment, Information, Management, Mathematics, Philosophy, Psychology, Public Health, and Sociology. The department maintains an active seminar series and strongly encourages graduate student participation.
PhD applicants will be able to select up to three potential supervisors at the time of their applications. Supervisors are then matched and assigned by the department upon acceptance of offer to the PhD program based on research areas of interest.
Quick Facts
Domestic  International  

Application deadline  PhD: 22Nov2022 22Jan2023  PhD: 22Nov2022 22Jan2023 
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 
Are any standardized tests required/recommended?  MSc, PhD: N/A  MSc, PhD: N/A 
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:

STA2101H Methods of Applied Statistics I

STA2201H Methods of Applied Statistics II

STA2111H Probability Theory I

STA2211H Probability Theory II

STA2112H Mathematical Statistics I

STA2212H 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 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 successfully complete a total of 3.0 fullcourse equivalents (FCEs) as follows:

STA3000Y Advanced Theory of Statistics (1.0 FCE)
and two of the following:

STA2101H Methods of Applied Statistics I and STA2201H Methods of Applied Statistics II (1.0 FCE)

STA2111H Probability Theory I and STA2211H Probability Theory II (1.0 FCE)

STA2311H Advanced Computational Methods for Statistics I and STA2312H Advanced Computational Methods for Statistics II (1.0 FCE).


Courses must be chosen in consultation with the advisor and approved by the Associate Chair of Graduate Studies.
Comprehensive Examination Requirements

Within Years 1 and 2, students must complete a twopart comprehensive examination: 1) an inclass written comprehensive exam and 2) a research comprehensive exam.

Students must attempt the inclass written comprehensive by the end of Year 1. If a student fails this portion of the comprehensive exam, one further attempt will be allowed by the end of Year 2. Students who achieve A or A+ grades in all required coursework are exempt from the inclass written exam.

Students must attempt the research comprehensive exam by the beginning of Year 2, which includes a technical report and an oral presentation. If a student fails this portion of the comprehensive exam, one further attempt will be allowed at the end of Year 2.

Students must pass both the inclass written exam and the research exam to continue in the program.

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

Students must successfully complete a total of 5.0 fullcourse equivalents (FCEs) as follows:

Year 1: complete 3.0 FCEs:

STA3000Y Advanced Theory of Statistics (1.0 FCE)
and two of the following: 
STA2101H Methods of Applied Statistics I and STA2201H Methods of Applied Statistics II (1.0 FCE)

STA2111H Probability Theory I and STA2211H Probability Theory II (1.0 FCE)

STA2311H Advanced Computational Methods for Statistics I and STA2312H Advanced Computational Methods for Statistics II (1.0 FCE).

Courses must be chosen in consultation with the advisor and approved by the Associate Chair of Graduate Studies.


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

Within Years 1 and 2, students must complete a twopart comprehensive examination: 1) an inclass written comprehensive exam and 2) a research comprehensive exam.

Students must attempt the inclass written comprehensive by the end of Year 1. If a student fails this portion of the comprehensive exam, one further attempt will be allowed by the end of Year 2. Students who achieve A or A+ grades in all required coursework are exempt from the inclass written exam.

Students must attempt the research comprehensive exam by the beginning of Year 2, which includes a technical report and an oral presentation. If a student fails this portion of the comprehensive exam, one further attempt will be allowed at the end of Year 2.

Students must pass both the inclass written exam and the research exam to continue in the program.

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 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):

(1.5 FCEs) All of:

STA2111H Probability Theory I,

STA2211H Probability Theory II, and

STA2503H Applied Probability for Mathematical Finance.


(0.5 FCE) One of:

STA2501H Advanced Topics in Actuarial Science or

STA4246H Research Topics in Mathematical Finance.


(1.0 FCE) One of:

STA2101H Methods of Applied Statistics I and STA2201H Methods of Applied Statistics II or

STA2311H Advanced Computational Methods for Statistics I and STA2312H Advanced Computational Methods for Statistics II or

STA3000Y Advanced Theory of Statistics.


Comprehensive Examination Requirements

Within Years 1 and 2, students must complete a twopart comprehensive examination: 1) an inclass written comprehensive exam and 2) a research comprehensive exam.

Students must attempt the inclass written comprehensive by the end of Year 1. If a student fails this portion of the comprehensive exam, one further attempt will be allowed by the end of Year 2. Students who achieve A or A+ grades in all required coursework are exempt from the inclass written exam.

Students must attempt the research comprehensive exam by the beginning of Year 2, which includes a technical report and an oral presentation. If a student fails this portion of the comprehensive exam, one further attempt will be allowed at the end of Year 2.

Students must pass both the inclass written exam and the research exam to continue in the program.

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
4 years
Time Limit
6 years
“Toronto has become one of the major research centres for AI in North America.”
 Cedric Beaulac
 PhD Candidate, Statistical Sciences