Degree and Diploma Programs by Graduate Unit
2014-15 SGS Calendar
Statistical Sciences
Faculty Affiliation
Arts and Science
Degree Programs Offered
Statistics—MSc, PhD
Fields:
 Statistical Theory and Applications (MSc, PhD)
 Probability (MSc, PhD)
 Actuarial Science and Mathematical Finance (PhD)
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.
The Department of Statistical Sciences offers
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 Department of
Statistical Sciences website for further details about the
fields offered, the research being conducted, and the
course offerings in the department.
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
Computer Science, Economics, Engineering,
Mathematics, Public Health Sciences, and the Rotman
School of Management. The department maintains an
active seminar series and strongly encourages graduate
student participation.
Interested applicants will find detailed information on the
department's website.
Contact and Address
Web: www.utstat.utoronto.ca
Email: grad-info@utstat.utoronto.ca
Telephone: (416) 978-5136
Fax: (416) 978-5133
Department of Statistical Sciences
University of Toronto
Sidney Smith Hall
Room 6022, 100 St. George Street
Toronto, Ontario M5S 3G3
Canada
Degree Programs
Statistics
Master of Science
Fields: Statistical Theory and
Applications; 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:
o 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.
o An average grade equivalent to at least a University of
Toronto mid-B in the final year or over senior courses.
o Three letters of reference.
 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 using one of the
official methods specified in the General Regulations of
the School of Graduate Studies.
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.
Full-Time Program
 Students must complete a total of 4.0 full-course
equivalents (FCEs), of which 2.0 must be chosen from
the list below:
2014-2015 School of Graduate Studies Calendar
www.sgs.utoronto.ca/calendar
Statistical Sciences
1
Degree and Diploma Programs by Graduate Unit
o STA 2101H Methods of Applied Statistics I
o STA 2201H Methods of Applied Statistics II
o STA 2111H Probability Theory I
o STA 2211H Probability Theory II
o STA 2112H Mathematical Statistics I
o STA 2212H Mathematical Statistics II
o STA 3000Y Advanced Theory of Statistics.
 The remaining 2.0 FCEs may be selected from:
o any Department of Statistical Sciences 2000-level
course or higher
o any 1000-level course or higher in another graduate
unit at the University of Toronto with sufficient
statistical, computational, probabilistic, or mathematical
content
o one 0.5 FCE as a reading course
o one 0.5 FCE as a research project
o a maximum of 1.0 FCE from any STA 4500-level
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.
Part-Time Program
 Students must satisfy the program requirements outlined
for the full-time MSc.
 Students are limited to taking 1.0 full-course equivalent
(FCE) during each session. In exceptional cases, the
Associate Chair for Graduate Studies may approve 1.5
FCE in a given session. Both the Statistical Theory and
Applications field and the Probability field are open to
part-time students.
Program Length
3 sessions full-time (typical registration sequence:
F/W/S);
6 sessions part-time
Time Limit
3 years full-time;
6 years part-time
Doctor of Philosophy
Minimum Admission Requirements
 Admission to the PhD program is competitive, and
applicants are admitted under the General Regulations
of the School of Graduate Studies.
 Students may be accepted through one of two routes: a
master's degree or by direct entry through a bachelor's
degree. Successful applicants present either:
1. 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.
2014-2015 School of Graduate Studies Calendar
www.sgs.utoronto.ca/calendar
2. 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 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 using one of the
official methods specified in the General Regulations of
the School of Graduate Studies.
Program Requirements
Fields: Statistical Theory and Applications;
Probability
Course Requirements:
 During the first year of study, students are required to
complete the following 3.0 full-course equivalents
(FCEs):
o STA 2111H Probability Theory I
o STA 2211H Probability Theory II
o STA 2101H Methods of Applied Statistics I
o STA 2201H Methods of Applied Statistics II
o STA 3000Y Advanced Theory of Statistics
Comprehensive Examination Requirements:
 At the end of the first year, students must attempt the
following comprehensive examinations:
o Probability
o Theoretical Statistics
o Applied Statistics
All three examinations must be passed by the end of the
second year.
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 two-year residency
requirement.
Program Requirements
Field: Actuarial Science and Mathematical Finance
Course Requirements:
 During the first year of study, students are required to
complete the following 3.0 full-course equivalents
(FCEs):
Statistical Sciences
2
Degree and Diploma Programs by Graduate Unit
1. All of:
 STA 2111H Probability Theory I,
 STA 2211H Probability Theory II, and
 STA 2503H Applied Probability for Mathematical
Finance
2. One of:
 STA 4246H Research Topics in Mathematical
Finance or
 STA 2501H Mathematical Risk Theory
3. Either:
 STA 3000Y Advanced Theory of Statistics or
 STA 2101H Methods of Applied Statistics I and
 STA 2201H Methods of Applied Statistics II
STA 1002H
Methods of Data Analysis
STA 1003H
Sample Survey Theory and its
Application
STA 1007H
Statistics for Life and Social Scientists
STA 1008H
Applications of Statistics
STA 2004H
Design of Experiments
STA 2005H
Applied Multivariate Analysis
STA 2006H
Applied Stochastic Processes
STA 2047H
Stochastic Calculus
STA 2100H
Mathematical Methods for Statistics
STA 2101H
Methods of Applied Statistics I
STA 2102H
Computational Techniques in Statistics
STA 2104H
Statistical Methods for Machine
Learning and Data Mining
STA 2105H
Nonparametric Methods of Statistics
STA 2111H
Probability Theory I
STA 2112H
Mathematical Statistics I
STA 2162H
Statistical Inference I
STA 2201H
Methods of Applied Statistics II
Direct-Entry PhD Program Requirements
STA 2202H
Time Series Analysis
The program requirements are identical to the regular PhD
program in the respective fields with the exception that
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.
STA 2209H
Lifetime Date Modelling and Analysis
STA 2211H
Probability Theory II
STA 2212H
Mathematical Statistics II
Students must also satisfy a three-year residency
requirement.
STA 2342H
Multivariate Analysis I
STA 2453H
Statistical Consulting
STA 2501H
Mathematical Risk Theory
STA 2502H
Stochastic Models in Investments
Course List
STA 2503H
The department offers a selection of courses each year
from the following list with the possibility of additions. The
core courses will be offered each year. Visit the
department's website for courses offered in the current
academic year.
Applied Probability for Mathematical
Finance
STA 2505H
Credibility Theory and Simulation
Methods
STA 2542H
Linear Models
Comprehensive Examination Requirements:
 At the end of the first year, students must attempt the
following comprehensive examinations:
o Probability
o Actuarial Science and Mathematical Finance
o Theoretical Statistics or Applied Statistics
All three examinations must be passed by the end of the
second year.
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 two-year residency
requirement.
Residency Requirements:
Program Length
4 years full-time; 5 years direct-entry
Time Limit
6 years full-time; 7 years direct-entry
STA 1001H
Applied Regression Analysis
2014-2015 School of Graduate Studies Calendar
www.sgs.utoronto.ca/calendar
Statistical Sciences
3
Degree and Diploma Programs by Graduate Unit
STA 3000Y
Advanced Theory of Statistics
STA 3431H
Monte Carlo Methods
STA 4000H, Y
Supervised Reading Project I
STA 4001H, Y
Supervised Reading Project II
STA 4246H
Research Topics in Mathematical
Finance
STA 4247H
Point Processes, Noise, and Stochastic
Analysis
STA 4273H
Research Topics in Statistical Machine
Learning
STA 4315H
Computational Methods in Statistical
Genetics
STA 4364H
Conditional Inference: Sample Space
Analysis
STA 4412H
Topics in Theoretical Statistics Modular
Courses
Note: The following modular courses are each worth 0.25
full-course equivalents (FCEs).
STA 4500H
Statistical Dependence: Copula Models
and Beyond
STA 4501H
Functional Data Analysis and Related
Topics
STA 4502H
Monte Carlo Estimation
STA 4503H
Advanced Monte Carlo Methods and
Applications
STA 4504H
An Introduction to Bootstrap Methods
STA 4505H
Applied Stochastic Control: High
Frequency and Algorithmic Trading
STA 4506H
Non-stationary Time Series Analysis
STA 4507H
Extreme Value Theory and Applications
STA 4508H
Topics in Likelihood Inference
STA 4509H
Insurance Risk Models I
STA 4510H
Insurance Risk Models II
2014-2015 School of Graduate Studies Calendar
www.sgs.utoronto.ca/calendar
Statistical Sciences
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