Program and Entrance Requirements
Department of Mathematical and Statistical Sciences will consider students who have an overall grade point average of 3.3
or higher in their undergraduate or graduate years at the University of
Alberta, or an equivalent grade point average from another institution. Strong Letters of Reference, a compelling Personal Statement and Curriculum Vitae are also necessary for consideration for admission.
International Applicants: For GPA equivalencies, please see this chart: minimum grade point average required from counties other than Canada.
Department of Mathematical and Statistical Sciences
requirements for admission are different than the minimum
requirements listed by the Faculty of Graduate Studies and
Research (FGSR). This pertains to coursework done within Canada, and outside
of Canada, as well as English Language Proficiency Tests. Applicants must meet the requirements set by the Department of Mathematical and Statistical Sciences to be considered for admission, as these requirements are higher than the requirements set by FGSR.
though an applicant may appear to satisfy the general
admission requirements, acceptance into a graduate program is not
guaranteed. This is due to the competitive nature of Mathematical and
Statistical Sciences programs, in which the Department cannot offer
admission to all qualified applicants, and therefore can offer
admission to the most qualified applicants only.
NOTE: Applicants whose first language is not English must provide a valid
English Language Proficiency score above the Department minimum. For
more information (including possible exemptions) go to: ENGLISH LANGUAGE PROFICIENCY
PROGRAM SPECIFIC REQUIREMENTS
Doctor of Philosophy (Ph.D.)
A student entering the
Ph.D. program will usually have a Master's degree. The student will
normally take at least three courses in each term of the first year, at
least two in each term of the second year. Students must take an Advisory examination at the beginning of the first term.
When a student has completed two winter session terms as a provisional
candidate for the Ph.D., a decision must be made by the Council of the
Department of Mathematical and Statistical Sciences whether the student
may continue in the program. The successful student is entitled to
begin research on a dissertation. One year after passing the Entrance
Year, when most of the course work is completed and a thesis project
started and well-defined, the student will take the Candidacy
Examination. Here they will describe their project mentioning results
obtained and be questioned on their field of research by an advisory
committee. Following the acceptance of their dissertation by the
advisory committee the final public oral examination will be held.
Degrees of Doctor of
Philosophy ( Ph.D.):
- Pure Mathematics
- Statistical Machine Learning
do not offer a Ph.D. program in Biostatistics
Requirements for Doctor of Philosophy (Ph.D.)
To be admitted as a
provisional candidate for the Ph.D. a student must normally hold the
equivalent of a M.Sc. degree in Mathematical and Statistical Sciences
from the University of Alberta. In special circumstances an M.Sc.
student may be allowed to transfer to the Ph.D. program, bypassing the
master’s degree. The residency requirement for a Ph.D. candidate is
full-time registration for 2 academic years.
Master of Science (M.Sc.) (Thesis or Course Based)
There are two programs
leading to the M.Sc. degree. The minimum requirements of the thesis program are the satisfactory completion of six single-term graduate
courses and a thesis. For the course-based program, the
minimum requirements are the satisfactory completion of eight
single-term graduate courses and an approved project. Normally the
project component for those specializing in Statistics will consist of
work on consulting problems. The M.Sc. degree requirements can be
completed in one year if the student pursues the course-based route;
students in the thesis program usually take slightly longer to complete
the degree. It is possible for a student to transfer to the Ph.D.
program without having completed the requirements of the M.Sc. degree.
The course-based M.Sc. degree is primarily intended as a terminal degree, to be followed by employment in a related occupation. For this reason, course-based M.Sc. students are not normally admitted with a full-time teaching assistantship. Students who plan to continue to a Ph.D. program, and then to a research-related career, are encouraged to enter the thesis-based M.Sc. program.
Degrees of Master of
Science ( M.Sc.):
- Pure Mathematics
- Statistical Machine Learning (Thesis Based Only)
Requirements for Master of Science (M.Sc.)
Candidates for the
M.Sc. degree will normally have a B.Sc. (Honors or Specialization)
degree or the equivalent from a recognized university, with a strong
background in applied or pure mathematics and/ or statistics. Students
with strong backgrounds in the area but specializing for the first time
will be required to take additional course work. The residency
requirement in all M.Sc. programs offered by the Department is
full-time registration for 2 four-month terms.
There is no specific
list of particular math or statistics courses required but the best
match would probably come from our Honors program in Mathematics or Statistics.
There are course-based
and thesis-based programs leading to the M.Sc. degree. The M.Sc. degree
requirements can be completed in one year if the student pursues the
non-thesis route; students in the thesis program usually take slightly
longer to complete the degree. It is possible for a student to transfer
to the Ph.D. program without having completed the requirements of the
Postgraduate Diploma in Statistics
The requirement of
this program is satisfactory completion of seven graduate courses. The
purpose of this program is to provide an organized package of courses
to those who are unable to undertake a graduate degree program. More
Areas of Research
|Department of Mathematical and Statistical Sciences
University of Alberta
632 Central Academic Building
Edmonton, AB T6G 2G1
Last modified Nov, 2008