Statistics
Head: Dr. Saman Muthukumarana 
Grad Chair: Dr. Po Yang
Campus Address/General Office: 206 Biological Sciences (Temporary Location)
Telephone: 204-474-9826
Email Address: grad-program@stats.umanitoba.ca
Website: umanitoba.ca/science/statistics
Academic Staff: Please refer to the Statistics website for academic staff information.

Statistics Program Information

The University of Manitoba offers graduate programs in statistics leading to the Master of Science and Doctor of Philosophy degrees. Applications are encouraged from students with strong interest in statistics, mathematics or related fields.

Admission Information

Admission to the Faculty of Graduate and Postdoctoral Studies

Application and Admission Procedures are found in the Academic Guide.

Admission requirements for Master’s students are found in the Master’s Degrees General Regulations section of the Guide.

Statistics M.Sc. Admission Requirements

Completion of a B.Sc. degree in Statistics is usually required for admission to the Master's program.

Pre-Master's Option

This unit offers a Pre-Master’s program of study. The Pre-Master’s program of study is intended to bring a student’s background up to the equivalent of the required 4-year degree in the major department/unit, and to provide the student with any necessary prerequisites for courses to be taken in the Master’s program. Completing the Pre-Master’s program does not guarantee acceptance to the Master’s program.

Application Information

Students should complete and submit their online application with supporting documentation by the date indicated on the Statistics M.Sc. program of study page.

Degree Requirements

The Master’s degree may be earned in one of three ways:

Submission of a Thesis

Submission of a Practicum

Course Work Option

Students are also expected to take part in laboratory instruction and department seminars.

Expected Time to Graduate: 1-2 years, depending on the option selected. 

Registration Information

Students should familiarize themselves with the Faculty of Graduate and Postdoctoral Studies ‘GRAD’ courses applicable to their program. If you have questions about which GRAD course(s) to register in, please consult your home department/unit.

All new and returning graduate students in the Department of Statistics must consult with the grad chair and the graduate program assistant prior to attempting to register.

All students must consult with their advisor prior to registration and present a completed registration form to 318 Machray Hall. Any changes, after the initial registration, must also be approved by the advisor. 

Regulations

Students must meet the requirements as outlined in both Supplementary Regulation and BFAR documents as approved by Senate.

Supplementary Regulations

Individual units may require specific requirements above and beyond those of the Faculty of Graduate and Postdoctoral Studies, and students should consult unit supplementary regulations for these specific regulations. 

Bona Fide Academic Requirements (BFAR)

Bona Fide Academic Requirements (BFAR) represent the core academic requirements a graduate student must acquire in order to gain, and demonstrate acquisition of, essential knowledge and skills.

All students must successfully complete:

• GRAD 7300 prior to applying to any ethics boards which are appropriate to the student’s research or within the student’s first year, whichever comes first; and
• GRAD 7500 within the first term of registration;

unless these courses have been completed previously, as per Mandatory Academic Integrity Course and Mandatory Research Integrity Online Course.

Students must also meet additional BFAR requirements that may be specified for their program.

General Regulations

All students must:

• maintain a minimum degree grade point average of 3.0 with no grade below C+,
• meet the minimum and not exceed the maximum course requirements, and
• meet the minimum and not exceed the maximum time requirements (in terms of time in program and lapse or expiration of credit of courses).

Courses

Statistics