- K. Butler, B.Sc. (Birmingham), M.Sc., Ph.D. (Simon Fraser), Assistant Professor, Teaching Stream
- S. Damouras, B.Sc. (Athens Univ. of Econ. and Bus.), M.Sc. (Warwick), Ph.D. (Carnegie Mellon), Associate Professor, Teaching Stream
- M. Evans, B.Sc. (Western Ontario), M.Sc., Ph.D. (Toronto), Professor
- S. Kang, B.Sc., M.Sc. (Chonnam National University, South Korea), M.Sc., Ph.D. (Toronto), Associate Professor, Teaching Stream
- D. Roy, B.Sc., M.Eng., Ph.D. (MIT), Associate Professor
- M. Samarakoon, B.Sc. (Colombo), M.Sc. (Alberta), Ph.D. (Toronto), Associate Professor, Teaching Stream
- S. Shams, B.Sc. (Dhaka), M.A. (York), M.Sc., Ph.D. (Toronto), Assistant Professor, Teaching Stream
- Q. Sun, B.Sc. (Science & Technology, China), Ph.D. (North Carolina), Assistant Professor
- B. Virag, B.A. (Harvard), M.A., Ph.D. (Berkeley), Professor
- L. Wang, B.Sc. (Peking), Ph.D. (Washington), Assistant Professor
- L. Wong, B.Sc., M.Phil. (Hong Kong), Ph.D. (Washington), Assistant Professor
Associate Chair: M. Evans (416-287-7274) Email: email@example.com
Probability and Statistics have developed over a period of several hundred years as attempts to quantify uncertainty. With its origins in modelling games of chance, probability theory has become a sophisticated mathematical discipline with applications in such fields as demography, genetics and physics.
Statistics is concerned with the proper collection and analysis of data, both to reduce uncertainty and to provide for its assessment via probability. Applications range from pre-election polling to the design and analysis of experiments to determine the relative efficacies of different vaccines.
STAB22H3 and STAB27H3 serve as a non-technical introduction to statistics. These courses are designed for students from disciplines where statistical methods are applied. STAB52H3 is a mathematical treatment of probability. STAB57H3 is an introduction to the methods and theory of statistical inference. The C-level courses build on the introductory material to provide a deeper understanding of the statistical methodology and of its practical implementation.
Admission to Statistics Programs
Beginning in 2018-19 there are admissions criteria for the Major/Major (Co-op) Program in Statistics. Details and information on how to apply for admission to these programs are found in the program descriptions below.
Combining Statistics and Economics Programs
Students who wish to combine studies in statistics and economics should consult the Economics for Management Studies section of the Calendar for information on the economics programs and restrictions on the order in which courses must be taken.
Double Degrees: BBA/BSc
The Department of Computer and Mathematical Sciences, in partnership with the Department of Management, offers the following Double Degree programs:
- Double Degree: BBA, Specialist program in Management and Finance/Honours BSc, Specialist program in Statistics, Quantitative Finance Stream
- Double Degree: BBA, Specialist (Co-op) program in Management and Finance/Honours BSc, Specialist (Co-op) program in Statistics, Quantitative Finance Stream
The Double Degree programs create an accelerated pathway for students who would otherwise have to complete two separate Specialist programs. They explicitly focus on finance and quantitative methods, providing students with a thorough education in both the business and the quantitative aspects of the financial industry. The Double Degree Programs take advantage of existing synergies to allow students to complete both undergraduate programs and degrees within five years without compromising their learning experience. Students will complete a total of 25.0 credits and, for those enrolled in the Double Degree (Specialist Co-op programs), students must also complete three mandatory Co-op work terms. For more information, including Admission and Program requirements, see the Double Degree Programs section of the Calendar.
Program Combination Restrictions in Statistics
The Specialist/Specialist Co-op, Major/Major Co-op, Minor in Statistics, and Minor in Applied Statistics cannot be combined.
Experiential Learning and Outreach
For a community-based experiential learning opportunity in your academic field of interest, consider the course CTLB03H3, which can be found in the Teaching and Learning section of the Calendar.