The Department has a range of undergraduate programs, offered under the auspices of the Faculty of Science: Majors, Honours, Co-operative Education, Combined Majors/Honours in Economics and Statistics, Mathematics and Statistics, Mathematical Sciences, and Computer Science and Statistics. In addition, students can complete a degree in statistics with a minor in another area, such as Economics or Commerce, with the approval of the Dean's Office in the Faculty of Science.
Students majoring in another area can minor in Statistics by completing 18 upper level STAT credits (MATH 302 can replace STAT 302). Information on minors can be found in the calendar.
For further information about academic aspects of the undergraduate program, please contact the ugradadv [at] stat.ubc.ca (subject: Undergraduate%20query) (Undergraduate Adviser) after first checking the FAQs.
For other types of information, such as registration issues, please contact the gradinfo [at] stat.ubc.ca (subject: Undergraduate%20inquiry) (Student Services Coordinator).
Have a concern or an idea that you'd like to discuss with fellow students? studentreps [at] stat.ubc.ca (E-mail the student representatives) on the department's Undergraduate Liaison Committee,
Get involved! Be a part of the UBC Undergraduate Statistics Society, an independent club that plans lots of great events of interest to students in Statistics. For more information, see the USS Facebook page.
Our undergraduate programs emphasize the role of statistics within the general framework of problem solving, and help students develop an understanding of the concepts of observation, hypothesis, evidence and validation. The programs help students develop critical statistical reasoning, with emphasis on the development of computational, mathematical and communication skills, both oral and written. Such an education enables a better understanding of the role of chance, that is, of uncertainty, in all aspects of life today. These skills at the undergraduate level are useful in many careers.
- the historical evolution of statistics along with its current directions;
- the scientific method and why statistics is essential in its implementation;
- the distinction between inductive and deductive inference along with an understanding of the role of probabilistic reasoning within statistics;
- the distinction between designed and observational studies in establishing cause and effect relationships;
- methods, including the use of randomization, of dealing with uncontrolled variation;
- the importance of design;
- the importance of good data and the determinants of data quality, including sampling and nonsampling errors;
- how observation is converted into information;
- the fundamental importance of variability along with its relationship to uncertainty and its impact on decision making;
- the meanings of probability;
- the various purposes of models including description, inference, and knowledge representation;
- a working knowledge of the processes involved in modelling, model fitting, model validation, and model improvements;
- the processes involved in formulating subject area questions in a statistical framework;
- the role statistics plays in broad areas of application, including actuarial science, environmental science, medical science, and industry, and in the shaping of public policy.