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Introduction to Statistics

Statistics makes sense of data using mathematical modelling to explain what is observed and to predict what is yet unknown. There are many areas in which statistics helps us to understand what is going on and to predict what is likely to happen in the future, from climate change to the economy to medicine.

Program Overview

The study of Statistics involves learning statistical processes and techniques, including collecting data, choosing methods, and communicating results. Students will take part in research and projects while working with visiting experts, research centres, and potential employers. Statistics can be studied in a wide range of degrees to add data knowledge to other interests.

Courses

• Statistics major
  • Bachelor of Arts: complete the following courses:
    • 100-level: MATH103 Mathematics 1B, one 100-level STAT course (or above)
    • 200-level: STAT213 Statistical Inference, STAT211 Random Processes OR STAT221 Introduction to Statistical Computing Using R, one 200-level STAT course
    • 300-level: three courses chosen from the options, one 300-level STAT course
  • Bachelor of Science: complete the following courses:
    • 100-level: MATH103 Mathematics 1B OR (200-level) DATA203 Data Science Multivariable Methods
    • 200-level: STAT213 Statistical Inference, STAT211 Random Processes OR STAT221 Introduction to Statistical Computing Using R, one 200-level STAT course
    • 300-level: three courses chosen from the options, one 300-level STAT course
• Statistics minor
  • Complete 75 points in 100 to 300-level STAT courses, with at least 45 points above 100-level

Career Opportunities

Statistics opens up career possibilities in many industries, such as finance and insurance, business, government, and research. Career pathways could include:

• Epidemiologist
• GIS expert
• Data analyst
• Risk surveyor

Research Areas

Students will have the opportunity to work on research projects and collaborate with visiting experts, research centres, and potential employers. The program covers a wide range of topics, including statistical inference, random processes, and statistical computing using R.