Bachelor of Science - Mathematics and Statistics (Optional Co-op)

The mysteries of number theory and the geometry of curved spaces: these are areas with important applications in data security, computer design and cosmology. For ages, through research both pure and applied, mathematicians have made invisible and unsung contributions to advancements in science and technology, and the importance of mathematical training is increasingly recognized by employers and governments around the world.

In numerous rankings of careers, a significant portion of the top careers are math-intensive, and a degree in Mathematics provides excellent training. For instance, CareerCast annually ranks 200 careers according to environment, income, outlook, and stress, and Mathematician, Actuary, Statistician, Data Scientist, Information Security Analyst, and Computer Systems Analyst regularly rank in the top ten.

Two Options • Mathematics: The mathematics major degree is designed to prepare students for a career in industry, government or education. Mathematics students are urged to obtain some expertise in an area of application such as the physical sciences, computer science, engineering or business. • Statistics: The statistics major degree is designed to prepare students with a career in industry or government as well as to provide a background for graduate study. Statistics students are urged to obtain some expertise in an area of applications such as the physical sciences, forestry, or computer science.

Hands-on learning • There are summer employment opportunities (e.g. NSERCs Undergraduate Student Research Awards) for upper-year students • The Faculty of Science has a Co-op degree program

Skills students will acquire: • Creating coherent, logical arguments, and identifying/rectifying illogical ones • Manipulating intricate ideas and following sophisticated reasoning • The ability to relate abstract ideas to real-world situations • Confronting difficult, unsolved problems with precision, attention to detail, and confidence • Creating mathematical models of real-world problems, identifying key issues, assumptions, and limitations