Quantitative/Analytical courses are defined as courses which have either quantitative (numerical, geometric) or formal (deductive, probabilistic) reasoning as part of their primary subject matter, or make substantial use of such reasoning in practical problem solving critical evaluation, or analysis. A Quantitative/Analytical course is a requirement of all University baccalaureate degrees as per Credential and Course Criteria (pdf).
To qualify as a quantitative/analytical course, a course must have either quantitative (numerical, geometric) or formal (deductive, probabilistic) reasoning as part of its primary subject matter, or make substantial use of such reasoning in practical problem solving critical evaluation, or analysis.
Interpreting the definition
Mathematics courses already required in Math, the Sciences, Engineering, Business Administration and Economics, and statistics courses required in Social Science programs clearly qualify as quantitative/analytical courses, as do symbolic logic course offered in Philosophy.
Courses currently offered in programs such as Engineering, Physics, Chemistry, Biology, Business, Economics and other Social Science programs that contain a significant math or stats component would also be eligible for quantitative/analytical designation.
The third type of course eligible for quantitative/analytical designation will be designed specifically for students in other programs at Capilano University. The goal of such a course will not simply be to nurture traditional mathematical skills. Such courses will aspire to the greater challenge of deepening the understanding and appreciation of quantitative and formal reasoning, their ubiquitous utility and their creative potential. We view such course as:
(a) focusing on the relation between concepts and structures communicated through numbers and other systems of abstract representation (such as formal languages, programming languages, geometries, graphs), and
(b) fostering students’ ability to engage more effectively with the subject matter of their respective programs and practical everyday situations. Such course need not focus primarily on quantitative or formal reasoning methods but should give significant exercise to such techniques through model building and problem-solving, both in class and in course assignments.