Faculty of
Science and Technology

Faculty of
Science and Technology

Mathematics 101 is intended for students who wish to upgrade their mathematics skills before or while attending a post-secondary institution. Students who successfully complete Mathematics 101 are generally permitted to pursue courses and programs that would otherwise require Pure Mathematics 30 as a prerequisite or corequisite.

The emphasis of this course is on using algebra and algebraic methods to solve mathematics problems. It also includes sections on functions of a single variable and trigonometry. As such, it provides a particular subset of mathematical skills that are often needed for study at the post-secondary level.

This course covers several areas of mathematics—including linear equations, functions, matrices, linear inequalities, linear programming, and game theory—with applications in economics, business, the social sciences and the life sciences.

MATH 215 gives students a working knowledge and understanding of descriptive and inferential statistics and how statistics is applied in the sciences, social sciences, and business.

Mathematics 216: Computer-oriented Approach to Statistics, is a three-credit, junior-level course designed to introduce the basic principles of statistical analysis, including organization and presentation of statistical data, probability theory and probability distributions, estimation of population parameters from sample data, hypothesis testing, and bivariate analysis.

MATH 244 is designed to introduce the basic mathematical skills needed to understand, analyse, and solve mathematical problems encountered in business and finance, and in investment decision making. There are no prerequisites for MATH 244; however, students are expected to be able to perform the basic arithmetic operations—addition, subtraction, multiplication and division—with ease, and to have some familiarity with fractions, with algebraic operations, and with some basic mathematical principles.
MATH 244 is designed to introduce the basic mathematical skills needed to understand, analyse, and solve mathematical problems encountered in business and finance, and in investment decision making. There are no prerequisites for MATH 244; however, students are expected to be able to perform the basic arithmetic operations—addition, subtraction, multiplication and division—with ease, and to have some familiarity with fractions, with algebraic operations, and with some basic mathematical principles.
MATH 265 is an introductory calculus course covering real numbers, functions, continuity and limits, derivatives, curve sketching, optimization areas between curves, applications of the derivative, anti-derivatives, integrals, and areas.
MATH 265 is an introductory calculus course covering real numbers, functions, continuity and limits, derivatives, curve sketching, optimization areas between curves, applications of the derivative, anti-derivatives, integrals, and areas.
MATH 265 is an introductory calculus course covering real numbers, functions, continuity and limits, derivatives, curve sketching, optimization areas between curves, applications of the derivative, anti-derivatives, integrals, and areas.
Mathematics 481 is a three-credit, senior level mathematics course designed to provide a foundation in mathematical modeling, with an emphasis on numerical methods and simulation modeling. In Math 481 you will learn a variety of mathematical modeling approaches with applications in physical sciences, social sciences, finance, medicine, and business. As with its predecessor course Mathematics 480: Mathematical Modeling I, this course does not emphasize the presentation of new mathematical theory, but rather, it teaches the application of known mathematical methods to real-world cases. The course examines both observational and explanatory models, though the emphasis is on the latter. Topics include stochastic modeling approaches such as Markov Processes and Discrete Event simulation, as well as deterministic approaches that use ordinary differential equations and partial differential equations. We will also introduce the concepts of optimization and learn how to pose and solve optimization problems via various modeling approaches.
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