Course Catalog

Functions Modeling Change provides the algebraic and geometric skills needed to succeed in a Calculus course. The central topic is functions (in particular linear, polynomial, exponential and logarithmic), function notation and graphs, transformations, composition and inverses. Students also work with computers building mathematical models based on these functions, and implemented using graphing calculators, mathematical software and Excel.

Introduces differential and integral calculus. Develops the concepts of calculus as applied to polynomials, logarithmic, and exponential functions. Topics include: limits, derivatives, techniques of differentiation, applications to extrema and graphing; the definite integral; the fundamental theorem of calculus, applications; logarithmic and exponential functions, growth and decay; partial derivatives. Appropriate for students in the biological, management, computer and social sciences.

We will investigate how adjusting the standard mathematical rules can create new worlds which behave very differently. In particular, we will explore various ways to make infinity attainable, create imaginary numbers, and use four dimensions to better navigate in three dimensions.

May be taken twice for credit.

This course is intended to study the computational methodologies of Linear Programming and its variants and extensions, from the Transportation Problem and the Assignment Model to Network optimisation.
Various types of applications from the fields of Environmental Science (for the determination of the efficient use of scarce resources), Economics, Finance, Advertising... will be investigated and the methods by which useful results are obtainable - together with the reasoning behind the use of these methods - will be discussed.
Both the mathematical aspects and the use of a software package will be highlighted, each approach reinforcing the other. All classes will be held in the computer lab so as to enhance understanding, favour an interactive approach and develop new insights.
Prerequisite: MA 1010 or above

Familiarizes students with several types of multivariate statistics methods with respect primarily to applications and interpretations in the area of social sciences. This course will cover the data-analysis concepts and procedures used in applied and experimental psychology, economics, business and in general in social sciences. Emphasis will be given to the qualitative interpretation and manipulation of mathematical and statistical concepts, showing the students their effectiveness through concrete applications. Students will use appropriate software packages for labs and projects.

The continuation of MA1030, Calculus I. This course is appropriate for economics, mathematics, business and computer science majors and minors. Topics include: infinite series and applications; differential equations of first and second order and applications, functions of several variables, partial derivatives with applications, especially Lagrange multipliers. Includes the use of Mathematica.

Treats applications in economics and computer science, limited to Euclidean n-space. Topics include: the linear structure of space, vectors, norms and angles, transformations of space, systems of linear equations and their applications, the Gauss-Jordan method, matrices, determinants, eigenvalues and eigenvectors. Uses Mathematica for graphics and algorithms.

This course is designed to highlight discrete mathematical structures. Discusses propositional logic, proofs and mathematical induction, matrices of relations and digraphs, set theory and number bases, combinatorial analysis, graph theory and Boolean algebra.The prerequisite for this course is MA1010 or above or CS 1040.

Examines probability in its various components and through its diverse applications. Topics include: combinatorial analysis, axioms of probability, discrete random variables and distributions & continuous random variables and probability density functions, joint distribution functions, law of large numbers. The statistical concepts of conditioning, independence and expectation will be highlighted, as well as the notion of moments. Selected applications will shed light on the use of probability in various fields.