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Program Requirements
Mentor: Professor A. Hundemer; Department of Mathematics and Statistics, Faculty of Science.
This program is comprised of 39 credits.
Students entering the Major Concentration in Mathematics are normally expected to have completed MATH 133, MATH 140, and MATH 141 or their equivalents. Otherwise, they will be required to make up any deficiencies in these courses over and above the 39 credits required by the program.
Required Courses (30 credits)

MATH 222 Calculus 3 (3 credits)
Overview
Mathematics & Statistics (Sci) : Taylor series, Taylor's theorem in one and several variables. Review of vector geometry. Partial differentiation, directional derivative. Extreme of functions of 2 or 3 variables. Parametric curves and arc length. Polar and spherical coordinates. Multiple integrals.
Terms: Fall 2016, Winter 2017, Summer 2017
Instructors: Stephen W Drury, Thomas F Fox (Fall) Alexander Garver (Winter) Geoffrey McGregor (Summer)

MATH 235 Algebra 1 (3 credits)
Overview
Mathematics & Statistics (Sci) : Sets, functions and relations. Methods of proof. Complex numbers. Divisibility theory for integers and modular arithmetic. Divisibility theory for polynomials. Rings, ideals and quotient rings. Fields and construction of fields from polynomial rings. Groups, subgroups and cosets; group actions on sets.
Terms: Fall 2016
Instructors: Jan Vonk (Fall)
Fall
3 hours lecture; 1 hour tutorial
Prerequisite: MATH 133 or equivalent

MATH 236 Algebra 2 (3 credits)
Overview
Mathematics & Statistics (Sci) : Linear equations over a field. Introduction to vector spaces. Linear mappings. Matrix representation of linear mappings. Determinants. Eigenvectors and eigenvalues. Diagonalizable operators. CayleyHamilton theorem. Bilinear and quadratic forms. Inner product spaces, orthogonal diagonalization of symmetric matrices. Canonical forms.
Terms: Winter 2017
Instructors: Rebecca Patrias (Winter)
Winter
Prerequisite: MATH 235

MATH 242 Analysis 1 (3 credits)
Overview
Mathematics & Statistics (Sci) : A rigorous presentation of sequences and of real numbers and basic properties of continuous and differentiable functions on the real line.
Terms: Fall 2016
Instructors: Axel W Hundemer (Fall)

MATH 243 Analysis 2 (3 credits)
Overview
Mathematics & Statistics (Sci) : Definition and properties of Riemann integral, Fundamental Theorem of Calculus, Taylor's theorem. Infinite series: alternating, telescoping series, rearrangements, conditional and absolute convergence, convergence tests. Power series and Taylor series. Elementary functions. Introduction to metric spaces.
Terms: Winter 2017
Instructors: Axel W Hundemer (Winter)

MATH 314 Advanced Calculus (3 credits)
Overview
Mathematics & Statistics (Sci) : Derivative as a matrix. Chain rule. Implicit functions. Constrained maxima and minima. Jacobians. Multiple integration. Line and surface integrals. Theorems of Green, Stokes and Gauss. Fourier series with applications.
Terms: Fall 2016, Winter 2017
Instructors: Charles Roth (Fall) Stephen W Drury (Winter)

MATH 315 Ordinary Differential Equations (3 credits)
Overview
Mathematics & Statistics (Sci) : First order ordinary differential equations including elementary numerical methods. Linear differential equations. Laplace transforms. Series solutions.
Terms: Fall 2016, Winter 2017, Summer 2017
Instructors: Xinyang Lu (Fall) John Mitry (Winter) Charles Roth (Summer)

MATH 323 Probability (3 credits)
Overview
Mathematics & Statistics (Sci) : Sample space, events, conditional probability, independence of events, Bayes' Theorem. Basic combinatorial probability, random variables, discrete and continuous univariate and multivariate distributions. Independence of random variables. Inequalities, weak law of large numbers, central limit theorem.
Terms: Fall 2016, Winter 2017, Summer 2017
Instructors: Masoud AsgharianDastenaei (Fall) Sanchayan Sen (Winter) Djivede Kelome (Summer)

MATH 324 Statistics (3 credits) *
Overview
Mathematics & Statistics (Sci) : Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.
Terms: Fall 2016, Winter 2017
Instructors: MariePier Côté (Fall) Masoud AsgharianDastenaei (Winter)
Fall and Winter
Prerequisite: MATH 323 or equivalent
Restriction: Not open to students who have taken or are taking MATH 357
You may not be able to receive credit for this course and other statistic courses. Be sure to check the Course Overlap section under Faculty Degree Requirements in the Arts or Science section of the Calendar.

MGSC 373 Operations Research 1 (3 credits)
Overview
Management Science : A realistic experience of analytical models which have been successfully applied in several areas of managerial decisionmaking like marketing, finance and IS. Emphasis on the formulation of problems, their solution approaches, limitations, underlying assumptions and practical use. Topics include: decision analysis, project management, simulation, linear and integer programming, sensitivity analysis.
Terms: Fall 2016
Instructors: Brian E Smith (Fall)
* Credits for MATH 324 are counted toward Management Core, where they replace MGCR 271. MGCR 271 cannot be taken for credit after credit for MATH 324 has been obtained.
Complementary Courses (9 credits)
6 credits selected from:

MATH 204 Principles of Statistics 2 (3 credits) **
Overview
Mathematics & Statistics (Sci) : The concept of degrees of freedom and the analysis of variability. Planning of experiments. Experimental designs. Polynomial and multiple regressions. Statistical computer packages (no previous computing experience is needed). General statistical procedures requiring few assumptions about the probability model.
Terms: Winter 2017
Instructors: Jose Andres Correa (Winter)
Winter
Prerequisite: MATH 203 or equivalent. No calculus prerequisites
Restriction: This course is intended for students in all disciplines. For extensive course restrictions covering statistics courses see Section 3.6.1 of the Arts and of the Science sections of the calendar regarding course overlaps.
You may not be able to receive credit for this course and other statistic courses. Be sure to check the Course Overlap section under Faculty Degree Requirements in the Arts or Science section of the Calendar.

MATH 316 Complex Variables (3 credits)
Overview
Mathematics & Statistics (Sci) : Algebra of complex numbers, CauchyRiemann equations, complex integral, Cauchy's theorems. Taylor and Laurent series, residue theory and applications.
Terms: Fall 2016
Instructors: John A Toth (Fall)

MATH 317 Numerical Analysis (3 credits)
Overview
Mathematics & Statistics (Sci) : Error analysis. Numerical solutions of equations by iteration. Interpolation. Numerical differentiation and integration. Introduction to numerical solutions of differential equations.
Terms: Fall 2016
Instructors: Tiago Miguel Saldanha Salvador (Fall)

MATH 319 Introduction to Partial Differential Equations (3 credits)
Overview
Mathematics & Statistics (Sci) : First order equations, geometric theory; second order equations, classification; Laplace, wave and heat equations, SturmLiouville theory, Fourier series, boundary and initial value problems.
Terms: Winter 2017
Instructors: Peter Bartello (Winter)

MATH 326 Nonlinear Dynamics and Chaos (3 credits)
Overview
Mathematics & Statistics (Sci) : Linear systems of differential equations, linear stability theory. Nonlinear systems: existence and uniqueness, numerical methods, one and two dimensional flows, phase space, limit cycles, PoincareBendixson theorem, bifurcations, Hopf bifurcation, the Lorenz equations and chaos.
Terms: Fall 2016
Instructors: Antony Raymond Humphries (Fall)

MATH 340 Discrete Structures 2 (3 credits)
Overview
Mathematics & Statistics (Sci) : Review of mathematical writing, proof techniques, graph theory and counting. Mathematical logic. Graph connectivity, planar graphs and colouring. Probability and graphs. Introductory group theory, isomorphisms and automorphisms of graphs. Enumeration and listing.
Terms: Winter 2017
Instructors: Sergey Norin (Winter)

MATH 407 Dynamic Programming (3 credits)
Overview
Mathematics & Statistics (Sci) : Sequential decision problems, resource allocation, transportation problems, equipment replacement, integer programming, network analysis, inventory systems, project scheduling, queuing theory calculus of variations, markovian decision processes, stochastic path problems, reliability, discrete and continuous control processes.
Terms: This course is not scheduled for the 20162017 academic year.
Instructors: There are no professors associated with this course for the 20162017 academic year.

MATH 410 Majors Project (3 credits)
Overview
Mathematics & Statistics (Sci) : A supervised project.
Terms: Fall 2016, Winter 2017, Summer 2017
Instructors: Djivede Kelome, Yi Yang, JeanChristophe Nave, Gantumur Tsogtgerel, David Stephens (Fall) Djivede Kelome, Gantumur Tsogtgerel, Yi Yang (Winter) Djivede Kelome, Masoud AsgharianDastenaei, Russell Steele (Summer)
Prerequisite: Students must have 21 completed credits of the required mathematics courses in their program, including all required 200 level mathematics courses.
Requires departmental approval.

MATH 417 Mathematical Programming (3 credits)
Overview
Mathematics & Statistics (Sci) : An introductory course in optimization by linear algebra, and calculus methods. Linear programming (convex polyhedra, simplex method, duality, multicriteria problems), integer programming, and some topics in nonlinear programming (convex functions, optimality conditions, numerical methods). Representative applications to various disciplines.
Terms: Fall 2016
Instructors: Tim Hoheisel (Fall)

MATH 423 Regression and Analysis of Variance (3 credits) ***
Overview
Mathematics & Statistics (Sci) : Leastsquares estimators and their properties. Analysis of variance. Linear models with general covariance. Multivariate normal and chisquared distributions; quadratic forms. General linear hypothesis: Ftest and ttest. Prediction and confidence intervals. Transformations and residual plot. Balanced designs.
Terms: Fall 2016
Instructors: David Stephens (Fall)
3 credits selected from:

MGSC 372 Advanced Business Statistics (3 credits) ***
Overview
Management Science : A practical managerial approach to advanced simple and multiple regression analysis, with application in finance, economics and business, including a review of probability theory, an introduction to methods of least squares and maximum likelihood estimation, autoregressive forecasting models and analysis of variance.
Terms: Fall 2016, Winter 2017
Instructors: Brian E Smith (Fall) Brian E Smith (Winter)

MGSC 479 Applied Optimization (3 credits)
Overview
Management Science : Applications of optimization models to management problems, including Linear Programming, Integer Programming and Nonlinear Programming.
Terms: This course is not scheduled for the 20162017 academic year.
Instructors: There are no professors associated with this course for the 20162017 academic year.
Prerequisite: MGSC 373.

MGSC 575 Applied Time Series Analysis Managerial Forecasting (3 credits)
Overview
Management Science : Management applications of time series analysis. Starting with ratiotomoving average methods, the course deals successively with Census 2, exponential smoothing methods, the methodology introduced by Box and Jenkins, spectral analysis and timeseries regression techniques. Computational aspects and applications of the methodology are emphasized.
Terms: This course is not scheduled for the 20162017 academic year.
Instructors: There are no professors associated with this course for the 20162017 academic year.

MGSC 578 Simulation of Management Systems (3 credits)
Overview
Management Science : Building simulation models of management systems. Design of simulation experiments and the analysis and implementation of results. Students are expected to design a complete simulation of a real problem using a standard simulation language.
Terms: Winter 2017
Instructors: Alexandre Ouellet (Winter)
** MATH 204 cannot be taken for credit after credit for MATH 324 has been obtained. The two courses can be taken concurrently. Students should consult the rules for credit for Statistics courses in the Course Overlap section.
*** MGSC 372 and MATH 423 cannot both be taken for program credit.