# Major Concentration Mathematics for Management Students (39 credits)

Offered by: Management     Degree: Bachelor of Commerce

### 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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. Cayley-Hamilton theorem. Bilinear and quadratic forms. Inner product spaces, orthogonal diagonalization of symmetric matrices. Canonical forms.

Terms: Winter 2017

Instructors: Rebecca Patrias (Winter)

• MATH 242 Analysis 1 (3 credits)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

• Fall

• Prerequisite: MATH 141

• Restriction(s): Not open to students who are taking or who have taken MATH 254.

• MATH 243 Analysis 2 (3 credits)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

• Prerequisite: MATH 222.

• Corequisite: MATH 133.

• Restriction: Not open to students who have taken or are taking MATH 325.

• MATH 323 Probability (3 credits)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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 Asgharian-Dastenaei (Fall) Sanchayan Sen (Winter) Djivede Kelome (Summer)

• Prerequisites: MATH 141 or equivalent.

• Restriction: Intended for students in Science, Engineering and related disciplines, who have had differential and integral calculus

• Restriction: Not open to students who have taken or are taking MATH 356

• MATH 324 Statistics (3 credits) *

Offered by: Mathematics and Statistics (Faculty of Science)

### 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: Marie-Pier Côté (Fall) Masoud Asgharian-Dastenaei (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)

Offered by: Management (Desautels Faculty of Management)

### Overview

Management Science : A realistic experience of analytical models which have been successfully applied in several areas of managerial decision-making 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)

• Prerequisite: MGCR 271

• Prerequisite (Continuing Studies): MGCR 273

• Restriction: Not open to students who have taken MGCR 373

• Continuing Studies: CMA Requirement

* 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) **

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### Overview

Mathematics & Statistics (Sci) : Algebra of complex numbers, Cauchy-Riemann 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### Overview

Mathematics & Statistics (Sci) : First order equations, geometric theory; second order equations, classification; Laplace, wave and heat equations, Sturm-Liouville theory, Fourier series, boundary and initial value problems.

Terms: Winter 2017

Instructors: Peter Bartello (Winter)

• MATH 326 Nonlinear Dynamics and Chaos (3 credits)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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, Poincare-Bendixson theorem, bifurcations, Hopf bifurcation, the Lorenz equations and chaos.

Terms: Fall 2016

Instructors: Antony Raymond Humphries (Fall)

• MATH 340 Discrete Structures 2 (3 credits)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### 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 2016-2017 academic year.

Instructors: There are no professors associated with this course for the 2016-2017 academic year.

• MATH 410 Majors Project (3 credits)

Offered by: Mathematics and Statistics (Faculty of Science)

### Overview

Mathematics & Statistics (Sci) : A supervised project.

Terms: Fall 2016, Winter 2017, Summer 2017

Instructors: Djivede Kelome, Yi Yang, Jean-Christophe Nave, Gantumur Tsogtgerel, David Stephens (Fall) Djivede Kelome, Gantumur Tsogtgerel, Yi Yang (Winter) Djivede Kelome, Masoud Asgharian-Dastenaei, 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)

Offered by: Mathematics and Statistics (Faculty of Science)

### Overview

Mathematics & Statistics (Sci) : An introductory course in optimization by linear algebra, and calculus methods. Linear programming (convex polyhedra, simplex method, duality, multi-criteria 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) ***

Offered by: Mathematics and Statistics (Faculty of Science)

### Overview

Mathematics & Statistics (Sci) : Least-squares estimators and their properties. Analysis of variance. Linear models with general covariance. Multivariate normal and chi-squared distributions; quadratic forms. General linear hypothesis: F-test and t-test. Prediction and confidence intervals. Transformations and residual plot. Balanced designs.

Terms: Fall 2016

Instructors: David Stephens (Fall)

3 credits selected from:

Offered by: Management (Desautels Faculty of Management)

### 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)

Offered by: Management (Desautels Faculty of Management)

### 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 2016-2017 academic year.

Instructors: There are no professors associated with this course for the 2016-2017 academic year.

• MGSC 575 Applied Time Series Analysis Managerial Forecasting (3 credits)

Offered by: Management (Desautels Faculty of Management)

### Overview

Management Science : Management applications of time series analysis. Starting with ratio-to-moving average methods, the course deals successively with Census 2, exponential smoothing methods, the methodology introduced by Box and Jenkins, spectral analysis and time-series regression techniques. Computational aspects and applications of the methodology are emphasized.

Terms: This course is not scheduled for the 2016-2017 academic year.

Instructors: There are no professors associated with this course for the 2016-2017 academic year.

• Restriction: Not open to students who have taken MGSC 675.

• MGSC 578 Simulation of Management Systems (3 credits)

Offered by: Management (Desautels Faculty of Management)

### 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)