Fall 2020 Undergraduate Calendar


MATHEMATICS AND STATISTICS: COURSES

Students are reminded that, as indicated in the course descriptions, certain Mathematics and Statistics courses may not be available for credit in some or all of the degree programs.
All courses listed will not necessarily be offered each year.

ACTUARIAL SCIENCE

ACSC-4030 Derivative Markets I
Topics include financial derivatives, short selling, European and American options, hedging, arbitrage, forwards, futures, swaps, bond price models, binomial model. (Prerequisite: MATH-3980, STAT-3920, STAT-3950) (3 lecture hours per week.)

MATHEMATICS

MATH-1020.Mathematical Foundations
This course will cover mathematical logic, proof methods and development of proof techniques, mathematical induction, sets, equivalence relations, partial ordering relations and functions. (Prerequisite: One of COMP-1000, MATH-1250, MATH-1260 or MATH-1270.) (2 lecture hours, 2 tutorial hours per week.)

MATH-1250.Linear Algebra I
This course will cover linear systems, matrix algebra, determinants, n-dimensional vectors, dot product, cross product, orthogonalization, eigenvalues, eigenvectors, diagonalization and vector spaces. (Prerequisites: Both Ontario Grade 12 Advanced Functions (MHF4U) and Calculus and Vectors (MCV4U) or MATH-1280.) (Antirequisites: MATH-1260, MATH-1270.) (3 lecture hours, 2 tutorial hours per week.)

MATH-1260. Vectors and Linear Algebra
This course is for students without Ontario Grade 12 Calculus and Vectors (MCV4U). The course MATH-1250 is for students with MCV4U. This course will cover vectors, three-dimensional geometry, linear systems, matrix algebra, determinants, n- dimensional vectors, dot product, cross product, orthogonalization, eigenvalues, eigenvectors, diagonalization and vector spaces. (Prerequisite: Ontario Grade 12 Advanced Functions (MHF4U).) (Antirequisites: MATH-1250, MATH-1270.) (4 lecture hours, 2 tutorial hours per week.)

MATH-1270. Linear Algebra (Engineering)
This course will cover linear systems, linear transformations, matrix algebra, determinants, vectors in Rn, dot product, orthogonalization, diagonalization, eigenvectors and eigenvalues, in the context of and with an emphasis on a broad range of applications in Science and Engineering. (Prerequisite: MATH-1280 or both Ontario Grade 12 Advanced Functions (MHF4U) and Calculus and Vectors (MCV4U)) (Antirequisite: MATH-1250, or MATH-1260.) (3 lectures hours, 1 tutorial hour per week.)

MATH-1280. Access to Linear Algebra
This course will cover matrix algebra, linear systems, vectors, lines and planes in three- dimensional space, equations and inequalities in one variable and linear relations. This course serves as the prerequisite for MATH-1250 and MATH-1270. Majors in Science and majors in Engineering will not be given credit for this course. (3 lecture hours, 1 tutorial hour per week.)

MATH-1720.Differential Calculus
This course will cover trigonometric functions and identities, inverse trigonometric functions, limits and continuity, derivatives and applications, mean value theorem, indeterminate forms and l’Hôpital’s rule, antiderivatives and an introduction to definite integrals. This course is for students who have taken both Ontario Grade 12 Advanced Functions (MHF4U) and Ontario Grade 12 Calculus and Vectors (MCV4U). Students who do not have credit for MCV4U should take MATH-1760. (Prerequisites: Ontario Grade 12 Advanced Functions (MHF4U) and Ontario Grade 12 Calculus and Vectors (MCV4U) or MATH-1780.) (Antirequisite: MATH-1760.) (3 lecture hours, 2 tutorial hours per week.)

MATH-1730.Integral Calculus
This course will cover antiderivatives, the definite integral and the fundamental theorem of calculus, techniques of integration, applications, improper integrals, sequences and series, convergence tests, power series, Taylor and Maclaurin series, and polar and parametric coordinates. (Prerequisite: MATH-1760 or MATH-1720.) (3 lecture hours, 1 tutorial hour per week.)

MATH-1760. Functions and Differential Calculus
This course will cover a review of functions, trigonometric functions and identities, transcendental functions, inverse trigonometric functions, introduction to limits, continuity, derivatives and applications, mean value theorem, indeterminate forms and l’Hôpital’s rule, antiderivatives and an introduction to definite integrals. This course is for students who have taken Ontario Grade 12 Advanced Functions (MHF4U), but have not taken Ontario Grade 12 Calculus and Vectors (MCV4U). Students who have credit for MCV4U should take MATH-1720. The course is equivalent to MATH-1720 for all prerequisite purposes. (Prerequisite: Ontario Grade 12Advanced Functions (MHF4U).) (Antirequisite: MATH-1720.) (4 lecture hours, 2 tutorial hours per week.)

MATH-1780. Access to Differential Calculus
The course will cover straight lines, relations and functions, trigonometric functions, limits, derivatives, curve sketching, equations and inequalities, transformations, symmetry, exponential and logarithmic functions. This course serves as the prerequisite for MATH-1720 and MATH-1760. Majors in Science, majors in Engineering and students with at least 70% in Ontario Grade 12 Advanced Functions (MHF4U) will not be given credit for this course. (Antirequisites: MATH-1760, or MATH-1720) (3 lecture hours, 1 tutorial hour per week.)

MATH-1980. Mathematics for Business
An introduction to concepts and techniques of mathematics useful in business situations. Topics include mathematical modeling of qualitative scenarios, linear simultaneous equations, inequalities, exponential and logarithmic functions, graphical linear programming, and probability.This course is intended for students in Business Administration. May not be taken for credit in any program within the Faculty of Science or the Faculty of Engineering. (Prerequisite: Any grade 12 “U” math course, or MATH-1780.) (3 lecture hours, 1 tutorial hour per week.)

MATH-2250. Linear Algebra II
This course is a rigorous and proof-based study of linear systems, vector spaces, linear transformations, projections, pseudo-inverses, determinants, inner product spaces and applications. (Prerequisites: MATH-1020 and one of MATH-1250, MATH-1260 or MATH-1270.) (3 lecture hours, 1 tutorial hour per week.)

MATH-2251. Linear Algebra III
This course is a rigorous and proof-based study of
eigenvalues and eigenvectors, diagonalization, similarity problem, canonical form for real and complex matrices, positive definite matrices, computational methods for approximating solutions to systems of linear equations and eigenvalues. (Prerequisite: MATH-2250.) (3 lecture hours, 1 tutorial hour per week.)

MATH-2780. Vector Calculus
This course will cover quadric surfaces, vector differential calculus, functions of several variables, maximum and minimum problems, multiple integrals, vector differential operators, line and surface integrals, Green’s theorem, Stokes’ theorem and Gauss’ theorem. (Prerequisites: MATH-1730, and one of MATH-1250, MATH-1260 or MATH-1270.) (3 lecture hours, 1 tutorial hour per week.)

MATH-2790. Differential Equations
This course will cover first-order ordinary differential equations (ODEs), higher-order ODEs with constant coefficients, Cauchy-Euler equations, systems of linear ODEs, Laplace transforms, and applications to science and engineering. (Prerequisites: MATH-1730, and one of MATH-1250, MATH-1260 or MATH-1270.) (3 lecture hours, 1 tutorial hour per week.)

MATH-3150. Introduction to Graph Theory
This course will cover paths and cycles, bipartite graphs, graph isomorphisms, connectivity, Eulerian graphs, Hamiltonian graphs, trees, properties of trees, planarity, Euler’s formula, dual graphs, coloring graphs, Brooks’ theorem, coloring maps, chromatic polynomials, digraphs, matchings, Menger’s theorem, Hall’s theorem, and Tutte’s theorem. (Prerequisites: MATH-2250 or COMP-2310.) (3 lecture hours per week.)

MATH-3160. Combinatorics
This course will cover finite combinatorics, in
particular, the pigeonhole principle, permutations and combinations, binomial coefficients, the inclusion-exclusion principle, recurrence relations and generating functions, special counting sequences, Polya counting. (Prerequisites: MATH-1730 and MATH-1020.) (3 lecture hours per week.)

MATH-3200. Abstract Algebra
This course will cover an introduction to groups, rings and fields. (Prerequisite: MATH-2250 or MATH-3270.) (3 lecture hours per week.)

MATH-3270. Number Theory
This course will cover divisibility, primes, fundamental theorem of arithmetic, greatest common divisor, Euclidean algorithm, least common multiple, linear Diophantine equations, congruency, residue classes, Chinese remainder theorem, number theoretic functions, theorems of Euler, Fermat, Wilson, theory of primes, and quadratic residues. (Prerequisites: one of MATH-1250, MATH-1260 or MATH-1270, and MATH-1020.) (3 lecture hours per week.)

MATH-3550. Introduction to Fourier Series and Special Functions
This course will cover Fourier series, Sturm- Liouville problems, heat and wave equations, Laplace equation, weighted L2 -spaces and orthogonal bases, Gamma function, Bessel functions, Legendre polynomials and hypergeometric functions. (Prerequisite: MATH-2780 and MATH-2790.) (3 lecture hours per week.)

MATH-3580. Introduction to Analysis I
This course is a rigorous and proof-based study of supremum and infimum, the real number system, countable and uncountable sets, metric spaces, compact sets, connected sets, Cauchy sequences, completeness, limits and continuity, maximum and minimum on compact sets, intermediate value theorem, differentiation and the mean value theorem. (Prerequisites: MATH-1730, MATH-1020 and one of MATH-1250, MATH-1260 or MATH-1270.) (3 lecture hours, 1 tutorial hour per week.)

MATH-3581. Introduction to Analysis II
This course is a rigorous and proof-based study of Riemann-Stieltjes integral, sequences and series of functions, uniform and absolute convergence, equicontinuity, Arzela-Ascoli theorem, Stone- Weierstrass theorem, power series, and functions of several variables. (Prerequisite: MATH-3580.) (3 lecture hours, 1 tutorial hour per week.)

MATH-3590. Complex Variables
This course will cover complex numbers, analytic functions, exponential and logarithm functions, contour integration, Cauchy’s integral formula, series, Taylor and Laurent expansions, residue theory, applications to real integrals. (Prerequisite: MATH-2780; Corequisite: MATH-2790.) (3 lecture hours, 1 tutorial hour per week.)

MATH-3800. Numerical Methods
This course will cover iterative solution methods for nonlinear equations in one variable, Lagrange interpolation, cubic splines, Bezier curves, numerical differentiation and integration (quadrature), initial value problems, linear algebraic systems (direct methods) and Newton’s method for nonlinear systems. (Prerequisites: MATH-2780, MATH-2790, and one of MATH-1250, MATH-1260 or MATH-1270.) (3 lecture hours per week.)

MATH-3940. Numerical Analysis for Computer Scientists
This course is an introduction to the applications of numerical methods using computer-oriented algorithms such as finding roots, solving systems of equations, differentiation, integration and optimization. (Restricted to students in Computer Science.) (Prerequisites: COMP-1410, MATH-1730 and one of MATH-1250, MATH-1260 or MATH-1270.) (3 lecture hours per week)

MATH-3960. Linear Optimization
This course will cover the graphical solution of two variable linear programs, the tableau simplex algorithm, the revised simplex algorithm, linear programming theory, sensitivity analysis, the transportation problem, the assignment problem and integer programming. (Prerequisite: MATH-2250 or consent of instructor.) (Antirequisite: INDE-3120.) (3 lecture hours per week.)

MATH-3980. Theory of Interest
This course will cover measurement of interest, elementary and general annuities, amortization schedules and sinking funds, bonds, depreciation, depletion and capitalized cost. (Prerequisite: MATH-1730 or consent of instructor.) (3 lecture hours per week.)

MATH-4000. Topics in Mathematics
This course will cover advanced topics not covered in other courses. (May be repeated for credit when the topic is different.) (Prerequisite: consent of instructor.) (3 lecture hours per week.)
    MATH-4210.Ring Theory and Modules
    This course is designed to introduce students to the structure and theory of general rings and their modules. It will provide an appropriate foundation for more advanced graduate material in algebra. Topics covered will include: semisimple rings, Wedderburn-Artin Theorem, modules over a principal ideal domain, projective, injective and flat modules, introduction to homology theory. (Prerequisite: MATH-2251 and MATH-3200.) (3 lecture hours per week.)

    MATH-4220. Introduction to Group Theory
    This course will cover abstract groups, subgroups,quotient groups, products, isomorphism theorems, group actions, orbits, class equation, Sylow theorems, finitely generated abelian groups. (Prerequisites: MATH-2251 and MATH-3200.) (3 lecture hours per week.)

    MATH-4230. Introduction to Field Theory
    This course will cover polynomial rings, splitting fields, the fundamental theorem of Galois theory, Galois' criterion for solvability by radicals, algebraically closed fields and finite fields. (Prerequisites: MATH-2251 and MATH-3200.) (3 lecture hours per week.) (Cross-listed with MATH-8220)

    MATH-4300. General Topology
    Introduction to general set theoretic topology, including product and quotient spaces, continuity and homeomorphisms, nets and filters, separation and countability, compactness, connectedness. (Prerequisite: MATH-3581.) (3 lecture hours per week.)

    MATH-4570. Functional Analysis
    This course will cover normed and Banach spaces, bounded linear operators, dual spaces, Hahn- Banach theorem, uniform boundedness principle, open mapping theorem, Hilbert spaces, operators on Hilbert spaces, and weak and weak* topologies. (Prerequisite: MATH-4580.) (3 lecture hours per week.)

    MATH-4580. Measure Theory and Integration
    This course will cover measures, Lebesgue measure, Lebesgue integral, monotone and dominated convergence theorems, Fubini’s theorem, Lp-spaces, modes of convergence and Radon-Nikodym theorem. (Prerequisite: MATH-3581.) (3 lecture hours per week.)

    MATH-4581. Real Analysis II
    This course will cover metric spaces, topological spaces, Stone-Weierstrass theorem, Ascoli’s theorem and classical Banach spaces. (Prerequisite: MATH-4580.) (3 lecture hours per week.)

    MATH-4960. Portfolio Optimization
    This is a first course on Markowitz mean-variance portfolio optimization. The course will cover quadratic programming, parametric quadratic programming, the efficient frontier, the capital asset pricing model, Sharpe ratios and implied risk-free returns, portfolio optimization with constraints, and quadratic programming solution algorithms; also covered are professional writing and presentation skills and the use of optimization software. (Prerequisite: MATH-2251.) (3 lecture hours per week.) (Cross-listed with MATH-8820.)

    MATH-4980. Life Contingencies I
    This course will cover life contingencies, survival distributions and life tables, life insurance, life annuities, net premiums and net premium reserves. (Prerequisites: MATH-2780, MATH-2790, MATH-3980, and STAT-2950, or consent of instructor.) (3 lecture hours per week.)

    MATH-4981. Life Contingencies II
    This course will cover advanced life contingencies, risk theory, survival models, and construction and graduation of mortality tables. (Prerequisite: MATH-4980 or consent of instructor.) (3 lecture hours per week.)


    STATISTICS

    Undergraduate Statistics courses taught outside Mathematics and Statistics may not be taken for credit in any mathematics program.

    STAT-2910. Statistics for the Sciences
    This course will cover descriptive statistics, probability, discrete and continuous distributions, point and interval estimation, hypothesis testing, goodness-of-fit and contingency tables. (Prerequisite: Grade 12 “U” Advanced Level Mathematics (MHF4U, MCV4U, MDM4U) or Grade 11 Functions and Applications (MCF3M) or Grade 11 Functions (MCR3U).) (Course equivalencies and antirequisites as stated in the University of Windsor Senate Policy on Introductory Statistics Courses.) (May not be taken for credit after taking STAT-2920 or STAT-2950.) (3 lecture hours, 1 tutorial hour per week.)

    STAT-2920. Introduction to Probability
    This course will cover descriptive measures, combinatorics, probability, random variables, special discrete and continuous distributions, sampling distribution, and point and interval estimation. (Prerequisite: MATH-1730.) (3 lecture hours, 1 tutorial hour per week.)

    STAT-2950. Introduction to Statistics
    This course will cover distributions, point and interval estimation, hypothesis testing, contingency tables, analysis of variance, bivariate distributions, regression, correlation and non-parametric methods. (Prerequisite: STAT-2920.) (3 lecture hours, 1 tutorial hour per week.)

    STAT-3920. Probability
    The course will cover the axioms of the theory of probability, discrete and continuous distributions including binomial, Poisson, exponential, normal chi-square, gamma, t, and F distributions, multivariate distributions, conditional distributions, independence, expectation, moment generating functions, characteristic functions, transformation of random variables, order statistics, law of large numbers and central limit theorem. (Prerequisite: STAT-2950.) (3 lecture hours per week.)

    STAT-3950. Statistics
    This course will cover point and interval estimations, properties of estimators, methods of estimation, least squares estimation and linear models, Bayesian estimation, Rao-Blackwell theorem, tests of hypotheses, Neyman-Pearson Lemma and analysis of variance. (Prerequisite: STAT-3920.) (3 lecture hours per week.)

    STAT-3960. Stochastic Operations Research
    This course will cover deterministic dynamic programming, stochastic dynamic programming, queuing theory, Brownian motion, decision analysis and simulation. Optional topics are inventory theory and Markov processes. (Prerequisites: STAT-2920, MATH-1250 or MATH-1260, MATH-1730.) (Antirequisite: INDE-4120.) (3 lecture hours per week.)

    STAT-4000. Topics in Statistics
    This course will cover advanced topics in probability or statistics not covered in other courses. (Prerequisite: consent of instructor.) (3 lecture hours per week.) (May be repeated for credit when the topic is different.)

    STAT-4200 Actuarial Regression and Time Series
    This course introduces regression and time series analyses. Topics include multiple linear regression, least squares, model fitting, estimation, testing, matrix formulation, indicator variables, logistic regression, residual analysis, prediction intervals, times series, autoregressive models, moving average models, ARIMA models, fitting models, estimation and forecasting. (Prerequisite: STAT-2950.) (Anti-requisite: STAT-4550.) (3 lecture hours per week.)
      STAT-4410. Stochastic Processes
      This course covers discrete and continuous time Markov processes, renewal theory, branching processes, Brownian motion. (Prerequisite: STAT-2920 and STAT-2950, MATH-1250 and MATH-2790.) (3 lecture hours per week.)
        STAT-4460 Statistical Data Analysis
        This course takes a computer-oriented approach to equip students with the experience of data analysis, beginning with the design of experiments to the presentation of results. Depending on the background of the students, different topics will be emphasized. (Prerequisite: STAT-3920, STAT-3950 and STAT-4550 or consent of instructor.) (3 lecture hours per week.)

        STAT- 4470 Survival Analysis
        This course covers survivorship and hazard functions and their relationship to lifetime distributions and densities, types of censoring, the Kaplan-Meier and Nelson-Aalen estimators of the survivor and cumulative hazard functions, log rank tests, parametric survival time distributions and related regressions, semi-parametric regression models including the Cox’s PH model, and regression diagnostics. Further topics may include the counting process approach, recurrent event analysis, time dependent covariates, frailty models, sequential and group sequential techniques and statistical learning algorithms. (Prerequisite: STAT-3920 and STAT-3950.) (3 lecture hours per week.)

        STAT-4500. Generalized Linear Models
        This course is aimed at giving theoretical and methodological background for the analysis of discrete or continuous data using generalized linear models and other semi-parametric models where full distributional assumptions cannot be justified. (Prerequisite: STAT-3920 and STAT-3950.) (3 lecture hours per week.)

        STAT-4550. Regression Analysis
        This course covers simple and multiple linear regression, inference on regression parameters, residual analysis, stepwise regression, polynomial regression, diagnostics and remedial measures for multicollinearity and influential observations, weighted least squares, logistic regression, nonlinear regression. (Prerequisite: (STAT-2910 or STAT-2950) and MATH-1250.) (3 lecture hours per week.)

        STAT 4560 Statistical Consulting
        This course is aimed at training students on how to: (a) develop problem solving skills in applied statistics; (b) interact with clients from other scientific disciplines who seek statistical consultancy; and (c) improve skills for writing statistical data analysis reports. (Pre-requisites: STAT 4460 and STAT 4550; Anti-requisite: STAT 4600) (3 lecture hours a week.)

        STAT-4490. Discrete Multivariate Analysis
        This course is aimed at giving theoretical and methodological background for the analysis of discrete or continuous data using generalized linear models. The main topics covered are descriptive and inferential statistics for two-way and three-way contingency tables, generalized linear models for discrete responses, binary regression models (emphasizing logistic regression), multicategory logit models for nominal and ordinal responses, loglinear models for contingency tables, matched pairs, Modeling correlated, clustered responses, and Random effects: Generalized linear mixed model. (Prerequisite: STAT-3920 and STAT-3950).

        STAT-4980. Experimental Designs
        This course will cover ANOVA models without and with interactions, randomized block, Latin square, factorial, confounded factorial, balanced incomplete block, other designs and response surface methodology. (Prerequisite: STAT-2950 or STAT-3920.) (3 lecture hours per week.)

        STAT-4981. Sampling Theory
        This course will cover basic concepts, simple random and stratified sampling, ratio and regression methods, systematic and cluster sampling, multi-stage sampling, PPS sampling, and errors in surveys and sampling methods in social investigation. (Prerequisite: STAT-2950 or STAT-3920.) (3 lecture hours per week.)