Last updated: June 24, 2004 @ 03:44PM

Mathematics

Chair
Hichem Ben-El-Mechaiekh

Professors Emeriti
Howard Bell, Velmer B. Headley, Charles F. Laywine, John P. Mayberry

Professors
Hichem Ben-El-Mechaiekh, Mei Ling Huang, Ronald A. Kerman, Eric R. Muller, Jan Vrbik, Thomas Wolf

Associate Professors
Stephen Anco, Henryk Fuks, Thomas A. Jenkyns, Yuanlin Li, William J. Ralph

Assistant Professors
Omar Kihel, Wai Kong (John) Yuen

Instructors
Dorothy Levay, Dorothy Miners

Mathematics Learning Resources

Manager
TBA

General Information

Administrative Assistant
Cathy Ugulini

905-688-5550, extension 3300
Mackenzie Chown J415
http://www.brocku.ca/mathematics/

The Department of Mathematics offers a unique program, Mathematics Integrated with Computers and Applications (MICA). This innovative program fully integrates computers and applications into a broad spectrum of courses that range over pure mathematics (the study of mathematics for its own sake), applied mathematics (mathematics for applications) and statistics. With its special focus on technology, the MICA program is especially suited for students desiring careers in applications of mathematics that involve computing. Within the MICA program, students can also form areas of concentration in pure mathematics or statistics.

Students in the MICA program get a solid grounding in mathematical theory and learn how to use computer and information technology to apply and present what they have learned. The core of the MICA program consists of MATH 1P40, 2F40 and 3F40 in which students will confront problems from pure and applied mathematics that require experimental and heuristic approaches. In dealing with such problems, students will be expected to develop their own strategies and make their own choices about the best combination of mathematics and computing required to obtain solutions.

The Computer Science and Mathematics Co-op program combines academic and work terms over a period of four and one-half academic years. Students spend one and one-half years in an academic setting studying the fundamentals of Computer Science and Mathematics prior to their first work placement. Successful completion of courses in the core areas of Computer Science and Mathematics provides the necessary academic background for the work experience. In addition to the current fees for courses in academic study terms, Computer Science and Mathematics Co-op students are assessed an administrative fee for each work term (see the Schedule of Fees).

Students admitted to the Computer Science and Mathematics Co-op program must follow the Co-op program schedule. Failure to adhere to the schedule may result in removal from the Computer Science and Mathematics Co-op program. Eligibility to continue in the Computer Science and Mathematics Co-op program is based on the student's major and non-major averages. A student with a minimum 70 percent major average and a minimum 60 percent non-major average may continue. A student with a major average lower than 70 percent will not be permitted to continue in the Computer Science and Mathematics Co-op program, but may continue in the non-co-op Computer Science and Mathematics stream. If a student subsequently raises his/her major average to 70 percent, the student may be readmitted only if approved by the Co-op Admissions Committee. For further information, see the Co-op Programs section of the Calendar.

The Computer Science and Mathematics Co-op program designation will be awarded to those students who have honours standing and who have successfully completed a minimum of twelve months of Co-op work experience.

The Department has a special interest in Mathematics Education and offers several programs and courses specifically for prospective teachers. These include both Concurrent and Consecutive Education Programs. See the section below on programs for future teachers.

Certain courses are required for any degree in Mathematics (see below). Because a Mathematics major needs both facility in dealing with mathematical theories and experience in the application of mathematics to real-world problems, each student should discuss his or her particular interests with faculty before selecting elective courses.

Program Notes
  1. All students must take three context credits: one Humanities context credit, one Science context credit and one Social Science context credit. Two credits must be used to satisfy context credit requirements in year 1.
  2. Students intending to pursue graduate studies in Pure Mathematics will find it essential to have MATH 4P11 and 4P12 or MATH 4P03 and 4P05 and desirable to have all of them.
  3. In all 20 credit degree programs, at least 12 credits must be numbered 2(alpha)00 or above, six of which must be numbered 2(alpha)90 or above and of these, three must be numbered 3(alpha)90 or above. In all 15 credit degree programs, at least seven credits must be numbered 2(alpha)00 or above, three of which must be numbered 2(alpha)90 or above.

Mathematics Integrated with Computers and Applications Honours Program (MICA)

Year 1
·   MATH 1P01, 1P02, 1P12 and 1P40
·   three elective credits (see program note 1)
Year 2
·   MATH 2F40, 2P03, 2P08, 2P12, 2P81 and 2P82
·   the Humanities context credit, Science context credit or Social Science context credit (not taken in Year 1)
·   one-half elective credit
Year 3
·   MATH 2P72 and 3F40
·   one and one-half MATH credits numbered 3(alpha)00 or above
·   two elective credits (see program note 3)
Year 4
·   Four MATH credits (see program notes 2 and 3)
·   one elective credit (see program note 3)

Mathematics Pass Program

Year 1
·   MATH 1P01, 1P02, 1P12 and 1P40
·   three elective credits (see program note 1)
Year 2
·   MATH 2F40 and 2P03
·   one of MATH 2P08 and 2P12, MATH 2P12 and 2P72, MATH 2P81 and 2P82
·   the Humanities context credit, Science context credit or Social Science context credit (not taken in Year 1)
·   one and one-half elective credits
Year 3
·   Three MATH credits numbered 3(alpha)00 or above
·   two elective credits

Combined Major Programs

Combined major programs have been developed by the Department of Mathematics in co-operation with each of these departments: Biological Sciences, Chemistry, Computer Science, Economics and Physics. Program requirements are listed in the calendar sections of the co-major discipline. Students may take a combined major in Mathematics and a second discipline. For requirements in the other discipline, the student should consult the relevant department/centre. It should be noted that not all departments/centres provide a combined major option.

Mathematics and Computer Science Co-op (Honours only)

Students admitted to the Co-op program must follow the program schedule as listed below. Failure to adhere may result in removal from the program.

Year 1
·   MATH 1P01, 1P02, 1P12 and 1P40
·   COSC 1P02, 1P03 and 1P12
·   one Science context credit
·   one-half elective credit
Year 2
Fall Term:
·   MATH 2P03 and 2P81
·   COSC 2P03, 2P13 and 2P90
·   SCIE 0N90
Winter Term:
·   COSC 0N01
Spring/Summer Sessions:
·   MATH 1P66 and 1P67
·   COSC 2P32
·   one-half COSC credit
Year 3
·   COSC 3F00
·   MATH 2F40 and 3F65
·   one Humanities context credit
·   one Social Science Context Credit
Spring/Summer Sessions:
·   COSC 0N02
Year 4
Fall Term:
·   COSC 0N03
Winter Term:
·   MATH 2P82, 3P60 and 4P61
·   COSC 2P50
·   one COSC credit (see program note 3)
Year 5
Fall Term:
·   One COSC credit (see program note 3)
·   one MATH credit (see program note 3)
·   one-half elective credit (see program note 3)

Programs and Courses for Future Teachers

The Department of Mathematics has identified courses that are particularly appropriate for students preparing to become teachers at either the elementary or secondary levels. Students should consult the Chair in the selection of courses.

Elementary
To help students meet Primary/Junior Pre-service Education admission requirements at Brock University - MATH 2P52.

Three credits for a specialization -
MATH 1F92, 1P66, 2P90, 2P93 and 3P91.

Secondary
For Mathematics as the first teachable subject (a minimum of five credits), an Honours degree in Mathematics is recommended.

For Mathematics as the second teachable subject (a minimum of three credits); for example: MATH 1P01, 1P02, 1P12, 2P90, 2P93 and one-half MATH credit.

Concurrent BSc/BEd

The Department of Mathematics and the Faculty of Education co-operate in offering two Concurrent BSc (Honours)/BEd programs and a BSc (Pass)/BEd program. The Mathematics BSc (Honours)/BEd programs combines the BSc Honours program or BSc Integrated Studies Honours program with the teacher education program for students interested in teaching at the Intermediate/Senior level (grades 7-12) and at the Junior/Intermediate level (grades 4-10). The BSc Integrated (Pass)/BEd combines the BSc Integrated Pass program with the teacher education program for students interested in teaching at the Junior/Intermediate level (grades 4-10). Refer to the Education - Concurrent BSc (Honours)/BEd (Intermediate/Senior), Education - Concurrent BSc Integrated Studies (Honours)/BEd (Junior/Intermediate) or Education Concurrent BSc Integrated Studies (Pass)/BEd (Junior/Intermediate) program listings for futher information.

Certificate in Statistics

The certificate program will be available to people (normally those with a degree in another discipline) who have completed the following:
·   at least one university Calculus credit
·   MATH 2P81, 2P82, 3P81, 3P82, 4P81 and 4P82
·   two other credits approved by the Mathematics department and normally selected from mathematics and statistics courses offered by the Mathematics Department.

Concentration Programs

Concentration in Pure Mathematics

Students may earn a Concentration in Pure Mathematics by successfully completing the following courses as part of the academic work leading to a BSc (Honours) in Mathematics (with the possible exception of MATH 2P72):
·   MATH 2P04, 2P12, 2P13, 3P03, 3P04, 3P12 and 3P13
·   MATH 2P71 (recommended) or 2P72
·   two credits from MATH 4F90, 4P03, 4P04, 4P11, 4P12, 4P71, 4P92, 4P93
The words "Concentration in Pure Mathematics" will be added to a student's official transcript when the student graduates with a BSc (Honours) in Mathematics having completed the above listed requirements.

Concentration in Statistics

Students may earn a Concentration in Statistics by successfully completing the following courses as part of the academic work leading to a BSc (Honours) in Mathematics:
·   MATH 2F40, 2P81, 2P82, 3F40, 3P81, 3P82, 4P81, 4P82, 4P84 and 4P85
The words "Concentration in Statistics" will be added to a student's official transcript when the student graduates with a BSc (Honours) in Mathematics having completed the above listed requirements.

Minor Programs

Minor in Mathematics

Students in other disciplines may obtain a Minor in Mathematics within their degree program by completing the following courses with a minimum 60 percent average:
·   MATH 1P01, 1P02, 1P12, 1P40 and 2F40
·   one elective credit numbered 2(alpha)00 or above
·   one elective credit numbered 3(alpha)00 or above
Minor Programs for Teachers

Students intending to become elementary teachers, who are in another discipline, can obtain a Minor in Elementary Teaching Mathematics within their degree program by completing the following courses with a minimum 60 percent overall average:
·   MATH 1P12, 1P66, 1P97, 1P98, 2P90, 2P93 and 3P91
·   one-half MATH credit
Students intending to become secondary teachers, who are in another discipline, can obtain a Minor in Secondary Teaching Mathematics within their degree program by completing the following courses with a minimum 60 percent overall average:
·   MATH 1P01, 1P02, 1P12, 1P40, 2P90 and 2P93
·   two MATH credits numbered 2(alpha)00 or above

Course Descriptions

Note that not all courses are offered in every session. Refer to the applicable term timetable for details.

# Indicates a cross listed course
* Indicates primary offering of a cross listed course

Prerequisites and Restrictions

Students must check to ensure that prerequisites are met. Students may be deregistered, at the request of the instructor, from any course for which prerequisites and/or restrictions have not been met.
MATH 1F92
Introductory Statistics
Types of scales; frequency distribution, mean, mode, median and measures of dispersion; elements of probability theory, probability distributions, nonparametric tests; normal, chi-squared, t- and F-distributions; means and variance tests; analysis of variance, correlation and regression, applications and use of a computer package.
Lectures, 3 hours per week.
Prerequisite: one grade 11 mathematics credit.
Note: designed for non-science majors. Not open to students with credit in any university mathematics or statistics course.

MATH 1P01
Calculus I
Applications of differential calculus, linearization and optimization; antiderivatives, definite integrals, the fundamental theorem of calculus, numerical integration; logarithms, exponentials, and inverse trigonometric functions, ordinary differential equations and their applications, improper integrals, the use of computer algebra systems.
Lectures, 4 hours per week; lab/tutorial, 1 hour per week.
Prerequisites: two OAC mathematics credits including OAC calculus or two grade 12 mathematics credits including MCB4U, or permission of instructor.

MATH 1P02
Calculus II
Applications of the definite integral: areas, volumes, and work; infinite series, Taylor's theorem, Taylor series; functions of several variables: and partial differentiation, limits and continuity, gradients, extrema with and without constraints, double integrals; the use of computer algebra systems to solve systems of equations, plot surfaces, compute partial derivatives and evaluate multiple integrals.
Lectures, 4 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 1P01.

MATH 1P12
Linear Algebra I
Introduction to finite dimensional real vector spaces; systems of linear equations: Gaussian elimination, matrix operations and inverses, determinants. Vectors in R2 and R3: dot product and norm, cross product, the geometry of lines and planes in R3; Euclidean n-space, linear transformations for Rn to Rm, eigenvalues and eigenvectors; selected applications and use of a computer algebra system.
Lectures, 4 hours per week.
Prerequisites: two grade 12 or OAC mathematics credits or permission of instructor.
Note: MCB4U recommended.

MATH 1P40
Applications I
Exploration of ideas and problems in algebra differential equations and dynamical systems using computers. Topics include number theory, integers mod p, roots of equations, fractals, predator-prey models and the discrete logistic equation for popular growth.
Lectures, 2 hours per week; lab, 2 hours per week.
Prerequisites: MATH 1P01 and 1P12.

MATH 1P66
Mathematics for Computer Science I
Development, analysis and applications of algorithms in computation; elementary logic, proofs; graphs and trees.
Lectures, 3 hours per week.
Prerequisite: one grade 12 or OAC mathematics credit.
Note: MCB4U recommended. Designed for students in Computer Science.

MATH 1P67
Mathematics for Computer Science II
Development, analysis and applications of algorithms in combinatorial analysis; discrete probability models; recursion; limiting procedures and summation; difference equations; introduction to automata theory.
Lectures, 3 hours per week.
Prerequisite: MATH 1P66.
Note: designed for students in Computer Science.

MATH 1P97
Differential and Integral Methods
Elementary functions, particularly the power function, the logarithm and the exponential; the derivative and its application; integration; approximation to the area under a curve; the definite integral; partial differentiation; simple differential equations; numerical methods; and the use of computer algebra systems.
Lectures, 4 hours per week.
Prerequisite: one grade 12 mathematics credit.
Note: MCB4U recommended. Designed for students in Biological Sciences, Biotechnology, Business, Earth Sciences, Environment, Economics, Geography and Health Sciences. Not open to students with credit in any university calculus course.

MATH 1P98
Basic Statistical Methods
Descriptive statistics; probability distributions, estimation; hypothesis testing; nonparametric tests; normal, chi-squared, t- and F-distributions; mean and variance tests; regression and correlation; and the use of statistical computer software.
Lectures, 3 hours per week.
Prerequisite: one grade 12 mathematics credit.
Note: designed for students in Biological Sciences, Biotechnology, Business, Earth Sciences, Economics, Environment, Geography and Health Sciences. Not open to students with credit in any university statistics course.

MATH 2F05
Applied Advanced Calculus
First and second order differential equations, vector functions, curves, surfaces; tangent lines and tangent planes, linear approximations, local extrema; cylindrical and spherical co-ordinates; gradient, divergence, curl; double and triple integrals, line and surface integrals; Green's theorem, Stokes' theorem, Gauss' theorem; elementary complex analysis. Emphasis on applications to physical sciences.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 1P02.
Completion of this course will replace previous assigned grade in MATH 2P03.

MATH 2F40
Mathematics Integrated with Computers and Applications II
Theory and application of mathematical models; discrete dynamical systems; time series and their application to the prediction of weather and sunspots; Markov chains; empirical models using interpolation and regression; continuous stochastic models; simulation of normal, exponential and chi-square random variables; queuing models and simulations.
Lectures, lab, 4 hours per week.
Prerequisites: MATH 1P02 and 1P40.

MATH 2P03
Calculus III
Multivariable integration, polar, cylindrical and spherical coordinates, vector algebra, parameterized curves and surfaces, vector calculus, arc length, curvature and torsion, projectile and planetary motion, line integrals, vector fields, Green's theorem, Stokes' theorem, the use of computer algebra systems to manipulate vectors, plot surfaces and curves, determine line integrals and analyze vector fields.
Lectures, 3 hours per week, lab/tutorial, 1 hour per week.
Prerequisite: MATH 1P02 .

MATH 2P04
Basic Concepts of Analysis
Sets; mappings, count ability; properties of the real number system; inner product, norm, and the Cauchy-Schwarz inequality; compactness and basic compactness theorems (Cantor's theorem, the Bolzano-Weierstrass theorem, the Heine-Borel theorem); connectedness; convergence of sequences; Cauchy sequences; continuous and uniformly continuous functions.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2P03.

MATH 2P08
Ordinary Differential Equations
Linear and nonlinear differential equations and autonomous systems; analytical and numerical solution methods, basic existence and uniqueness theory, qualitative analysis of solutions including periodic cycles and steady-states, attractors, chaos, asymptotic behavior; modeling and applications of differential equations.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisites: MATH 1P02 and 1P12.

MATH 2P12
Linear Algebra II
Finite dimensional real vector spaces and inner product spaces; matrix and linear transformation; eigenvalues and eigenvectors; the characteristic equation and roots of polynomials; diagonalization; complex vector spaces and inner product spaces; selected application.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 1P12.

MATH 2P13
Abstract Linear Algebra
Vector spaces over fields; linear transformations; diagonalization and the Cayley-Hamilton theorem; Jordan canonical form; linear operators on inner product spaces; the spectral theorem; bilinear and quadratic forms.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2P12.

MATH 2P52
Principles of Mathematics for Primary and Junior Teachers
Mathematical concepts and ideas in number systems; geometry and probability arising in the Primary and Junior school curriculum.
Lectures, seminar, 4 hours per week.
Restriction: students must have a minimum of 5.0 overall credits.
Note: designed to meet the mathematics admission requirement for the Primary/Junior Pre-service program of the Faculty of Education at Brock University. Not open to students holding credit in any grade 12 (Advanced)/OAC or university mathematics course.

MATH 2P71
Introduction to Combinatorics
Permutations, combinations, binomial and multinomial expansions; the inclusion-exclusion principle; recurrence relations; ordinary and exponential generating functions. Introduction to graph theory including isomorphism, trees, Euler and Hamilton path problems, planarity and map colouring. Pigeonhole principle and an introduction to classical Ramsey theory.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Prerequisites: two grade 12(OAC) mathematics credits or permission of the instructor.

MATH 2P72
Discrete Optimization
Problems and methods in discrete optimization. Linear programming: problem formulation, the simplex method, software, and applications. Network models: assignment problems, max-flow problem. Directed graphs: topological sorting, dynamic programming and path problems, and the travelling salesman's problem. General graphs: Eulerian and Hamiltonian paths and circuits, matchings.
Lectures, 3 hours per week; lab, 1 hour per week.
Prerequisite: MATH 1P12.
Completion of this course will replace previous assigned grade in MATH 2P60.

MATH 2P75
Introductory Financial Mathematics
Applications of mathematics to financial markets. Models for option pricing, rates of interest, price/yield, pricing contracts and futures, arbitrage-free conditions, market risk, hedging and sensitivities, volatility; stock process as random walks and Brownian motions; Black-Scholes formula; finite difference methods and VaR.
Lectures, lab, 4 hours per week.
Prerequisites: MATH 1P97 and 1P98.

MATH 2P81
Probability
Probability, events, algebra of sets, independence, conditional probability, Bayes' theorem. Random variables and their univariate, multivariate, marginal and conditional distributions. Expected value of a random variable, the mean, variance and higher moments, moment generating function, Chebyshev's theorem. Discrete and continuous distributions. Transforming random variables, central limit theorem and its applications.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2F05 or 2P03.
Note: MATH 2F05 or 2P03 may be taken concurrently.

MATH 2P82
Mathematical Statistics
Random sample, sampling distributions of sample mean and variance. Law of large numbers and central limit theorem. Chi-square, t, F distributions. Order statistics. Unbiased, consistent, efficient and robust estimators. Moments, maximum likelihood and Bayesian estimation. Confidence intervals. Hypothesis testing,, power function, Neyman-Pearson Lemma, likelihood-ratio test. Linear regression and correlation analysis. Analysis of variance. Nonparametric methods.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2P81.

MATH 2P90
Euclidean and Non-Euclidean Geometry I
The development of Euclidean and non-Euclidean geometry from Euclid to the 19th century. The deductive nature of plane Euclidean geometry as an axiomatic system, the central role of the parallel postulate and the general consideration of axiomatic systems for geometry in general and non-Euclidean geometry in particular. Introduction to transformation geometry.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: one MATH credit.
Completion of this course will replace previous assigned grade in MATH 2P50.

MATH 2P93
Great Moments in Mathematics I
Triumphs in mathematical thinking emphasizing many cultures up to 1000 AD. Special attention is given to analytical understanding of mathematical problems from the past, with reference to the stories and times behind the people who solved them. Students will be encouraged to match wits with great mathematicians by solving problems and developing activities related to their discoveries.
Lectures, 4 hours per week.
Prerequisite: one MATH credit.
Completion of this course will replace previous assigned grade in MATH 2P51.

MATH 2P98
Applied Statistics
Single-factor and factorial experimental design methods; nested-factorial experiments. Simple and multiple linear regression methods, correlation analysis, indicator regression; regression model building and transformations. Contingency tables, binomial tests, nonparametric rank tests. Simple random and stratified sampling techniques, estimation of sample size and related topics.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 1F92 or 1P98.

MATH 3F40
Mathematics Integrated with Computers and Applications III
Advanced applications of mathematics involving computers. Topics may include deterministic models; equilibrium; optimal control; probabilistic models; models from physics such as the n-body problem, the heat equation and finite element methods, and the driven pendulum; image compressing; genetic algorithms; neural nets; optimization and stochastic processes.
Lectures, lab, 4 hours per week.
Prerequisites: MATH 2P03, 2F40 and 2P82.
Co-requisite: MATH 2P72.
Note: projects demonstrating creative application of the course content.

MATH 3F65
Mathematical Methods for Computer Science
Applied probability, Markov chains, Poisson and exponential processes, renewal theory, queuing theory, applied differential equations. Networks, graph theory, reliability theory, NP-completeness.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Prerequisites: MATH 1P12, 1P66, 1P67 and 1P97.

MATH 3P03
Real Analysis
Approximation of functions by algebraic and trigonometric polynomials (Taylor and Fourier series); Weierstrass approximation theorem; Riemann integral of functions on Rn, the Riemann-Stieltjes integral on R; improper integrals; Fourier transforms.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Prerequisite: MATH 2P04.

MATH 3P04
Complex Analysis
Algebra and geometry of complex numbers, complex functions and their derivatives; analytic functions; harmonic functions; complex exponential and trigonometric functions and their inverses; contour integration; Cauchy's theorem and its consequences; Taylor and Laurent series; residues.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Prerequisite: MATH 2F05 or 2P03.

MATH 3P08
Advanced Differential Equations
Linear second-order differential equations. Integral transform methods, series solutions, special functions (Bessel, Legendre, Laguerre, Hermite). Boundary value problems and general Sturm-Liouville theory, orthogonal functions, series expansions. Linear autonomous systems and phase plane analysis. Emphasis on applications to physical sciences.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2F05 or 2P08.

MATH 3P09
Partial Differential Equations
First-order equations and method of characteristics. Second-order linear equations, initial and boundary value problems for the heat equation, wave equation, and Laplace equation. Fourier series, cylindrical (Bessel) and spherical (Legendre) harmonic series. Eigenfunction problems and normal modes. Nonlinear wave equations. Emphasis on applications to physical sciences.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2F05 or 2P08.

MATH 3P12
Applied Algebra
Group theory with applications. Topics include modular arithmetic, symmetry groups and the dihedral groups, subgroups, cyclic groups, permutation groups, group isomorphism, frieze and crystallographic groups, Burnside's theorem, cosets and Lagrange's theorem, direct products and cryptography.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 1P12.

MATH 3P13
Abstract Algebra
Further topics in group theory: normal subgroups and factor groups, homomorphisms and isomorphism theorems, structure of finite abelian groups. Rings and ideals; polynomial rings; quotient rings. Division rings and fields; field extensions; finite fields; constructability.
Lectures, 3 hours per week; lab/tutorial 1 hour per week.
Prerequisite: MATH 3P12.

MATH 3P60
Numerical Methods
Survey of computational methods and algorithms; basic concepts (algorithm, computational cost, convergence, stability); roots of functions; linear systems; numerical integration and differentiation; Runge-Kutta method for ordinary differential equations; finite-difference method for partial differential equations; fast Fourier transform; Monte Carlo methods. Implementation of numerical algorithms in a scientific programming language.
Lectures, 3 hours per week; lab, 1 hour per week.
Prerequisites: MATH 1P02 and 1P12.

MATH 3P72
Continuous Optimization
Problems and methods in non-linear optimization. Classical optimization in Rn: inequality constraints, Lagrangian, duality, convexity. Non-linear programming. Search methods for unconstrained optimization. Gradient methods for unconstrained optimization. Constrained optimization. Dynamic programming.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisites: MATH 2F05 or 2P03; MATH 2P72 (2P60).

MATH 3P73
Game Theory
(also offered as ECON 3P73)
Applications of modelling, review of elementary decision theory and subjective probability theory, game theory (Nash equilibrium, two player NZS games, Nash cooperative solution), Shapley value, voting power, selected cases from economics and other applications.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2P72 (2P60) or ECON 3P91.

MATH 3P75
Theory of Financial Mathematics
Probability, Brownian motion, martin-gales, Markov processes, differential equations, finite difference and tree models used in financial mathematics of options; stocks; one-dimensional Ito processes, Black-Scholes for both constant and non-constant inputs, continuous time hedging, valuing American and exotic options.
Lectures, lab, 4 hours per week.
Prerequisites: MATH 1P12 and 2P82; MATH 2F05 or MATH 2P03 and 2P08.

MATH 3P81
Experimental Design
Analysis of variance; single-factor experiments; randomized block designs; Latin squares designs; factorial designs; 2f and 3f factorial experiments; fixed, random and mixed models; nested and nested-factorial experiments; Taguchi experiments; split-plot and confounded in blocks factorial designs; factorial replication; regression models; computational techniques and computer packages, related topics.
Lectures, 3 hours per week; lab, 1 hour per week.
Prerequisite: MATH 2P82.

MATH 3P82
Regression Analysis
Simple and multiple linear regression and correlation, measures of model adequacy, residual analysis, weighted least squares, polynomial regression, indicator variables, variable selection and model building, multicollinearity, time series, selected topics.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2P82.

MATH 3P90
Euclidean and NonEuclidean Geometry II
Topics in Euclidean and non-Euclidean geometry chosen from the classification of isometries in selected geometries, projective geometry, finite geometries and axiometic systems for plane Euclidean geometry.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisites: MATH 1P12 and 2P90 (2P50).
Completion of this course will replace previous assigned grade in MATH 3P50.

MATH 3P91
Mathematics at the Junior/Intermediate/Senior Level
A treatment of mathematics and its teaching and learning at the junior, intermediate and senior levels. A major portion of the course will involve directed projects.
Lectures, seminar, 4 hours per week.
Restriction: open to BSc/BEd MATH majors with a minimum of 9.0 overall credits.
Prerequisite: three MATH credits.
Note: students in the minor programs for Teachers may register. Contact the Mathematics Department.

MATH 3P93
Great Moments in Mathematics II
The development of modern mathematics from medieval times to the present. The course includes Fibonacci's calculation revolution, the disputes over cubic equations, Pascal and probability, Fermat's last theorem, Newton and Calculus, Euler and infinite series, set theory and the possibilities of inconsistencies in mathematics.
Lectures, 4 hours per week.
Prerequisites: MATH 1P02, 1P12 and 2P93.
Completion of this course will replace previous assigned grade in MATH 3P51.

MATH 3P97
Introductory Topology
Introduction to metric and topological spaces; connectedness, completeness, countability axioms, separation pro-perties, covering properties, metrization of topological spaces.
Lectures, 4 hours per week.
Prerequisites: MATH 2P04; MATH 2P12 and 2P13 or MATH 3P12 and 3P13.

MATH 3P98
Functional Analysis
Introduction to the theory of normed linear spaces, fixed-point theorems, Stone-Weierstrass approximation on metric spaces and preliminary applications on sequence spaces.
Lectures, 4 hours per week.
Prerequisite: MATH 3P97.

MATH 4F90
Honours Project
Independent project in an area of pure or applied mathematics, or mathematics education.
Restriction: open to MATH (single or combined) majors with either a minimum of 14.0 credits, a minimum 70 percent major average and a minimum 60 percent non-major average or approval to year 4 (honours) and permission of the instructor.
Note: carried out under the supervision of a faculty member. The supervisor must approve the topic in advance. Presentation of the project is required.

MATH 4P03
Advanced Real Analysis
Lebesgue integration on Rn; differentiation and absolute continuity; Fubini's theorem; Lp spaces, elementary theory of Banach and Hilbert spaces.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Prerequisite: MATH 3P03.

MATH 4P05
Introduction to Wavelets
Wavelets as an orthonormal basis for Rn, localized in space and frequency; wavelets on the real line; image compression (fingerprint files); wavelet-Galerkin numerical solution of differential equations with variable coefficients.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisites: MATH 2P08 and 2P12.
Completion of this course will replace previous assigned grade in MATH 4P04.

MATH 4P07
Topics in Differential Equations
Topics may include ordinary differential equations: existence and uniqueness theory, strange attractors, chaos, singularities. Partial differential equations: Cauchy-Kovalevski theorem, well-posedness of classical linear heat equation and wave equation, weak solutions, global existence, uniqueness, and asymptotic behaviour.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 3P08.
Completion of this course will replace previous assigned grade in MATH 4F08.

MATH 4P09
Topics in Nonlinear Partial Differential Equations
Topics may include nonlinear partial differential equations, exact solutions and symmetry methods, global existence of solutions, finite element methods. Quasilinear elliptic equations and variational inequalities. Nonlinear wave equations, solitons and solitary wave solutions. Integrable systems and their properties. Field equations in mathematical physics.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 3P09.
Completion of this course will replace previous assigned grade in MATH 4F08.

MATH 4P11
Topics in Groups and Rings
Advanced topics from group theory and ring theory. Topics may include the Sylow theorems, free groups, nilpotent and solvable groups and Galois theory.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 3P13.
Completion of this course will replace previous assigned grade in MATH 4F10.

MATH 4P12
Advanced Mathematical Structures
Topics may include modules, homological algebra, group algebra, algebraic geometry, lattice theory, graph theory and logic.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 3P13 or permission of the Department.
Completion of this course will replace previous assigned grade in MATH 4F10.

MATH 4P61
Theory of Computation
Regular languages and finite state machines: deterministic and non-deterministic machines, Kleene's theorem, the pumping lemma, Myhill-Nerode Theorem and decidable questions. Context-free languages: generation by context-free grammars and acceptance by pushdown automata, pumping lemma, closure properties, decidability. Turing machines: recursively enumerable languages, universal Turing machines, halting problem and other undecidable questions.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Restriction: open to COSC (single or combined) majors.
Prerequisite: MATH 1P67.
Note: MATH students may take this course with permission of Department.

MATH 4P71
Combinatorics
Review of basic enumeration including distribution problems, inclusion-exclusion and generating functions. Polya theory. Finite fields. Orthogonal Latin squares, affine and projective planes. Coding theory and cryptography.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Restriction: permission of the Department.
Note: while no specific course is an essential prerequisite, students should have competence in abstraction equivalent to that obtained by successful completion of MATH 3P12.

MATH 4P81
Sampling Theory
Theory of finite population sampling; simple random sampling; sampling proportion; estimation of sample size; stratified random sampling; optimal allocation of sample sizes; ratio estimators; regression estimators; systematic and cluster sampling; multi-stage sampling; errors in surveys; computational techniques and computer packages; related topics.
Lectures, 3 hours per week; lab, 1 hour per week.
Prerequisite: MATH 2P82.

MATH 4P82
Nonparametric Statistics
Order statistics, rank statistics, methods based on the binomial distribution, contingency tables, Kolmogorov Smirnov statistics, nonparametric analysis of variance, nonparametric regression, comparisons with parametric methods.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2P82.

MATH 4P84
Topics in Stochastic Processes and Models
Topics may include general stochastic processes, Markov chains and processes, renewal process, branching theory, stationary processes, stochastic models, Monte Carlo simulations, and related topics.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2P82.
Completion of this course will replace previous assigned grade in MATH 4F83.

MATH 4P85
Topics in Advanced Statistics
Topics may include advanced topics in stochastic processes and models, queueing theory, time series analysis, multivariate analysis, Bayesian statistics, advanced methods and theory in statistical inference, and related topics.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 2P82.
Completion of this course will replace previous assigned grade in MATH 4F83.

MATH 4P92
Topics in Number Theory and Cryptography
Topics may include algebraic number theory, analytic number theory and cryptography.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Restriction: permission of the Department.
Completion of this course will replace previous assigned grade in MATH 4F91.

MATH 4P93
Topics in Topology and Dynamical Systems
Topics may include point set topology, differential geometry, algebraic topology and dynamical systems.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite: MATH 3P97 or permission of the Department.
Completion of this course will replace previous assigned grade in MATH 4F91.