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.
MATHEMATICS COURSES
MATH 1F92
Introductory Statistics
Describing and comparing data sets, linear regression analysis, basic probability theory, discrete probability distributions, binomial and normal distributions, Central Limit Theorem, confidence intervals and hypothesis tests on means and proportions, properties of t, F and chisquared distributions, analysis of variance, inference on regression. Emphasis on interpretation of numerical results for all topics. Use of Minitab.
Lectures, 3 hours per week.
Prerequisite(s): one grade 11 mathematics credit.
Note: designed for nonscience majors. Not open to students with credit in any university mathematics or statistics course.
MATH 1P01
Calculus Concepts I
Differential calculus with an emphasis on concepts and the use of both theory and computers to solve problems. Precalculus topics, limits, continuity and the intermediate value theorem, derivatives and differentiability, implicit differentiation, linear approximation, mean value theorem with proof and applications, max and min, related rates, curve sketching, l'Hospital's rule, antiderivatives, Riemann sums, FTC with proof, integration by substitution. Use of Maple.
Lectures, 4 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): two grade 12 mathematics credits including MCV4U or permission of the instructor.
Note: open to all, but primarily intended for mathematics majors and/or future teachers. Students must successfully complete a Mathematics skills test.
Completion of this course will replace previous assigned grade and credit obtained in MATH 1P05.
MATH 1P02
Calculus Concepts II
Integral calculus emphasizing concepts, theory and computers to solve problems. Further integration techniques. Applications to areas between curves, volumes, arc length and probabilities. Multivariable calculus: partial derivatives, optimization of functions of two variables. Sequences and series: convergence tests, Taylor and Maclaurin series and applications. Differential Equations: direction fields, separable equations, growth and decay, the logistic equation, linear equations. Use of Maple.
Lectures, 4 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 1P01, 1P05 or permission of instructor.
Note: open to all, but primarily intended for mathematics majors and/or future teachers.
Completion of this course will replace previous assigned grade and credit obtained in MATH 1P06.
MATH 1P05
Applied Calculus I
Differential calculus emphasizing problem solving, calculation and applications. Precalculus topics, limits, continuity, derivatives and differentiability, implicit differentiation, linear approximation, max and min, related rates, curve sketching, l'Hospital's rule, antiderivatives, integrals, FTC without proof, integration by substitution. Use of Maple.
Lectures, 4 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): two grade 12 mathematics credits including MCV4U or permission of the instructor.
Note: designed for students in the sciences, computer science, and future teachers. Students must successfully complete a Mathematics skills test.
Completion of this course will replace previous assigned grade and credit obtained in MATH 1P01.
MATH 1P06
Applied Calculus II
Integral calculus emphasizing problem solving, calculations and applications. Further techniques of integration. Applications to areas between curves, volumes, arc length and probabilities. Multivariable calculus: partial derivatives, optimization of functions of two variables. Sequences and series: convergence tests, Taylor and Maclaurin series and applications. Differential Equations: direction fields, separable equations, growth and decay, the logistic equation, linear equations. Use of Maple.
Lectures, 4 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 1P01 or 1P05.
Note: designed for students in the sciences, computer science, and future teachers.
Completion of this course will replace previous assigned grade and credit obtained in MATH 1P02.
MATH 1P12
Linear Algebra I
Introduction to finite dimensional real vector spaces; systems of linear equations: matrix operations and inverses, determinants. Vectors in R^{2} and R^{3}: Dot product and norm, cross product, the geometry of lines and planes in R^{3}; Euclidean nspace, linear transformations for R^{n} to R^{m}, complex numbers, selected applications and use of a computer algebra system.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): two grade 12 mathematics credits or permission of instructor.
MATH 1P20
Introduction to Mathematics
Essential mathematics skills required for university mathematics courses. Sets, real and complex numbers, solutions of inequalities and equations, functions, inverse functions, composition of functions, polynomial functions, rational functions, trigonometry, trigonometric functions, trigonometric identities, conic sections, exponential functions, logarithmic functions, polar coordinates, mathematical induction, binomial theorem, vectors and matrices.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): one grade 11 mathematics credit.
Note: not open to students with credit in any university calculus course.
MATH 1P40
Mathematics Integrated with Computers and 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, predatorprey models and the discrete logistic equation for popular growth.
Lectures, 2 hours per week; lab, 2 hours per week.
Prerequisite(s): MATH 1P01 or 1P05.
MATH 1P66
Mathematical Reasoning
Introduction to mathematical abstraction, logic and proofs including mathematical induction.
Lectures, 3 hours per week.
Prerequisite(s): one grade 12 mathematics credit.
Note: MCB4U recommended. Students may not concurrently register in MATH 2P04, 2P13 or 2P71.
Students will not receive earned credit for MATH 1P66 if MATH 2P04, 2P13 or 2P71 have been successfully completed
MATH 1P67
Mathematics for Computer Science
Development and analysis of algorithms, complexity of algorithms; recursion solving recurrence relations; relations and functions.
Lectures, 3 hours per week.
Prerequisite(s): MATH 1P66.
Note: designed for students in Computer Science.
MATH 1P97
Calculus With Applications
Lines, polynomials, logarithms and exponential functions; twosided limits; rates of change using derivatives; max and min of functions using derivatives; higher derivatives and concavity; area under a curve using integrals; optimization of functions of two variables using partial derivatives; growth and decay using differential equations; applications to many different disciplines; use of computer algebra systems.
Lectures, 4 hours per week.
Prerequisite(s): one grade 12 mathematics credit
Note: Designed for students in Biological Sciences, Biotechnology, Business, Earth Sciences, Economics, Environmental Geoscience, Geography and Health Sciences. Not open to students with credit in any university calculus course.
MATH 1P98
Practical Statistics
Descriptive statistics; probability of events; counting rules; discrete and continuous probability distributions: binomial, Poisson and normal distributions; Central Limit Theorem; confidence intervals and hypothesis testing; analysis of variance; contingency tables; correlation and regression; emphasis on realworld applications throughout; use of statistical computer software.
Lectures, 3 hours per week.
Prerequisite(s): one grade 12 mathematics credit or MATH 1P20.
Note: designed for students in Biological Sciences, Biotechnology, Business, Earth Sciences, Economics, Environmental Geoscience 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 coordinates; 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. Use of Maple.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 1P02 or 1P06.
Students will not receive earned credit in MATH 2F05 if MATH 2P03 has been successfully completed.
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 chisquare random variables; queuing models and simulations, use of a computer algebra system.
Lectures, lab, 4 hours per week.
Prerequisite(s): MATH 1P02 and 1P40 or permission of the instructor.
MATH 2P03
Multivariate and Vector Calculus
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(s): MATH 1P02, 1P06 or permission of the instructor.
MATH 2P04
Basic Concepts of Analysis
Sets; mappings, count ability; properties of the real number system; inner product, norm, and the CauchySchwarz inequality; compactness and basic compactness theorems (Cantor's theorem, the BolzanoWeierstrass theorem, the HeineBorel theorem); connectedness; convergence of sequences; Cauchy sequences; continuous and uniformly continuous functions.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2P03.
MATH 2P08
Ordinary Differential Equations
Linear and nonlinear differential equationsd Basic existence and uniqueness theory. Analytical and numerical solution methods; asymptotic behaviour. Qualitative analysis of autonomous systems including periodic cycles and steadystates. Examples of conservative systems and dissipative systems. Modelling and applications of differential equations.
Use of Maple.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 1P02, 1P06 or permission of the instructor.
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 applications; use of a computer algebra system and selected applications.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 1P12.
MATH 2P13
Abstract Linear Algebra
Vector spaces over fields; linear transformations; diagonalization and the CayleyHamilton 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(s): 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 Preservice program of the Faculty of Education at Brock University. Not open to students holding credit in any grade 12 or university mathematics course.
MATH 2P71
Introduction to Combinatorics
Counting, inclusion and exclusion, pigeonhole principle, permutations and combinations, derangements, binomial expansions , introduction to discrete probability; to graph theory, Eulerian graphs, Hamilton Cycles, colouring, planarity, trees.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Prerequisite(s): two 4U 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, maxflow problem. Directed graphs: topological sorting, dynamic programming and path problems, and the travelling salesman's problem. General graphs: Eulerian and Hamiltonian paths and circuits, and matchings.
Lectures, 3 hours per week; lab, 1 hour per week.
Prerequisite(s): MATH 1P12.
MATH 2P75
Introductory Financial Mathematics
Applications of mathematics to financial markets. Models for option pricing, rates of interest, price/yield, pricing contracts and futures, arbitragefree conditions, market risk, hedging and sensitivities, volatility; stock process as random walks and Brownian motions; BlackScholes formula; finite difference methods and VaR.
Lectures, lab, 4 hours per week.
Prerequisite(s): 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. Some common discrete and continuous distributions: Binomial, Poisson, hypergeometric, normal, uniform and exponential. Use of SAS, Maple or other statistical packages.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2P03 or permission of the instructor.
Note: may be taken concurrently with MATH 2P03.
MATH 2P82
Mathematical Statistics I
Transforming random variables, central limit theorem, law of large numbers. Random sample; sample mean and variance. Sampling from normal population: chisquare, t and F distributions, sample median and order statistics. Point and interval estimation of population parameters: method of moments, maximumlikelihood technique, consistent, unbiased and efficient estimators, confidence intervals. Hypotheses testing: type I and II errors, most powerful tests. Use of SAS, Maple or other statistical packages.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2P81.
MATH 2P90
Euclidean and NonEuclidean Geometry I
The development of Euclidean and nonEuclidean 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 nonEuclidean geometry in particular. Introduction to transformation geometry. Use of Geometer's Sketchpad.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): one MATH credit.
Completion of this course will replace previous assigned grade and credit obtained 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(s): one MATH credit.
Completion of this course will replace previous assigned grade and credit obtained in MATH 2P51.
MATH 2P95
Mathematics and Music
Scales and termperaments, history of the connections between mathematics and music, set theory in atonal music, group theory applied to composition and analysis, enumeration of rhythmic canons, measurement of melodic similarity using metrics, topics in mathematical music theory, applications of statistics to composition and analysis.
Lectures, 3 hours per week; lab/tutorial 1 hour per week.
Prerequisite(s): one of MATH 1P01, 1P02, 1P05, 1P06, 1P97; MATH 1P12 or permission of the instructor.
Completion of this course will replace previous assigned grade and credit obtained in MATH 2P31.
MATH 2P98
Applied Statistics
Singlefactor and factorial experimental design methods; nestedfactorial 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. Use of SAS, Maple or other statistical packages.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 1F92 or 1P98.
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, NPcompleteness.
Lectures, 3 hours per week.
Prerequisite(s): MATH 1P01 or 1P97; MATH 1P12, 1P66 and 1P67.
MATH 3P03
Real Analysis
Approximation of functions by algebraic and trigonometric polynomials (Taylor and Fourier series); Weierstrass approximation theorem; Riemann integral of functions on R^{n}, the RiemannStieltjes integral on R; improper integrals; Fourier transforms.
Lectures, 3 hours per week; tutorial, 1 hour per week.
Prerequisite(s): 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(s): MATH 2F05 or 2P03.
MATH 3P08
Advanced Differential Equations
Linear secondorder differential equations. Integral transform methods, series solutions, special functions (Gamma, Bessel, Legendre). Boundary value problems; introduction to SturmLiouville theory and series expansions by orthogonal functions.
Emphasis on applications to physical sciences. Use of Maple.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2F05 or 2P08.
MATH 3P09
Partial Differential Equations
Firstorder equations and method of characteristics. Secondorder 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. Use of Maple.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): 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(s): MATH 2P12 or permission of the instructor.
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(s): MATH 3P12.
MATH 3P51
Applied Mathematics with Maple
Blending mathematical concepts with computations and visualization in Maple. Modelling of physical flows, waves and vibrations. Animation of the heat equation and wave equation; applications including vibrations of rectangular and circular drums, heat flow and diffusion, sound waves. Eigenfunctions and convergence theorems for Fourier eigenfunction series. Approximations, Gibbs phenomena, and asymptotic error analysis using Maple.
Lectures, lab, 4 hours per week.
Prerequisite(s): MATH 2F40 and 2P03.
Completion of this course will replace previous assigned grade and credit obtained in MATH 3F40.
MATH 3P52
Partial Differential Equations in C++
Analytic solution of first order PDEs (characteristic ODE systems and their analytic solution) and the numerical solution of first and second order PDEs (discretization, derivation and comparison of different finite difference equations, stability analysis, boundary conditions), the syntax of the C++ programming language, projects in C++ solving PDEs numerically.
Lectures, lab, 4 hours per week.
Prerequisite(s): MATH 2F40 and 2P03.
Completion of this course will replace previous assigned grade and credit obtained in MATH 3F40.
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; RungeKutta method for ordinary differential equations; finitedifference 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.
Prerequisite(s): MATH 1P02 and 1P12 or permission of the instructor.
MATH 3P72
Continuous Optimization
Problems and methods in nonlinear optimization. Classical optimization in R^{n}: inequality constraints, Lagrangian, duality, convexity. Nonlinear 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.
Prerequisite(s): MATH 2F05 or 2P03; MATH 2P72 (2P60).
*MATH 3P73
Game Theory
(also offered as ECON 3P73)
Representation of Games. Strategies and payoff functions. Static and dynamic games of complete or incomplete information. Equilibria concepts: Nash, Bayesian Nash, and Perfect Bayesian Nash equilibria. Convexity concepts, fixed points for correspondences and minimax. Core and Shapley value of a game. Refinements and Applications.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2P72 or ECON 3P91.
MATH 3P75
Theory of Financial Mathematics
Probability, Brownian motion, martingales, Markov processes, differential equations, finite difference and tree models used in financial mathematics of options; stocks; onedimensional Ito processes, BlackScholes for both constant and nonconstant inputs, continuous time hedging, valuing American and exotic options.
Lectures, lab, 4 hours per week.
Prerequisite(s): MATH 1P12 and 2P82; MATH 2F05 or MATH 2P03 and 2P08.
MATH 3P81
Experimental Design
Analysis of variance; singlefactor experiments; randomized block designs; Latin squares designs; factorial designs; 2^{f} and 3^{f} factorial experiments; fixed, random and mixed models; nested and nestedfactorial experiments; Taguchi experiments; splitplot and confounded in blocks factorial designs; factorial replication; regression models; computational techniques and use of SAS, Maple or other statistical packages; related topics.
Lectures, 3 hours per week; lab, 1 hour per week.
Prerequisite(s): 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. Use of SAS, Maple or other statistical packages.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2P12 and 2P82 or permission of the instructor.
MATH 3P85
Mathematical Statistics II
Review of distributional theory. Convergence types. Some special and limiting distributions. Review of point and interval estimations. Efficiency, sufficiency, robustness and completeness. Bayesian estimations, credible intervals, prediction intervals. Basic theory of hypotheses testing: NeymanPearson lemma, likelihood ratio test, chisquare test, Test of stochastic independence. Normal models: quadratic forms, noncentral chisquare and noncentral Fdistributions. Use of SAS, Maple or other statistical packages.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2P82.
MATH 3P86
Applied Multivariate Statistics
Matrix algebra and random vector, sample geometry and random sampling, multivariate normal distribution, inference about mean, comparison of several multivariate means, multivariate linear regression model, principle components, factor analysis, covariance analysis, canonical correlation analysis, discrimination and classification, cluster analysis, computational techniques and use of SAS, Maple or other statistical packages and related topics.
Lectures, 3 hours per week; lab 1 hour per week.
Prerequisite(s): MATH 2P12 and 2P82 or permission of the instructor.
MATH 3P90
Euclidean and Non Euclidean Geometry II
Topics in Euclidean and nonEuclidean 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.
Prerequisite(s): MATH 1P12 and 2P90 (2P50).
Completion of this course will replace previous assigned grade and credit obtained 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 MATH (Honours) BSc/BEd(Intermediate/Senior), BA (Honours)/BEd (Junior/Intermediate), BSc (Honours)/BEd (Junior/Intermediate) and students in minor programs for teachers with a minimum of 9.0 overall credits.
Prerequisite(s): three MATH credits.
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.
Prerequisite(s): MATH 1P02, 1P12 and 2P93.
Completion of this course will replace previous assigned grade and credit obtained in MATH 3P51.
MATH 3P97
Introductory Topology
Introduction to metric and topological spaces; connectedness, completeness, countability axioms, separation properties, covering properties, metrization of topological spaces.
Lectures, 4 hours per week.
Prerequisite(s): MATH 2P04; MATH 2P12 and 2P13 or MATH 3P12 and 3P13.
MATH 3P98
Functional Analysis
Introduction to the theory of normed linear spaces, fixedpoint theorems, StoneWeierstrass approximation on metric spaces and preliminary applications on sequence spaces.
Lectures, 4 hours per week.
Prerequisite(s): 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 nonmajor 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 R^{n}; differentiation and absolute continuity; Fubini's theorem; L^{p} spaces, elementary theory of Banach and Hilbert spaces.
Lectures, 3 hours per week.
Prerequisite(s): MATH 3P03.
MATH 4P05
Introduction to Wavelets
Wavelets as an orthonormal basis for R^{n}, localized in space and frequency; wavelets on the real line; image compression (fingerprint files); waveletGalerkin numerical solution of differential equations with variable coefficients.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2P08, 2P12 and 3P03.
Completion of this course will replace previous assigned grade and credit obtained 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: CauchyKovalevski theorem, wellposedness 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(s): MATH 3P08.
Completion of this course will replace previous assigned grade and credit obtained in MATH 4F08.
*MATH 4P09
Solitons and Nonlinear Wave Equations
(also offered as PHYS 4P09)
Introduction to solitons. Travelling waves, nonlinear wave and evolution equations (Korteweg de Vries, Bousinesq, nonlinear Schrodinger, sineGordon), soliton solutions and their interaction properties, Lax pairs and construction of single and multisoliton solutions.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): one of MATH 3P09, 3P51, 3P52.
MATH 4P11
Topics in Groups
Advanced topics from group theory. Topics may include the Sylow theorems, free groups, nilpotent and solvable groups and some simple Lie groups.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 3P13.
Completion of this course will replace previous assigned grade and credit obtained in MATH 4F10.
MATH 4P13
Topics in Rings and Modules
Advanced topics from ring theory. Topics may include radicals, WedderburnArtin theorems, modules over rings and some special rings.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 3P13.
Completion of this course will replace previous assigned grade and credit obtained in MATH 4F10.
MATH 4P14
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(s): MATH 3P13 or permission of the Department.
Completion of this course will replace previous assigned grade and credit obtained in MATH 4F10 or 4P12.
*MATH 4P61
Theory of Computation
(also offered as COSC 4P61)
Regular languages and finite state machines: deterministic and nondeterministic machines, Kleene's theorem, the pumping lemma, MyhillNerode Theorem and decidable questions. Contextfree languages: generation by contextfree 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.
Restriction: open to COSC (single or combined) majors.
Prerequisite(s): MATH 1P67.
Note: MATH students may take this course with permission of Department.
MATH 4P71
Combinatorics
Review of basic enumeration including distribution problems, inclusionexclusion 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; multistage sampling; errors in surveys; computational techniques and use of SAS, Maple or other statistical packages and related topics.
Lectures, 3 hours per week; lab, 1 hour per week.
Prerequisite(s): MATH 3P85 or permission of the instructor.
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. Use of SAS, Maple or other statistical packages.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 3P85 or permission of the instructor.
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. Use of SAS, Maple or other statistical packages.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 3P85 or permission of the instructor.
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. Use of SAS, Maple or other statistical packages.
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 3P85 or permission of the instructor.
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 and credit obtained 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(s): MATH 3P97 or permission of the Department.
Completion of this course will replace previous assigned grade and credit obtained in MATH 4F91.
*MATH 4P94
General Relativity and Black Holes
(also offered as PHYS 4P94)
Review of Special Relativity and Minkowski spacetime. Introduction to General Relativity theory including gravitation and the spacetime metric, light cones, horizons, asymptotic flatness; energymomentum of particles and light rays (geodesics). Static black holes (Schwarzschild metric), properties of light rays and particle orbits. Rotating black holes (Kerr metric).
Lectures, 3 hours per week; lab/tutorial, 1 hour per week.
Prerequisite(s): MATH 2F05, PHYS 2P20 and 2P50 or permission of the instructor.
COOP COURSES
MATH 0N01
Coop Work Placement I
First coop work placement (4months) with an approved employer.
Restriction: open to MATH and MICA Coop students.
MATH 0N02
Coop Work Placement II
Second coop work placement (4 months) with an approved employer.
Restriction: open to MATH and MICA Coop students.
MATH 0N03
Coop Work Placement III
Third coop work placement (4 months) with an approved employer.
Restriction: open to MATH and MICA Coop students.
MATH 0N04
Coop Work Placement IV
Optional coop work placement (4 months) with an approved employer.
Restriction: open to MATH and MICA Coop students.
MATH 0N05
Coop Work Placement V
Optional coop work placement (4 months) with an approved employer.
Restriction: open to MATH and MICA Coop students.
MATH 2C01
Coop Reflective Learning and Intergration I
Provide student with the opportunity to apply what they've learned in their academic studies through careeroriented work experiences at employer sites.
Restriction: open to MATH and MICA Coop students.
Prerequisite(s): SCIE 0N90.
Corequisite(s): MATH 0N01.
Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.
MATH 2C02
Coop Reflective Learning and Integration II
Provide students with the opportunity to apply what they've learned in their academic studies through careeroriented work experiences at employer sites.
Restriction: open to MATH and MICA Coop students.
Prerequisite(s): SCIE 0N90.
Corequisite(s): MATH 0N02.
Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.
MATH 2C03
Coop Reflective Learning and Integration III
Provide student with the opportunity to apply what they've learned in their academic studies through careeroriented work experiences at employer sites.
Restriction: open to MATH and MICA Coop students.
Prerequisite(s): SCIE 0N90.
Corequisite(s): MATH 0N03.
Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.
MATH 2C04
Coop Reflective Learning and Integration IV
Provide students with the opportunity to apply what they've learned in their academic studies through areeroriented work experiences at employer sites.
Restriction: open to MATH and MICA Coop students.
Prerequisite(s): SCIE 0N90.
Corequisite(s): MATH 0N04.
Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.
MATH 2C05
Coop Reflective Learning and Integration V
Provide students with the opportunity to apply what they've learned in their academic studies through careeroriented work experiences at employer sites.
Restriction: open to MATH and MICA Coop students.
Prerequisite(s): SCIE 0N90.
Corequisite(s): MATH 0N05.
Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.

