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Mathematics and Statistics Courses

Teaching of Mathematics MTM Courses

Each year the Department of Mathematics and Statistics offers a selection of the following courses.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

This reading course is closely related to the project or thesis. The outcome is a section of the literature review chapter, related to the domain of research that is the focus of the project or thesis.

Component(s):

Reading

Description:

A student investigates a mathematics education topic, prepares a report, and gives a seminar presentation under the guidance of a faculty member.

Component(s):

Research

Description:

Topics are chosen from the area of Number Theory.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

This course is an extension of undergraduate courses in linear algebra, covering a selection of topics in advanced linear algebra (e.g. from the theory of general vector spaces, linear and multilinear algebras, matrix theory, etc.).

Component(s):

Lecture

Description:

Topics are chosen from the area of the Application of Mathematics.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

The course offers an insight into Euclidean and Non-Euclidean geometries.

Component(s):

Lecture

Description:

The course looks at objects such as numbers, polynomials, matrices or transformations from an algebraic-structural point of view. The course may aim at proving such “famous impossibilities” as squaring the circle, duplicating the cube, trisecting an angle or solving a polynomial equation of degree 5 or more by radicals.

Component(s):

Lecture

Description:

This course is an overview and critical analysis of theories and technologies of mathematics teaching. Applications of the theories to studying and/or developing teaching situations or tools for specific mathematical topics are examined.

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

The course develops elements of the theory of topological spaces and their transformations.

Component(s):

Lecture

Description:

The course is an extension of undergraduate courses in mathematical analysis in the real domain (Analysis I, II; Real Analysis; Measure Theory).

Component(s):

Lecture

Notes:


  • Students may substitute this course with any of the MAST 660-669 courses in the MA/MSc program.

Description:

The course is an extension of undergraduate courses in mathematical analysis in the complex domain (Complex Analysis I, II).

Component(s):

Lecture

Notes:


  • Students may substitute this course with any of the MAST 660-669 courses in the MA/MSc program.

Description:

This course studies epistemological, cognitive, affective, social and cultural issues involved in mathematics.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

This course is an overview of the impact of information and communication technology on curricula, textbooks and teaching approaches.

Component(s):

Lecture

Description:

This course is an overview and critical evaluation of computer software designed for use in mathematics instruction.

Component(s):

Lecture

Description:

This course discusses theoretical and applied aspects of statistics and probability.

Component(s):

Lecture

Description:

This course involves the elaboration, experimentation and critical analysis of individual projects of integration of ICT in mathematics education.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

Topics are chosen from the area of Mathematical Logic.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

This course is an overview of recent results in mathematics education research.

Component(s):

Lecture

Description:

This course is an overview of qualitative and quantitative methods in mathematics education research.

Component(s):

Lecture

Description:

This course is an overview of research literature on a chosen topic or issue in mathematics education.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

Students conduct a pilot study or participate in a research project as a research assistant under the supervision of a senior researcher. The outcome is a written report of the study.

Component(s):

Research

Description:

The course is closely related to project or thesis writing. Its outcome is a section of the literature review chapter, focused on the student’s particular research question.

Component(s):

Reading

Description:

Topics are chosen from the area of the History of Mathematics.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course, provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

This course examines cognitive processes, tools and strategies involved in solving mathematical problems.

Component(s):

Lecture

Description:

This course is primarily a thesis or project preparation seminar but it is open to students in the Course Option as well. The research related to students’ research projects is presented and critically evaluated.

Component(s):

Seminar

Description:

Students are required to demonstrate their ability to carry out original, independent research. The thesis is researched and written under the direction of a supervisor and thesis committee. Upon completion of the thesis, the student is required to defend his/her thesis before the thesis committee.

Component(s):

Thesis Research

Mathematics MA/MSc Courses

The MA/MSc courses offered by the Department of Mathematics and Statistics fall into the following categories:

Mathematics History and Methods Courses
Topology and Geometry Courses
Analysis Courses
Statistics and Actuarial Mathematics Courses
Applied Mathematics Courses
Algebra and Logic Courses

The course content will be reviewed each year

Mathematics History and Methods Courses

Description:

This course examines several major mathematical advances over the centuries in the historical and intellectual contexts of the day and also focuses on the developments of a particular branch of mathematics over the more recent past. Examples may include recent advances in number theory and geometry leading to a proof of Fermat’s Last Theorem and applications of number theory to cryptography.

Component(s):

Lecture

Description:

The general aim of this course is to acquaint students with research problems in mathematics education and ways of approaching them (theoretical frameworks and research methodologies).

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

This course focuses on foundational issues and developments in mathematics, with topics chosen from particular branches of mathematics, e.g., geometry (Euclidean and non-Euclidean geometries; comparison of Euclid’s “Elements” with Hilbert’s “Grundlagen der Geometrie”, etc.), or logic (evolution of logic from Aristotle to Boole; Hilbert’s program; Gödel’s Incompleteness theorems, etc.). It may also look at foundational problems in mathematics suggested by physics and other sciences. More general, philosophical, epistemological and methodological questions about the nature of mathematics may also be chosen as topics for the course.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

This course may focus on a particular epoch and place in the history of mathematics (e.g., Ancient Greek, Indian and Chinese mathematics; the development of mathematics in Europe in the 17th to 19th centuries, etc.), or on the history of a particular area of mathematics (history of geometry, algebra, analysis, number theory, etc.). Aspects related to the history of approaches to teaching mathematics may also be addressed.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Topology and Geometry Courses

Description:

Topological spaces. Order, product, subspace, quotient topologies. Continuous functions. Compactness and connectedness. The fundamental group and covering spaces.

Component(s):

Lecture

Description:

Mappings, functions and vectors fields on Rn, inverse and implicit function theorem, differentiable manifolds, immersions, submanifolds, Lie groups, transformation groups, tangent and cotangent bundles, vector fields, flows, Lie derivatives, Frobenius’ theorem, tensors, tensor fields, differential forms, exterior differential calculus, partitions of unity, integration on manifolds, Stokes’ theorem, Poincaré lemma, introduction to symplectic geometry and Hamiltonian systems.

Component(s):

Lecture

Component(s):

Lecture

Component(s):

Lecture

Analysis Courses

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

This course will be an introduction to the theory of Hilbert spaces and the spectral analysis of self-adjoint and normal operators on Hilbert spaces. Applications could include Stone’s theorem on one parameter groups and/or reproducing kernel Hilbert spaces.

Component(s):

Lecture

Description:

This course covers the following topics: measurable transformations, functional analysis review, the Birkhoff Ergodic Theorem, the Mean Ergodic Theorem, recurrence, ergodicity, mixing, examples, entrophy, invariant measures and existence of invariant measures.

Component(s):

Lecture

Description:

An introduction to the range of dynamical behaviour exhibited by one-dimensional dynamical systems. Recurrence, hyperbolicity, chaotic behaviour, topological conjugacy, structural stability, and bifurcation theory for one-parameter families of transformation. The study of unimodal functions on the interval such as the family Fr (X) = rx (1-x), where 0 ≤ r ≤ 4 . For general continuous maps of the interval, the structure of the set of periodic orbits, for example, is found in the theorem of Sarkovskii.

Component(s):

Lecture

Description:

Review of Cauchy-Riemann equations, holomorphic and meromorphic functions, Cauchy integral theorem, calculus of residues, Laurent series, elementary multiple-valued functions, periodic meromorphic functions, elliptic functions of Jacobi and Wierstrass, elliptic integrals, theta functions. Riemann surfaces, uniformization, algebraic curves, abelian integrals, the Abel map, Riemann theta functions, Abel’s theorem, Jacobi varieties, Jacobi inversion problem. Applications to differential equations.

Component(s):

Lecture

Component(s):

Lecture

Component(s):

Reading

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Component(s):

Lecture

Description:

Measure and integration, measure spaces, convergence theorems, Radon-Nikodem theorem, measure and outer measure, extension theorem, product measures, Hausdorf measure, Lp-spaces, Riesz theorem, bounded linear functionals on C(X), conditional expectations and martingales.

Component(s):

Lecture

Statistics and Actuarial Mathematics 600-level Courses

Description:

This course will discuss mathematical topics which may be used concurrently or subsequently in other statistics stream courses. The topics will come mainly from the following broad categories; 1) geometry of Euclidean space; 2) matrix theory and distribution of quadratic forms; 3) measure theory applications (Reimann-Stieltjes integrals); 4) complex variables (characteristic functions and inversion); 5) inequalities (Cauchy-Schwarz, Holder, Minkowski, etc.) and numerical techniques (Newton-Raphson algorithm, scoring method, statistical differentials); 6) some topics from probability theory.

Component(s):

Lecture

Description:

Axiomatic construction of probability; characteristic and generating functions; probabilistic models in reliability theory; laws of large numbers; infinitely divisible distributions; the asymptotic theory of extreme order statistics.

Component(s):

Lecture

Description:

Order statistics; estimation theory; properties of estimators; maximum likelihood method; Bayes estimation; sufficiency and completeness; interval estimation; shortest length confidence interval; Bayesian intervals; sequential estimation.

Component(s):

Lecture

Description:

Testing of hypotheses; Neyman-Pearson theory; optimal tests; linear hypotheses; invariance; sequential analysis.

Component(s):

Lecture

Description:

An introduction to multivariate distributions will be provided; multivariate normal distribution and its properties will be investigated. Estimation and testing problems related with multivariate normal populations will be discussed with emphasis on Hotelling’s generalized T2 and Wishart distribution. Other multivariate techniques including MANOVA; canonical correlations and principal components may also be introduced.

Component(s):

Lecture

Description:

A review of statistical techniques and simple random sampling, varying probability sampling, stratified sampling, cluster and systematic sampling-ratio and product estimators.

Component(s):

Lecture

Description:

Matrix approach to development and prediction in linear models will be used. Statistical inferences on the parameters will be discussed after development of proper distribution theory. The concept of generalized inverse will be fully developed and analysis of variance models with fixed and mixed effects will be analyzed.

Component(s):

Lecture

Description:

Statistical analysis of time series in the time domain. Moving average and exponential smoothing methods to forecast seasonal and non-seasonal time series, construction of prediction intervals for future observations, Box-Jenkins ARIMA models and their applications to forecasting seasonal and non-seasonal time series. A substantial portion of the course will involve computer analysis of time series using computer packages (mainly MINITAB). No prior computer knowledge is required.

Component(s):

Lecture

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Applied Mathematics Courses

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

Introduction to nonsmooth analysis: generalized directional derivative, generalized gradient, nonsmooth calculus; connections with convex analysis. Mathematical programming: optimality conditions; generalized multiplier approach to constraint qualifications and sensitivity analysis. Application of the theory: functions defined as pointwise maxima of a family of functions; minimizing the maximal eigenvalue of a matrix-valued function; variational analysis of an extended eigenvalue problem.

Component(s):

Lecture

Description:

Jordan canonical form and applications, Perron-Frobenius theory of nonnegative matrices with applications to economics and biology, generalizations to matrices which leave a cone invariant.

Component(s):

Lecture

Description:

This course consists of fundamental topics in numerical analysis with a bias towards analytical problems involving optimization integration, differential equations and Fourier transforms. The computer language C++ will be introduced and studied as part of this course; the use of “functional programming” and graphical techniques will be strongly encouraged. By the end of the course, students should have made a good start on the construction of a personal library of tools for exploring and solving mathematical problems numerically.

Component(s):

Lecture

Description:

The aim of this course is two-fold: (i) to provide an elementary account of the theory of non-relativistic bound systems, and (ii) to give an introduction to some current research in this area, including spectral geometry.

Component(s):

Lecture

Component(s):

Lecture

Component(s):

Reading

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Description:

Linear algebraic background material, linear differential and control systems, controllability and observability, properties of the attainable set, the maximal principle and time-optimal control.

Component(s):

Lecture

Component(s):

Lecture

Component(s):

Lecture

Algebra and Logic Courses

Component(s):

Lecture

Description:

Field extensions, normality and separability, normal closures, the Galois correspondence, solution of equations by radicals, application of Galois theory, the fundamental theorem of algebra.

Component(s):

Lecture

Description:

Dedekind domains; ideal class groups; ramification; discriminant and different; Dirichlet unit theorem; decomposition of primes; local fields; cyclotomic fields.

Component(s):

Lecture

Description:

Introduction to group theory, including the following topics: continuous and locally compact groups, subgroups and associated homogeneous spaces. Haar measures, quasi-invariant measures, group extensions and universal covering groups, unitary representations, Euclidean and Poincaré groups, square integrability of group representations with applications to image processing.

Component(s):

Lecture

Component(s):

Lecture

Component(s):

Reading

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Component(s):

Lecture

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Statistics and Actuarial Mathematics 700-level Courses

Prerequisite/Corequisite:

Permission of the project supervisor and the Graduate Program Director is required.

Description:

This course offers a review of the literature in the area of the proposed project.

Component(s):

Research

Notes:


  • This course is graded on a pass/fail basis.


Prerequisite/Corequisite:

Permission of the project supervisor and the Graduate Program
Director is required.

Description:

This course involves the formulation of the project proposal and development of the theoretical framework and methodology.

Component(s):

Research

Notes:


  • This course is graded on a pass/fail basis.

Prerequisite/Corequisite:

Permission of the project supervisor and the Graduate Program
Director is required.

Description:

This course involves investigations and research leading to obtaining results in the project.

Component(s):

Research

Notes:


  • This course is graded on a pass/fail basis.

Prerequisite/Corequisite:

Permission of the project supervisor and the Graduate Program
Director is required.

Description:

This course involves the conclusion of the research and writing of the first draft of the project report.

Component(s):

Research

Notes:


  • This course is graded on a pass/fail basis.

Prerequisite/Corequisite:

Permission of the project supervisor and the Graduate Program
Director is required.

Description:

This course involves the completion of the written project report.

Component(s):

Research

Notes:


  • This course is graded on a pass/fail basis.

Description:

Parametric and non-parametric failure time models; proportional hazards; competing risks.

Component(s):

Lecture

Description:

General risk contingencies; advanced multiple life theory; population theory; funding methods and dynamic control.

Component(s):

Lecture

Description:

Valuation methods, gains and losses, stochastic returns, dynamic control.

Component(s):

Lecture

Description:

Asset and liability management models, optimal portfolio selection, stochastic returns, special topics.

Component(s):

Lecture

Description:

General risk models; renewal processes; Cox processes; surplus control.

Component(s):

Lecture

Description:

Classical, regression and hierarchical Bayes models, empirical credibility, robust credibility, special topics.

Component(s):

Lecture

Description:

Heavy tailed distributions, grouped/censured data, point and interval estimation, goodness-of-fit, model selection.

Component(s):

Lecture

Description:

Cluster analysis, principal components, discriminant analysis, Mahalanobis distance, special topics.

Component(s):

Lecture

Component(s):

Reading

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Mathematics MA/MSc Thesis and Literature Courses.

Component(s):

Thesis Research

Mathematics PhD Courses

The PhD courses offered by the Department of Mathematics and Statistics fall into the following categories:

Number Theory and Computational Algebra Courses
Analysis Courses
Physics and Differential Geometry Courses
Dynamical Systems Courses
Statistics and Actuarial Mathematics Courses

Elective Courses

Number Theory and Computational Algebra Courses

Description:

L-series, Dirichlet theorem, Gauss sums, Stickelberger theorem, class groups and class number, circular units, analytic formulae.

Component(s):

Lecture

Description:

Local and global class field theory, ideles and adeles, reciprocity laws, existence theorem.

Component(s):

Lecture

Description:

Introduction to elliptic curves over finite fields, local and global fields, rational points, Mordell-Weil theorem, formal groups.

Component(s):

Lecture

Description:

The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Analysis Courses

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Mathematical Physics and Differential Geometry Courses

Description:

The mathematical theory of Lie groups and introduction to their representation theory with applications to mathematical physics. Topics will include classical Lie groups, one-parameter subgroups, Lie algebras and the exponential mapping, adjoint and coadjoint representations, roots and weights, the Killing form, semi-direct products, Haar measure and decompositions such as those of Cartan and Iwasawa. The theory of unitary representations on Hilbert spaces. Physical applications of compact Lie groups (such as SU(2) and SU(3)) and non-compact groups (such as the Lorentz and Poincaré groups).

Component(s):

Lecture

Description:

Introduction to the mathematical theory of P.D.E.’s, including applications to mathematical physics. Topics will include Sturm-Liouville systems, boundary value and eigenvalue problems, Green’s functions for time-independent and time-dependent equations, Laplace and Fourier transform methods. Additional topics will be selected from the theory of elliptic equations (e.g. Laplace and Poisson equations), hyperbolic equations (e.g., the Cauchy problem for the wave equation) and parabolic equations (e.g., the Cauchy problem for the heat equation). Links will be made with the theory of differential operators and with analysis on manifolds.

Component(s):

Lecture

Description:

Manifolds, differential systems, Riemannian, Kahlerian and symplectic geometry, bundles, supermanifolds with applications to relativity, quantization, gauge field theory and Hamiltonian systems.

Component(s):

Lecture

Description:

Algebraic curves, Jacobi varieties, theta functions, moduli spaces of holomorphic bundles and algebraic curves, rational maps, sheaves and cohomology with applications to gauge theory, relativity and integrable systems.

Component(s):

Lecture

Description:

Yang-Mills theory, connections of fibre bundles, spinors, twistors, classical solutions, invariance groups, instantons, monopoles, topological invariants, Einstein equations, equations of motion, Kaluza-Klein, cosmological models, gravitational singularities.

Component(s):

Lecture

Description:

Geometric quantization, Borel quantization, Mackey quantization, stochastic and phase space quantization, the problems of prequantization and polarization, deformation theory, dequantization.

Component(s):

Lecture

Description:

Schrödinger operators; min-max characterization of eigenvalues, geometry of the spectrum in parameter space, kinetic potentials, spectral approximation theory, linear combinations and smooth transformations of potentials, applications to the N-body problem.

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Dynamical Systems Courses

Description:

The study of dynamical properties of diffeomorphisms or of one-parameter groups of diffeomorphisms (flows) defined on differentiable manifolds. Periodic points, the non-wandering set, and more general invariant sets. Smale’s horseshoe, Anosov, and Morse-Smale systems, general hyperbolic systems, the stable manifold theorem, various forms of stability, Markov partitions and symbolic dynamics.

Component(s):

Lecture

Description:

Review of functional analysis, Frobenius-Perron operator and its properties, existence of absolutely continuous invariant measures for piecewise expanding transformations, properties of invariant densities, compactness of invariant densities, spectral decomposition of the Frobenius-Perron operator, bounds on the number of absolutely continuous invariant measures, perturbations of absolutely continuous invariant measures.

Component(s):

Lecture

Description:

Continuation of solutions, homotopy methods, asymptotic stability, bifurcations, branch switching, limit points and higher order singularities, Hopf bifurcation, control of nonlinear phenomena, ODE with boundary and integral constraints, discretization, numerical stability and multiplicity, periodic solutions, Floquet multipliers, period doubling, tori, control of Hopf bifurcation and periodic solutions, travelling waves, rotations, bifurcation phenomena in partial differential equations, degenerate systems.

Component(s):

Lecture

Description:

Local and global bifurcations. Generalized Hopf bifurcation and generalized homoclinic bifurcation. Hamiltonian systems and systems close to Hamiltonian systems, local codimension two bifurcations of flows.

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Statistics and Actuarial Mathematics 800-level Courses

Description:

Definition of probability spaces, review of convergence concepts, conditioning and the Markov property, introduction to stochastic processes and martingales.

Component(s):

Lecture

Description:

Stochastic sequences, martingales and semi-martingales, Gaussian processes, processes with independent increments, Markov processes, limit theorems for stochastic processes.

Component(s):

Lecture

Description:

Decision functions, randomization, optimal decision rules, the form of Bayes’ rule for estimation problems, admissibility and completeness, minimax, rules, invariant statistical decisions, admissible and minimax decision rules, uniformly most powerful tests, unbiased tests, locally best tests, general linear hypothesis, multiple decision problems.

Component(s):

Lecture

Description:

Wishart distribution, analysis of dispersion , tests of linear hypotheses, Rao’s test for additional information, test for dimensionality, principal component analysis, discriminant analysis, Mahalanobis distance, cluster analysis, relations with sets of variates.

Component(s):

Lecture

Description:

Unequal probability sampling, multistage sampling, super population models, Bayes and empirical Bayes estimation, estimation of variance from complex surveys, non-response errors and multivariate auxiliary information.

Component(s):

Lecture

Description:

Failure time models, inference in parametric models, proportional hazards, non-parametric inference, multivariate failure time data, competing risks.

Component(s):

Lecture

Description:

Reliability performance measures, unrepairable systems, repairable systems, load-strength reliability models, distributions with monotone failure rates, analysis of performance effectiveness, optimal redundancy, heuristic methods in reliability.

Component(s):

Lecture

Description:

Generalizations of the classical risk model, renewal processes, Cox processes, diffusion models, ruin theory and optimal surplus control.

Component(s):

Lecture

Notes:


  • The content varies from term to term and from year to year. Students may re-register for this course provided the course content has changed. Changes in content are indicated by the title of the course.

Seminars

Component(s):

Seminar

Component(s):

Seminar

Component(s):

Seminar

Component(s):

Seminar

Component(s):

Seminar

Component(s):

Seminar

Thesis and Comprehensive Examinations Courses

Description:

This is a written examination, consisting of two parts. The first part of the Comprehensive A examination tests the candidate's general knowledge of fundamental mathematical or statistical concepts. It will normally be completed within one year (3 terms) of the candidate's entry into the program or the equivalent of part-time study. The second part of the Comprehensive A examination tests the candidate's knowledge of topics in their area of specialization. The material will be chosen from the list of course descriptions given by the Graduate
Studies Committee in consultation with the candidate's research supervisor and the student's Advisory Committee. Candidates are allowed at most one failure in the Part A examination.

Component(s):

Thesis Research

Description:

The Comprehensive B examination is an oral presentation of the candidate's plan of his or her doctoral thesis in front of the student's Advisory Committee. It is normally taken within two-three years of the candidate's entry into the program (or the equivalent of part-time study) and at least one year before the expected completion of the thesis.

Component(s):

Thesis Research

Description:

Concurrently with the preparation for the Part B exam, the students will be engaging in their research work towards the dissertation. After submitting the doctoral thesis, the candidate is required to pass an oral defence of the thesis. The doctoral thesis must make an original contribution to mathematical knowledge, at a level suitable for publication in a reputable professional journal in the relevant area.

Component(s):

Thesis Research

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