No Title

3000-level Courses



AS/SC/AK/MATH3010 3.0 W
Vector Integral Calculus

1998/99 CALENDAR COPY:Integrability of continuous functions over suitable domains, iterated integrals and Fubini's theorem, counterexamples, change of variables, Jacobian determinants, polar and spherical coordinates, volumes, vector fields, divergence, curl, line and surface integrals, Green's and Stokes's theorems, differential forms, general Stokes's theorem. The text and marking scheme have not yet been determined.

Prerequisite: AS/SC/MATH2010 3.0; or AS/SC/AK/MATH
2310 3.0; or AS/SC/MATH2015 3.0 and written permission of the Mathematics Undergraduate Director (normally granted only to students proceeding in Honours programmes in Mathematics or in the Specialized Honours Programme in Statistics).

Corequisite: (or prerequisite) AS/SC/MATH2022 3.0
or AS/SC/AK/MATH2222 3.0.

Coordinator: M-W. Wong


AS/SC/AK/MATH3020 6.0
Algebra I

1998/99 CALENDAR COPY:Introduction to the basic concepts of abstract algebra, with applications: groups (cyclic, symmetric, Lagrange's theorem, quotients, homomorphism theorems); rings (congruences, quotients, polynomials, integral domains, PID's and UFD's); fields (field extensions, constructions with ruler and compass, coding theory).

Algebra is the study of algebraic systems, that is, sets of elements endowed with certain operations. A familiar example is the set of integers with the operations of addition and multiplication.

Algebra is used in almost every branch of mathematics; indeed, it has simplified the study of mathematics by indicating connections between seemingly unrelated topics. In addition the success of the methods of algebra in unravelling the structure of complicated systems has led to its use in many fields outside of mathematics.

One aim of this course is to help students learn to write clear and concise proofs, read the mathematical literature, and communicate mathematical ideas effectively, both orally and in writing.

Any student who performed well in the prerequisite linear algebra course is welcome to enrol, but THIS COURSE IS INTENDED PRIMARILY FOR STUDENTS WHO HAVE TAKEN THE HONOURS VERSIONS OF FIRST AND SECOND YEAR COURSES.

The text will be Fraleigh, A First Course in Abstract Algebra, 5th Edition (Addison-Wesley).

The final grade will be based on assignments, class participation, quizzes, class tests, and a final examination.

Prerequisite: AS/SC/MATH2022 3.0
or AS/SC/AK/MATH2222 3.0.

Degree credit exclusion: AK/MATH3420 6.0

Coordinator: J.W. Pelletier


AS/SC/MATH3033 3.0 F
Classical Regression Analysis

1998/99 CALENDAR COPY:General linear model. Properties and geometry of least-squares estimation. General linear hypothesis, confidence regions and intervals. Multicollinearity. Relationship between ANOVA models and linear models. Residual analysis, outliers, partial and added variable plots.

This course is closely linked with MATH3034 3.0, Modern Regression Analysis, for which it is a prerequisite. The emphasis, in contrast to MATH3330 3.0 and MATH3230 3.0, will be a more mathematical development of linear models including modern regression techniques. To develop a solid knowledge of regression models, it is strongly advised that you take both MATH3033 3.0 and MATH3034 3.0.

Students will use the computer for some exercises. No previous courses in computing are required. The statistical software package SPLUS in a UNIX enrivonment will be used and instructions will be given in class.

The text is R. H. Myers (ed.), Classical and Modern
Regression with Applications
(Duxbury).

The final grade may be based (in each term) on assignments, quizzes, a project, one midterm, and a final examination.

Prerequisites: AS/SC/MATH1132 3.0 , or an average of
B or higher in AS/SC/AK/MATH2560 3.0 and
AS/SC/AK/MATH2570 3.0; AS/SC/MATH2022 3.0
or AS/SC/AK/MATH2222 3.0.

Corequisite: AS/SC/AK/MATH3131 3.0 or permission of the course coordinator.

Degree credit exclusions: AS/SC/AK/MATH3330 3.0, AS/SC/
GEOG3421 3.0, AS/SC/PSYC3030 6.0, AK/PSYC3110 3.0.

Coordinator: P. Song


AS/SC/MATH3034 3.0 W
Modern Regression Analysis

1998/99 CALENDAR COPY:Selecting best model, cross-validation. Influence diagnostics. Weighted least squares, correlated errors, transformations, Box-Cox transformations. Logistic and Poisson regression. Generalized linear models. Multicollinearity, ridge regression. Topics selected from non-linear regression, scatterplot smoothing, non-parametric regression, additive non-linear regression, projection pursuit, robust regression.

For course description see AS/SC/MATH3033 3.0 F.

Prerequisite: AS/SC/MATH3033 3.0.

Degree credit exclusions: AS/SC/AK/MATH3230 3.0,
AS/SC/GEOG3421 3.0, AS/SC/PSYC3030 6.0,
AK/GEOG4200 6.0, AK/PSYC3110 3.0.

Coordinator: T.B.A.


AS/SC/AK/MATH3050 6.0
Introduction to Geometries

(Note: This course will probably not be offered in 1999/2000.) 1998/99 CALENDAR COPY:Analytic geometry over a field with vector and barycentric coordinate methods, affine and projective transformations, inversive geometry, foundations of Euclidean and non-Euclidean geometry, applications throughout to Euclidean geometry.

Geometry has an important classical side, moving from the Greeks to non-Euclidean geometries (which differ in their assumptions about ``parallel lines''), including spherical, hyperbolic and projective geometries. This shift from Euclidean geometry to multiple geometries is one of the critical ``paradigm shifts'' in the history of mathematics. In modern geometry, the fertile interplay of synthetic (constructive and visual) methods, groups of transformations, analytic methods and axiomatics presents a rich mix of problems and methods to be explored. Through multiple mathematical and pedagogical approaches we will introduce these geometries in their classical and modern forms.

Modern geometry has important applications to areas involving shape and computing: Computer Aided Design; Robotics; computer graphics; physics and engineering. Geometry also has a critical role in developing our skills and vocabulary for reasoning with visual representations. Both why we practice geometry and how we practice (and teach) geometry are changed by computers.

The course is designed to prepare the student for further studies in: (i) pure mathematics, (ii) applications of geometry, or (iii) teaching geometry. The formal prerequisites are minimal: familiarity with linear algebra and some mathematical maturity. Other background will be developed as needed. We will expect students to join in group work, to work with and build physical models in class (using spheres for spherical geometry, plastic Polydron for polyhedra, mirrors for symmetry, etc.), to use a dynamic geometry program, The Geometer's Sketchpad (available in the classroom and at Steacie Labs), and to develop their own geometric questions and projects.

The text for the course is David Henderson, Experiencing Geometry on Plane and Sphere (Prentice-Hall), 1996.

Graded work will include regular assignments, including proofs, conjectures and open-ended explorations, oral presentations, written (and drawn) projects and possibly quizzes.

Prerequisite: AS/SC/MATH2022 3.0 or AS/SC/AK/MATH2222 3.0 or permission of the Course Coordinator.

Degree credit exclusion: AK/MATH/3550 6.0

Coordinator: Walter Whiteley


AS/SC/MATH3100 3.0 W
Famous Problems in Mathematics

(Note: This course will probably not be offered in 1999/2000.)

1998/99 CALENDAR COPY:An attempt to foster an appreciation of the history, the personalities and some of the content of different areas of mathematics, by means of a study of some specific problems which have exercised the minds of mathematicians.

The problems will range from ancient to recent times, and will be selected from the fields of algebra, analysis, geometry, number theory, set theory, and foundations of mathematics.

The course will deal wih mathematical ideas in the context of mathematical techniques. Philosophical issues in the develoment of mathematics will also be discussed.

The final grade will be based on term work (assignments, class test(s), and possibly presentations) worth 70%, and a final examination worth 30%.

There will be no text for the course, but many references will be provided. Students may get a flavor of the course by consulting the following books:

P. Davis & R. Hersh, The Mathematical Experience.
W. Dunham, Journey Through Genius: The Great Theorems
of Mathematics
. H. Eves, Great Moments in Mathematics.

Prerequisites: At least 12 credits from 2000-level MATH courses without second digit 5, or permission of the Course Coordinator.

Coordinator: I. Kleiner


AS/SC/AK/MATH3110 3.0 F
Introduction to Mathematical Analysis

1998/99 CALENDAR COPY:Proofs in calculus and analysis. Topics include sets, functions, axioms for R, applications of the completeness axiom, countability, sequences and their limits, monotone sequences, limits of functions, continuity.

This course provides a path towards an honours degree for those students who have not taken the honours first year calculus course MATH1010 3.0. The course MATH3210 3.0, which is required for several honours programmes, has this course as an alternative to MATH1010 3.0 as a prerequisite.

The course will emphasize the theoretical aspects of the subject. A principal goal of the course is learning to understand the various definitions and to use them to prove basic properties of the objects being defined. The structure of proofs and the basic logic underlying them will be carefully considered. Relatively little effort will be devoted to problems involving calculations, except when they are useful for explaining the concepts.

The text has not yet been selected.

The final grade will be based 60% on term work, 40% on the final exam.

Prerequisite: AS/SC/AK/MATH1310 3.0
or AS/SC/MATH1014 3.0.

Corequisites: AS/SC/AK/MATH2310 3.0 or AS/SC/MATH
2010 3.0 or AS/SC/MATH2015 3.0; AS/SC/MATH
2021 3.0
or AS/SC/AK/MATH2221 3.0 or AS/SC/MATH1025 3.0.

Degree credit exclusions: AS/SC/MATH1010 3.0,
AK/MATH2400 6.0.

Coordinator: G. O'Brien


AS/SC/AK/MATH3131 3.0 F
Mathematical Statistics I

1998/99 CALENDAR COPY:Topics include common density functions, probability functions, principle of likelihood, the likelihood function, the method of maximum likelihood, likelihood regions, tests of hypotheses, likelihood ratio tests, goodness of fit tests, conditional tests, and confidence sets with a view towards applications.

This course is intended for students who need a theoretical foundation in mathematical statistics. Students who have taken it normally take MATH3132 in the second term. It continues where MATH2030 left off, while providing a theoretical foundation for many of the statistical procedures learned in MATH1131 and MATH1132.

Prerequisite: AS/SC/AK/MATH2030 3.0 or permission of the course coordinator.

Degree credit exclusions: AK/MATH3030 3.0 (before SU95),
AS/SC/MATH3030 3.0 (before 1993/94), AK/MATH3530 6.0.

Coordinator: Y. Wu


AS/SC/AK/MATH3132 3.0 W
Mathematical Statistics II

(formerly MATH3031) 1998/99 CALENDAR COPY:Important examples and methods of statistical estimation and hypothesis testing are discussed in terms of their mathematical and statistical properties. Topics include sufficiency, Bayesian statistics, decision theory, most powerful tests, likelihood ratio tests.

This course is a continuation of MATH3131 3.0. The basic nature of statistical inference will be studied. Joining the above list of topics is that of asymptotics.

Prerequisite: AS/SC/AK/MATH3131 3.0.

Degree credit exclusions: AS/SC/MATH3031 3.0,
AK/MATH3530 6.0.

Coordinator: Y. Wu


AS/SC/AK/MATH3140 6.0
Number Theory and Theory of Equations

This course will not be offered in 1998/99. It is expected to be offered in 1999/2000.


AS/SC/AK/MATH3170 6.0
Operations Research I

1998/99 CALENDAR COPY:A study of linear programming; transportation problems, including network flows, assignment problems and critical path analysis; integer programming; dynamic programming and an introduction to stochastic models. Application to a set of problems representative of the field of operations research.

This course deals with standard optimization techniques used in Operations Research. The main topics include:
(a) Linear Programming: the theory and applications of linear programming including the simplex algorithm, duality theorem, postoptimality analysis, and a discussion of the types of problems that lead to linear programming problems. (b) Transportation Problems: the transportation algorithm with applications to network flows, assignment problems, shortest-route problems, and critical path scheduling. (c) Integer Programming: a study of the situations leading to integer-programming problems, branch-and-bound algorithm for solving such problems. (d) Dynamic Programming: an introduction to the concepts of dynamic programming with a discussion of typical problems and their solutions.

The text will be W.L. Winston, Operations Research.
Applications and Algorithms
, 3rd ed.
(Wadsworth Publishing Co., Duxbury Press), 1994.

The final grade will be based on two computer assignments (5%), three tests (55%), and a final examination (40%).

Prerequisites: AS/SC/MATH2021 3.0 or AS/SC/AK/
MATH2221 3.0 or AS/SC/MATH1025 3.0,
plus SC/AS/COSC1530 3.0 or SC/AS/
COSC1540 3.0 or equivalent. Students who have not taken
these courses need the permission of the course coordinator.

Degree credit exclusions: AK/MATH2751 3.0,
AK/MATH3490 6.0, AK/ADMS3351 3.0,
AK/COSC3450 6.0, AK/ECON3120 3.0.

Coordinator: Silviu Guiasu


AK/AS/SC/MATH3190 3.0 W
Set Theory and Foundations of Mathematics

(Note: This course is offered on an irregular basis.) 1998/99 CALENDAR COPY:The following topics are covered: paradoxes in naive set theory; functions and relations, transfinite numbers, their ordering and their arithmetic; well-ordered sets and ordinal numbers; Zorn's lemma; an introduction to axiomatic set theory.

The relevance of set theory to a mathematician (student or otherwise) is equivalent to the relevance to an intelligent human being of the ability to speak, read, and write. Practically the entire ``modern'' literature in mathematics (Topology, Analysis, Algebra, etc.) relies heavily on the ``language'' of set theory, but also on the deeper results involving cardinal and ordinal numbers.

Additionally to the above considerations of ``relevance'', one will want to study set theory for its own sake.

We shall first look into the basic (informal) definitions and notations, eventually leading to the notions of relations and functions, equivalence relations and partial orders. En route we will get a flavour of the foundational difficulties that a purely ``informal'' approach entails. We will see--in a ``naive'' manner--how the introduction of axioms helps to get around these paradoxes. We will be ``fixing'' the theory as we go by introducing appropriate ``assumptions'' (axioms)--as needed--regarding the behaviour of sets.

The Axiom of Choice and a number of its equivalent variants (including ``Zorn's Lemma'') will be discussed, and some of its elementary consequences will be considered.

The final grade will be determined by assignments (70%) and a final exam (30%).

The text will consist of typeset notes from a preprint of Set Theory, by G. Tourlakis.

Prerequisite: Six credits from 2000-level MATH courses without second digit 5.

Coordinator: G. Tourlakis


AS/SC/AK/MATH3210 3.0 W
Principles of Mathematical Analysis

1998/99 CALENDAR COPY:Rigorous presentation, with proofs, of fundamental concepts of analysis: limits, continuity, differentiation, integration, fundamental theorem, power series, uniform convergence.

The origins of some ideas of mathematical analysis are lost in antiquity. About 300 years ago, Newton and Leibniz independently created the calculus. This was used with great success, but for the most part uncritically, for about 200 years. In the last century, mathematicians began to examine the foundations of analysis, giving the concepts of function, continuity, convergence, derivative and integral the firm basis they required. These developments continue today, for example with the study of calculus on infinite dimensional spaces.

This course is a continuation of first and second year calculus. The material will be presented in a rigorous manner, putting emphasis on careful mathematical arguments, proofs and illustrative examples. The objectives of the course include improved skill at understanding and writing mathematical arguments as well as understanding of the concepts of the course. The course will provide a useful theoretical background for a variety of higher level and graduate courses including those in analysis, probability, topology, mathematical statistics, and numerical analysis.

The text for the course has not yet been chosen.

The final grade will be based on assignments, tests and a final examination.

Prerequisite:
AS/SC/MATH2010 3.0 or AS/SC/AK/MATH3110 3.0.

Note: Subject to approval by the Faculty of Arts after we go to press, these prerequisites will be augmented to include MATH1010 + MATH2310, or MATH1010 + MATH2015, as alternatives. Please inquire at the Undergraduate Office (N502 Ross).

Coordinator: G. O'Brien


AS/SC/AK/MATH3230 3.0 W
Analysis of Variance

(Note: This course will not be offered after 1999/2000. At that time, a slightly modified version of MATH3034 3.0 will replace it as prerequisite for other courses.)

1998/99 CALENDAR COPY:Categorical variables; one factor and two factor analysis; fixed, random and mixed models; nested designs; an introduction to randomized block and Latin square designs. Second term.

A major focus will be on models with categorical variables as predictors (classical ANOVA, or Analysis of Variance). The computer will be used heavily, but no previous computing courses are required. See also the course description for MATH3330, with which this course is closely linked.

Prerequisite: AS/SC/AK/MATH3330 3.0.

Degree credit exclusions: AS/SC/MATH3034 3.0,
AS/SC/GEOG3421 3.0, AS/SC/PSYC3030 6.0,
AK/PSYC3110 3.0.

Coordinator: D. Montgomery


AS/SC/MATH3241 3.0 F
Numerical Methods I

1998/99 CALENDAR COPY:An introductory course in computational linear algebra. Topics include simple error analysis, linear systems of equations, nonlinear equations, linear least squares and interpolation. (Same as SC/AS/COSC3121 3.0.)

The course begins with a general discussion of computer arithmetic and computational errors. Examples of ill-conditioned problems and unstable algorithms will be given. The first class of numerical methods we introduce are those for nonlinear equations, i.e., the solution of a single equation in one variable. We then turn to a discussion of the most basic problem of numerical linear algebra: the solution of a linear system of n equations in n unknowns. The Gaussian elimination algorithm will be discussed as well as the concepts of error analysis, condition number and iterative refinement. We then turn to the least squares methods for solving overdetermined systems of linear equations. Finally we discuss polynomial interpolations. The emphasis in the course is on the development of numerical algorithms, the use of mathematical software, and the interpretation of the results obtained on some assigned problems.

A possible textbook is R.L. Burden and J.D. Faires, Numerical Analysis (6th ed.), PWS, 1997. (The description of this course continues on the next page.)

The final grade will be based on assignments (including computer assignments), tests and a final examination. Details will be announced.

Prerequisites: One of AS/SC/MATH1010 3.0,
AC/SC/MATH1014 3.0, AS/SC/AK/MATH1310 3.0; one
of AS/SC/MATH1025 3.0, AS/SC/AK/MATH2221 3.0,
AS/SC/MATH2021 3.0; one of SC/AS/COSC1540 3.0,
SC/AS/COSC2011 3.0, SC/AS/COSC2031 3.0.

Degree credit exclusions: SC/AS/COSC3121 3.0,
AK/COSC3511 3.0.

Coordinator: Martin Muldoon


AS/SC/MATH3242 3.0 W
Numerical Methods II

1998/99 CALENDAR COPY:Algorithms and computer methods for solving problems of differentiation, integration, differential equations, and an introduction to systems of non-linear equations. (Same as SC/AS/COSC3122 3.0.)

The textbook will be the same as for MATH3241.

The final grade will be based on assignments (including computer assignments), tests and a final examination. Details will be announced.

Prerequisites: AS/SC/AK/MATH2270 3.0;
AS/SC/MATH3241 3.0 or SC/AS/COSC3121 3.0.

Degree credit exclusions: SC/AS/COSC3122 3.0,
AK/COSC3512 3.0.

Coordinator: A.D. Stauffer


AS/SC/AK/MATH3260 3.0 W
Introduction to Graph Theory

1998/99 CALENDAR COPY: Introductory graph theory with applications. Graphs, digraphs. Eulerian and Hamiltonian graphs. The travelling salesman. Path algorithms; connectivity; trees; planarity; colourings; scheduling; minimal cost networks. Tree searches and sortings, minimal connectors and applications from physical and biological sciences.

This is a first course in graph theory. After an introduction to graphs, we consider trees, circuits, cycles and connectedness. We may also consider extremal problems, and counting and labelings of graphs.

The text and grading scheme have not been determined as we go to press.

Prerequisite: At least six credits from 2000-level (or higher) MATH courses (without second digit 5), or permission of the instructor.

Coordinator: Richard Ganong


AS/SC/MATH3271 3.0 F
Partial Differential Equations

1998/99 CALENDAR COPY:Partial differential equations of mathematical physics and their solutions in various coordinates, separation of variables in Cartesian coordinates, application of boundary conditions; Fourier series and eigenfunction expansions; generalized curvilinear coordinates; separation of variables in spherical and polar coordinates.

Further topics include Sturm-Liouville theory, the gamma function, and Bessel, Legendre, Laguerre, Hermite, Chebyshev, hypergeometric, and confluent hypergeometric equations and functions and their properties.

The principal reference text will be G. Arfken,
Mathematical Methods for Physicists.

The final grade may be based on assignments, two tests, and a final exam.

Prerequisites: AS/SC/AK/MATH2270 3.0; one of AS/
SC/MATH2010 3.0, AS/SC/MATH2015 3.0, AS/SC/AK/
MATH2310 3.0; AS/SC/AK/MATH3010 3.0 is also desirable, though not essential, as prerequisite for students presenting AS/SC/MATH2010 3.0 or AS/SC/AK/MATH2310 3.0.

Degree credit exclusion: AS/MATH4200A 6.0.

Coordinator: H. Freedhoff


AS/SC/MATH3280 6.0
Actuarial Mathematics

1998/99 CALENDAR COPY:Actuarial mathematics at a level appropriate for examination 150 of the Society of Actuaries. Topics include survival distributions and life tables, premiums and reserves for life insurance and annuities, multiple life functions, multiple decrement models, valuation theory of pension plans.

This course is intended for students contemplating careers in the actuarial profession. It will help prepare them for Examination 150 of the Society of Actuaries. We will cover most of Chapters 3-10 of the official text, N.L. Bowers et al., Actuarial Mathematics, 2nd ed. (Society of Actuaries). There is inadequate time in a one-year course to cover Chapters 11, 15 and 16, the remaining material needed for Exam 150. However, students who complete this course should acquire enough background to enable them to study the omitted chapters on their own.

The prerequisites are a sound knowledge of both interest
theory and probability theory. For the probability prere-
quisite, students should have completed MATH2030 3.0. For interest theory the preferred prerequisite is MATH2280 3.0. Those who have completed MATH2580 6.0 with a grade of B+ or better may be allowed to enrol, but such students should note that MATH3280 6.0 is considerably more advanced, and requires much more mathematical ability, than MATH2580 6.0.

The final grade will be based on a combination of assignments, midterm tests and a final examination.

Prerequisites: AS/SC/MATH2280 3.0;
AS/SC/AK/MATH2030 3.0.

Coordinator: S.D. Promislow


AS/SC/AK/MATH3330 3.0 FW
Regression Analysis

1998/99 CALENDAR COPY:Simple regression analysis, multiple regression analysis, matrix form of the multiple regression model, estimation, tests (t- and F-tests), multicollinearity and other problems encountered in regression, diagnostics, model building and variable selection, remedies for violations of regression assumptions. First term.

This course is closely linked with MATH3230 3.0, Analysis of Variance, for which it is a prerequisite. Students will use the computer heavily in these courses, but no previous courses in computing are required.

MATH3330 3.0 will focus on linear models for the analysis of data on several predictor variables and a single response. The emphasis will be on understanding the different models and statistical concepts used for these models and on practical applications, rather than on the formal derivations of the models. The approach will require the use of matrix representations of the data, and the geometry of vector spaces, which will be reviewed in the course.

The first term (MATH3330 3.0) will cover the basic ideas of multiple regression, having reviewed in depth the elements of simple linear regression. The second term (MATH3230 3.0) will have a major focus on models with categorical variables as predictors (classical ANOVA, or Analysis Of Variance).

The nature of the course requires that students be involved on a constant basis with the material, and not fall behind.

The text and grading scheme have not been determined as we go to press.

Prerequisites: One of AS/SC/MATH1132 3.0,
AS/SC/AK/MATH2570 3.0, AS/SC/PSYC2020 6.0,
or equivalent; some acquaintance with matrix algebra
(such as is provided in AS/SC/MATH1025 3.0,
AS/SC/MATH1505 6.0, AS/AK/MATH1550 6.0,
AS/SC/MATH2021 3.0, or AS/SC/AK/MATH2221 3.0).

Degree credit exclusions: AS/SC/MATH3033 3.0,
AS/SC/GEOG3421 3.0, AS/SC/PSYC3030 6.0,
AS/ECON4210 3.0, AK/PSYC3110 3.0.

Coordinator: Fall: D. Montgomery. Winter: P. Song


AS/SC/AK/MATH3410 3.0 W
Complex Variables

1998/99 CALENDAR COPY:Analytic functions, the Cauchy-Riemann equations, complex integrals, the Cauchy integral theorem, maximum modulus theorem. Calculations of residues and applications to definite integrals, two-dimensional potential problems and conformal mappings.

Some polynomials, such as x^2 + 1, have no roots if we confine ourselves to the real number system, but do have roots if we extend the number system to the complex numbers, which can be defined as the set of all numbers of the form a + ib , where a and b are real and i is a new kind of number satisfying i^2 + 1 = 0, where the basic arithmetic operations have the same structure as those of the real numbers. The complex numbers include the reals (case b = 0), and the extended system has the desirable property that not only x^2 + 1 but every [nonconstant -- Ed.] polynomial now has a root. In the system of complex numbers certain connections are seen between otherwise apparently unconnected real numbers. A striking example is Euler's formula e^(pi i) = -1 , which is a simple consequence of the extension to complex variables of the familiar exponential and trigonometric functions. The concepts and operations of calculus (differentiation, integration, power series, etc.) find their most natural setting in complex (rather than real) variables. The present course is intended to give the student a basic knowledge of complex numbers and functions and a basic facility in their use.

Further topics include: Complex numbers and their representations; functions of a complex variable; extensions of elementary functions from real to complex variables; mapping of elementary functions; complex differentiation; Cauchy's theorem; Cauchy's integral formula and its applications; complex power series; the residue theorem and its applications.

Prerequisite: AS/SC/MATH2010 3.0 or AS/SC/MATH2015 3.0 or AS/SC/AK/MATH2310 3.0. (AS/SC/AK/MATH3010 3.0 is also recommended as a prerequisite for students who have taken AS/SC/MATH2010 3.0.)

Coordinator: Martin Muldoon


AS/SC/AK/MATH3430 3.0 W
Sample Survey Design

1998/99 CALENDAR COPY:Principal steps in planning and conducting a sample survey. Sampling techniques including simple random sampling, stratified random sampling, cluster sampling, and sampling with probabilities proportional to size. Estimation techniques including difference, ratio, and regression estimation.

This course deals with the peculiarities of sampling and inference commonly encountered in sample surveys in medicine, business, the social sciences, political science, natural resource management, and market research. Attention will be focused on the economics of purchasing a specific quantity of information. (See next page.)

That is, methods for designing surveys that capitalize on characteristics of the population under study will be presented, along with associated estimators to reduce the cost of acquiring an estimate of specified accuracy. (The emphasis will be on the practical applications of theoretical results.)

The text will be R. L. Scheaffer, W. Mendenhall, and L. Ott, Elementary Survey Sampling (5th ed.), PWS-Kent.

The final grade may be based on assignments (5%), class tests (40%) and a final examination (55%).

Prerequisite: AS/SC/MATH2030 3.0
or AS/SC/MATH3030 3.0 (taken before 1993/94)
or AS/SC/AK/MATH3330 3.0 or AS/SC/PSYC3030 6.0.

Degree credit exclusions: These courses may not be taken for credit after taking MATH3430: AK/MATH2752 3.0,
AK/ADMS3352 3.0, AK/ECON3130 3.0.

Coordinator: P. Peskun


AS/SC/MATH3440 3.0 F
The Mathematics of Physics

(Note: This course is offered on an irregular basis.) 1998/99 CALENDAR COPY:Various topics in physics which require mathematical analysis are discussed. The emphasis is on showing how such mathematical techniques as multivariable calculus, ordinary and partial differential equations, probability and calculus of variations arise in the study of these topics. Normally offered in alternate years.

Particular emphasis will be placed on the symbiotic evolution of the techniques of calculus and physics which, ultimately, resulted in Maxwell's formulation of the equations of electromagnetism and special relativity.

The text for the course will be David M.Bressoud, Second year Calculus, but this will be supplemented by various materials made available in class. Students must be prepared to read this text on their own since much of the class time will be devoted to student presentations of assigned problems and extra readings.

These student presentations will form 20% of the final course mark. Of the remaining 80%, 60% will be based on written solutions to assigned exercises and 20% on a final examination.

For more information, a course web page will soon be available.

Prerequisite: AS/SC/AK/MATH2270 3.0.

Prerequisite or corequisite:
AS/SC/MATH2015 3.0 or AS/SC/AK/MATH3010 3.0.

Degree credit exclusion: Not open to Physics majors.

Coordinator: J. Steprans
[See note to "Coordinator" of MATH2041 for spelling of this name.]



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