Summer 2000 Course Outline
MATH 5450
6.0 
Geometry
for Teachers 
This course will assume a year of linear
algebra. It will combine explorations of plane and spherical geometry, use of dynamic
geometry programs (in particular The Geometer’s Sketchpad) and projects generated by
students. The marks will be base on inclass work, assignments and a project (which you
are encouraged to do in a group).
Text: David Henderson, Experiencing Geometry on Plane and
Sphere, PrenticeHall, 1996.
Instructor: W. Whiteley, S616 Ross, ext. 33971, email:
whiteley@mathstat.yorku.ca 

MATH 6003D
3.0 
Mixed
Models 
Mixed (random and fixed) effects models
have been developed under different guises in many different fields: hierarchical models,
multilevel linear models, randomeffects models, randomcoefficient regression models,
covariance component models, etc. These models have very wide applications to:
longitudinal data analysis, unbalanced nested designs, hierarchical data structures, meta
analysis, etc. This course will consider both the theory and the practical aspects of the
use of these models. As with most new methods, mixed models present many potential
pitfalls. The course will stress model interpretation, diagnostics and dealing with
numerical problems. A major component of the course will be the analysis of a suitably
complex real data set.
Prerequisites
An intermediate course in linear models such as MATH3330 or MATH3033,
an introduction to likelihood.
Text: J.C. Pinheiro, D.M. Bates. 2000. Mixed Effects Models
in S and SPlus. Springer, New York
Instructor: Professor G. Monette, 263 SSB, Ext. 77164 

MATH 6003P
3.0 
Mathematical
Modelling 
Mathematical modelling is the basis of
almost all applied mathematics. A ‘realworld' problem is dissected and phrased in a
mathematical setting, allowing it to be simplified and ultimately solved. In this course,
models in a variety of applications are derived, simplified, and analyzed.
Using examples from industrial, environmental, biological, and
financial applications, we discuss the uniformity of the approach used by applied
mathematicians in these different contexts and various analytical and numerical
techniques. Only a basic mathematical background in calculus
and analysis is required. The course is designed to develop and improve
problem solving skills for graduate students. Students will be encouraged to attend one of
the industrial problem solving workshops/study groups.
Prerequisites
Calculus & Analysis such as Math3210 and Differential Equations
(e.g. Math2270) or equivalent. Some basic programming skills and knowledge of Partial
Differential Equations will be helpful.
Text: A.C. Fowler, Mathematical Models in the Applied
Sciences, Cambridge University Press, 1996.
Instructor: H. Huang, S622, Ext. 66090 

MATH 6003Q
3.0 
Introduction
to Lie Algebras and their Representations 
This is an introductory course on Lie
algebras and representation theory. Lie Algebra is a very elegant area which involves many
parts of mathematics and has a lot of applications in both mathematics and physics.
Elementary structural properties of semisimple Lie algebras over the complex field,
finite irreducible root systems, Weyl groups, and sltheory will be studied. Although the
primary subject in this course is finite dimensional Lie algebras, some basics about
certain important infinite dimensional Lie algebras such as the Heisenberg algebra,
Virasoro algebra and KacMoody Lie algebra will be touched upon as well.
Prerequisites: A good knowledge of Linear Algebra (Math 2022, or
equivalent) and some familiarity with Abstract Algebra (Math 3020, or equivalent).
Instructor: Y. Gao, S624 Ross, ext. 33952 

MATH 6003R
3.0 
Robust
Statistics 

Robust statistics are those which provide
protection against violation of assumptions underlying the statistical procedure. In this
course, basic robustness concepts including sensitivity, influence function and breakdown
points of estimates and tests will be discussed. Classical procedures will be evaluated in
terms of robustness and alternative techniques will be developed. Mestimator,
Lestimator, Restimator, LMS estimator, LTS estimator and other robust estimators will be
introduced and their efficiency compared with the classical estimators will be
investigated. Besides, the resistent diagnostics will be described. Starting from the
location problem, we will move on to regression problems. The statistical software package
SPLUS will be used.
Prerequisites
Math 6621 or equivalent and Math 6620B or equivalent
Instructor: Y. Wu, N609 Ross, Ext. 88604 

MATH 6530
3.0 
Differential
Geometry 
The course will begin with an introduction
to differentiable manifolds, including also matrix groups as an important class of
examples. The tangent bundle to a smooth manifold will be defined and there will be some
discussion of vector bundles and smooth bundles. Included in this section is the
discussion of vector fields on a manifold and the differential map on the corresponding
tangent bundles that is induced by a smooth map betwen manifolds.
A second section of the course introduces differential forms on a
smooth manifold including also a discussion of differential forms with values in a vector
space. Integration of differential forms, the Poincare Lemma and Stokes' Theorem will be
studied.
A third section of the course introduces the theory of connections on a
manifold, with some discussion of affine connections on a vector bundle. Riemannian
manifolds, the curvature tensor and Riemannian connections will be discussed. Time
permitting, some properties of the curvature tensor will be developed, and generalized
versions of Green's Theorem on a Riemannian manifold will be discussed.
Prerequisites:
(i) A good knowledge of advanced calculus of several variables, linear
algebra and some modern algebra. (ii) A basic understanding of point set topology, or
permission of the instructor.
Reading List:
There is no one textbook that covers adequately all the topics above in
an introductory manner, with applications. I will use the following book as a REQUIRED
TEXT:
M. do Carmo, "Riemannian Geometry", Birkhauser (1992).
OTHER BOOKS that are useful sources for some of the above topics are:
1. M. do Carmo, " Differential Forms and Applications",
Springer Verlag (Universitext) (1991).
2. M.W. Hirsch, "Differential Topology", Springer Verlag,
Graduate texts in mathematics.
3. F.W. Warner, "Foundations of Differentiable Manifolds and Lie
Groups", SpringerVerlag, Graduate texts in Mathematics.
4. G.E. Bredon, "Topology and Geometry", SpringerVerlag,
Graduate Texts in Mathematics.
5. S. Kobayashi and K. Nomizu, "Foundations of Differential
Geometry, Volume I", J. Wiley and Sons.
Instructor: D. Spring, Glendon College, York Hall 351, 4876731
ext. 66815 
