Teaching

Teaching Assistant

Basic computational methods for interpolation, least squares, approximation, numerical quadrature, numerical solution of nonlinear equations, systems of linear equations, and initial value problems for ordinary differential equations. Emphasis on the methods and their computational properties rather on their analytic aspects.

Teaching Assistant

Basic concepts of linear algebra: vector spaces, applications to line and plane geometry, linear equations and matrices, similar matrices, linear transformations, eigenvalues, determinants and quadratic forms.

Teaching Assistant

Introduces the basic concepts of statistical reasoning and modern computer based techniques for organizing and interpreting data. Students will learn how to summarize data, how to interpret variability in data in terms of probability, and how to apply statistical methods to examples. Real world applications from the social, behavioral and biological sciences are used to illustrate the usefulness of statistical techniques.

Teaching Assistant

An introductory course to probability, the mathematical theory of randomness, and to statistics, the mathematical science of data analysis and analysis in the presence of uncertainty. Applications of statistics and probability to real world problems are also presented.

Undergraduate Teaching Assistant

Fundamental concepts of computer science: data structures, analysis of algorithms, recursion, trees, sets, graphs, sorting.

Undergraduate Teaching Assistant

Introduces macroeconomic analysis and policy, teaching students to apply economic tools to major issues like national income, unemployment, and inflation in a global context.