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Mathematical logic and proof, mathematical induction, counting methods, recurrence relations, algorithms and complexity, graph theory and graph algorithms.
Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression and analysis of variance.
This course is a problem oriented introduction to the basic concepts of probability and statistics, providing a foundation for applications and further study.
Fourier series, Fourier integrals, boundary value problems for partial differential equations, eigenvalue problems
Linear algebra in R^n, standard Euclidean inner product in R^n, general linear spaces, general inner product spaces, least squares, determinants, eigenvalues and eigenvectors, symmetric matrices
Elementary combinatorial techniques used in discrete problem solving: counting methods, solving linear recurrences, graph and network models, related algorithms, and combinatorial designs.
Review of linear algebra and ordinary differential equations, brief introduction to functions of a complex variable.
Geometry, convergence, and structure of linear operators in infinite dimensional spaces. Applications to science and engineering, including integral equations and ordinary and partial differential equations.
Topics include L^p, Banach and Hilbert spaces, basic functional analysis.
Functions, the derivative, applications of the derivative, techniques of differentiation, integration, applications of integration to probability and statistics, multidimensional calculus.
Georgia Institute of TechnologyNorth Avenue, Atlanta, GA 30332Phone: 404-894-2000