Georgia Institute of Technology College of Sciences

This is a 2 week intense course, with lectures in the morning and computational lab in the afternoon. 

Students will be asked to have a laptop with Matlab on it.
 

The course will meet in the mornings for lecture, break for  lunch, and reconvene for the lab in the afternoons.

This is a 2 week intense course, with lectures in the morning and computational lab in the afternoon. 

Students will be asked to have a laptop with Matlab on it.
 

The course will meet in the mornings for lecture, break for  lunch, and reconvene for the lab in the afternoons.

Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression and analysis of variance.

Mathematical logic and proof, mathematical induction, counting methods, recurrence relations, algorithms and complexity, graph theory and graph algorithms.

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.

This course is a problem oriented introduction to the basic concepts of probability and statistics, providing a foundation for applications and further study.

Elementary combinatorial techniques used in discrete problem solving: counting methods, solving linear recurrences, graph and network models, related algorithms, and combinatorial designs.

Pass/Fail only. A course for graduate students in Mathematics to help prepare for the written comprehensive exams in Algebra and Analysis. Offered Summer 2017.

In 2017, the course was split into two sections: MATH 8802 ALG and MATH 8802 ANA.