Structured programming, verification of program validity, data structures, combinatorial problems, flow network algorithms, random number generators, simulation of random and nonrandom processes. Introduction to network and graph theoretic concepts. Consider properties with application in computational mathematics, social science decision making and physical science. Probability models, discrete and continuous random variables, sampling distributions, estimation, tests of hypothesis and simple linear regression. Eigenvalue problems, diagonalizing matrices, Jordan Canonical form, Linear Programming, Simplex method, game theory, applications in areas such as business, industry, economics, social sciences, and behavioral sciences.
Emphasis is on oral presentations by the students and discussion.