This is an application of mathematics to various fields. It consists of two parts: Introduction to Mathematical Modeling, and some Mathematical Models: Optimization Models, Dynamic Models and Probabilistic Models. Introduction to Mathematical Modeling discusses steps in modeling difference equations, different modeling processes and model fittings. Several problems involving optimization modeling, dynamic modeling and probabilistic modeling were discussed and solved using analytical and computation methods.
The course requires student to present original or expository research paper in a seminar.
This is an introductory course in probability covering axiomatic probability space, discrete and continuous random variables, special distributions, mathematical expectation, conditional probability and independence, multivariate distributions. Sampling and Sampling Distribution, Point and Interval estimate, and Hypothesis testing and its applications.
Students are required to participate in conferences and seminars in applied mathematics and its allied field.