This is an application of mathematics to various fields. It consists of three parts: Optimization Models, Dynamic Models and Probabilistic Models. Real world problems are modelled and solved using analytical and computational methods. Some computer applications are used to approximate solutions, if exact solution is not feasible.
The course requires the students in groups to model and solve problems in Optimization, Dynamics and Probabilistic, and present it in a Seminar Form.
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