This course is intended to introduce and give an understanding of numerical methods for the solution of ordinary and partial differential equations. The methods will be derived and the convergence and stability of the methods will be analyzed. The applications of these methods in solving real world problems will be emphasized. Students will be exposed to modern mathematical software for the practical use of the problems and for better visualization of the convergence and stability of these methods.

This course aims at introducing students to methods of analyzing multivariate data. It introduces students to the notion of principal components factor analysis, various multivariate distributions, analysis of variance, multivariate analysis of variance (MANOVA), multivariate regression and multidimensional scaling and cluster analysis. At the end of the course students would have also considerably improved their knowledge of applied linear algebra and matrix theory and to be somewhat competent with at least one statistical software package.