The objectives of this course are to develop an understanding of modern computationally intensive methods for statistical inference, exploratory data analysis, with applications. Advanced computational methods for statistics will be introduced, including univariate, multivariate and combinatorial optimization methods and simulation methods. In addition, the course will demonstrate how to apply the above techniques effectively for use on large data sets in practice. Finally, this course will show how to make inferences about populations of interest in data mining problems. In addition to that, other topics that will be covered including: theory of sampling distributions; principles of data reduction; interval and point estimation, sufficient statistics, order statistics, hypothesis testing, correlation and regression.