This course introduces students to the various statistical learning methods and their applications in statistics modeling. Topics discussed includes review on elementary probability and statistics learning, principles and different types of statistical learning, simple and multiple linear regression, regression models, time series models, principal components analysis, decision trees, and cluster analysis.The statistical programming language R will be introduced.