Data Analytics

Catalog description

This course builds on basic statistics courses and explores contemporary topics in the areas of data science and business analytics. Grounded in methodological theory and practice, the course addresses such topics as forecasting and multiple regression, simulation, risk analysis, linear and non-linear optimization, and decision analysis. Maintaining a state-of-the-art perspective, the course introduces students to the use of recently emerging techniques, such as market basket analysis. Acknowledging the changing nature of analytic software, the course uses R, a robust, open-source statistical platform with an enormous library of multidisciplinary application. The course has multiple goals, including preparing students to understand the application of data analytics, helping students develop skill in applying techniques to complex organizational problems, and facilitating lifelong learning. Students must achieve a minimum grade of C. Prerequisite: MA 132 or MA 218 with a minimum grade of C-.