Description

A leader in a data driven world requires the knowledge of both data-related (statistical) methods and of appropriate models to use that data. This Business Analytics class focuses on the latter: it introduces students to analytical frameworks used for decision making though Excel modeling. These include Linear and Integer Optimization, Decision Analysis, and Risk modeling. For each methodology students are first exposed to the basic mechanics, and then apply the methodology to real-world business problems using Excel. Emphasis will be not on the "how-to" of Excel, but rather on formulating problems, translating those formulations into useful models, optimizing and/or displaying the models, and interpreting results. The course will prepare managers who are comfortable with translating trade-offs into models, understanding the output of the software, and who are appreciative of quantitative approaches to decision making. Business analytics makes extensive use of data and modeling to drive decision making in organizations. This class focuses on introducing students to analytical frameworks used for decision making to make sense of the data, starting from the basics of Excel and working up to advanced modeling techniques.