Business Analytics

Catalog description

Prerequisites: MATH 1030 and spreadsheet modeling or equivalent competency. This course covers all three pillars of analytics (descriptive, predictive and prescriptive) for data-driven business applications at the graduate level. Topics include, but are not limited to, probability, hypothesis testing, regression analysis, time series, linear/integer programming and data mining. Real world examples and case studies in various business domains, including supply chain, finance, marketing and information systems will be introduced. It lays the foundation for students to be successful in more advanced analytical-oriented courses.