QTM6610: Analytics for Decision-Makers
1.5 credits
Data exploration and data-driven decision making are integral to identifying and validating business opportunities. Depending on the nature of the problem and the entrepreneurial context, techniques ranging from classical statistical methods (descriptive and inferential statistics) to more recent advances in big data and tools (Excel, R, Tableau) might provide the greatest utility and deepest insights. In this course, students encounter a selection of these techniques and develop their ability to formulate analytics problems in ambiguous contexts, quantify the performance of various solutions, and articulate the key results of their analysis to a non-technical audience, including through visualization methods.