This course is designed for students who want to be optimally prepared to perform quantitative analysis at a level consistent with and exceeding expectations for MBA interns in positions where quantitative sophistication is required. The only prerequisite for the course is First Year Decision Analysis; no additional quantitative experience or acumen is needed. The course will focus primarily on data analysis, used to gain useful insights into relationships and to make better, more useful forecasts. In addition to more advanced treatment of regression analysis with its goal of students being able to build and apply sophisticated regression models, students will become familiar with other common approaches to forecasting, such as rudimentary time-series analysis. Students also will be able to improve their ability to structure, analyze, and manage situations involving uncertainty and risk, using Crystal Ball simulation, decision trees, and the other tools introduced in the Decision Analysis course. Finally, the course will introduce students to the concepts of optimization using Excel’s Solver add-in, used to determine how to optimally allocate resources in situations involving complex trade offs.


Academic course objectives:


·         Familiarize students with the basic tools of management science and how apply them effectively to help solve managerial problems

·         Build recognition of the basic tools of data analysis, statistical inference, and regression

·         Develop students’ familiarity with rudimentary time-series analysis

·         Give students a working knowledge of optimization using Excel’s Solver tool


Elements of the course grade:


Class contribution       40%

Final exam                   60%