Quant. Methods in Business (QMB)

The course is an introduction to Business Analytics. It covers managerial statistical tools in descriptive analytics and predictive analytics, including regression. Other topics covered include forecasting, risk analysis, simulation, data mining, and decision analysis.

In this course, students learn how to make better business decisions by solving complex optimization problems. Topics include Decision Trees, Linear and Non-Linear programming, Integer and Dynamic programming, Simulation and Real-Time Analytics.

The general objective of this course is to acquaint students with the practice of data-driven decision making. This course exposes students to the tools, techniques and principles that managers employ to translate business and external data (including customer data, financial data, business operations data, industry data etc.) into actionable decisions and policies. The emphasis of the class will be on transformation of data into models using various software applications, and interpretation of the results for making real life business decisions.