QTM2000
Case Studies in Business Analytics Spring 2016 Section 01:T/Th 9:45AM-11:20AM – Gerber 102
Section 02:T/Th 11:30AM-1:05PM – Gerber 102

Instructor: Denise Sakai Troxell Office: Babson Hall 318 Office hrs: By appointment only | Phone: (781) 239-6309e-mail: troxell@babson.edu |

Course Description (from catalog):

This course builds on the modeling skills acquired in the QTM core with special emphasis on case studies in Business Analytics – the science of iterative exploration of data that can be used to gain insights and optimize business processes. Data visualization and predictive analytics techniques are used to investigate the relationships between items of interest to improve the understanding of complex managerial models with sometimes large data sets to aid decision-making. These techniques and methods are introduced with widely used commercial statistical packages for data mining and predictive analytics, in the context of real-world applications from diverse business areas such as marketing, finance, and operations. Students will gain exposure to a variety of software packages, including R, the most popular open-source package used by analytics practitioners around the world. Topics covered include advanced methods for data visualization, logistic regression, decision tree learning methods, clustering, and association rules. Case studies draw on examples ranging from database marketing to financial forecasting. This course satisfies one of the core requirements towards the new Business Analytics concentration. It may also be used as an advanced liberal arts elective or an elective in the Quantitative Methods or Statistical Modeling concentrations. Prerequisite: QTM1010 (or QTM2420)

Course Objectives:

* To familiarize students with the fundamental principles and techniques of business analytics.

* To instill appreciation