BNAN277

036737

Corporations today are said to be data rich but information poor. For example, retailers can easily process and capture millions of transactions every day. In addition, the widespread proliferation of social and economic activity on the Internet leaves behind a rich trail of micro-level data on consumers, their purchases, interactions, retailers and their offerings, auction bidding, music sharing, so on and so forth. The business press, recruiters, and the companies that hire our students constantly tell us of the need for business people to manage very large data sets and use analytical modeling to achieve business results. This course will provide foundations of quantitative analyses to equip students with the necessary background to further develop their analytical skills in their business majors. It will focus on analysis of real business datasets in the context of business-related decision making.
This course introduces and reinforces the concepts, methods, and applications of quantitative and statistical tools that are used by business decision makers. It will be taught as a sequel to BNAD 276, reviewing Statistics concepts and Single Linear Regression and moving to Multiple Linear Regression and other concepts that are useful to business analytics, such as visualization techniques and software. The course will have a heavy focus on hands-on analysis of real business datasets. It will use Excel for data management, cleaning, and statistical analysis and Tableau for data visualization. Students will be required to work with large data sets to perform statistical analysis, extract valuable insights, and communicate their findings in professional manner that can be understood by someone not versed in statistics.

GRD - Regular Grades A, B, C, D, E

Undergraduate

016233