This is a first course in business statistics, with an emphasis on techniques for data analysis and inference in management. Students are assumed to be familiar with basic descriptive statistics, probability theory and probability distributions. Presentation of technical material is combined with hands-on analysis of data to aid managerial decision making. Meeting will be a mix of lecture and problem-solving. There are two objectives for the course. First, to develop a conceptual understanding of statistics and the role of data analysis in management. Second, to master the mechanics of applied statistics.

Units: 3
Usually offered: Fall, Spring
Grading: Regular Grades
Prerequisites: MATH 113 or MATH 116 or MATH 122B, or MATH 125
Identical to: ECON 276,  MAP 276,  MGMT 276, BNAD 276

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 and more. The business media, 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/BNAN 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 and another business-relevant statistical package, such as SPSS or SAS.

Units: 4
Usually offered: Fall, Spring
Grading: Regular Grades
Prerequisites: BNAN 276
Identical to: BNAD 277