Business Analytics (BAN)

BAN 610. Introduction to Business Analytics.3 Credits.

This course develops ideas for helping to make decisions based upon the examination of data. Topics include variability, data display and summary statistics, regression, and correlation, probability, probability distributions, sampling, the central limit theorem, confidence intervals and hypothesis testing. Attention is also given to the design of experiments and analysis of variance, frequency distributions, statistical inference and sampling theory.

Offered: Every year, Fall and Spring

BAN 615. Predictive Modeling.3 Credits.

The course introduces the techniques of predictive modeling and analytics in a data-rich business environment. It covers the process of formulating business objectives, data selection, preparation and partition to successfully design, build, evaluate and implement predictive models for a variety of practical business applications (such as marketing, customer retention, delinquency and collection analytics, fraud detection and insurance). Predictive models such as classification and decision trees, neural networks, regressions, pattern discovery analysis and other techniques are studied.

Prerequisites: Take BAN 610;
Offered: Every year, Fall and Spring

BAN 620. Text Mining.3 Credits.

This course builds upon previously introduced data mining methods, focusing specifically on techniques for text extraction and mining. Topics include efficient text indexing; document clustering and classification; information retrieval models; enhancement of structured data; scenario detection techniques; and using textual data in predictive models.

Prerequisites: Take CIS 628;
Offered: Every year, Fall and Spring

BAN 650. Data Visualization.3 Credits.

This course provides an introduction as well as hands-on experience to the field of data visualization. Students learn basic visualization design and evaluation principles to create meaningful displays of quantitative and qualitative data. They learn techniques for visualizing multivariate, temporal, text-based, geospatial, hierarchical and network/graph-based data.

Offered: Every year, Spring and Summer

BAN 660. Optimization.3 Credits.

This course focuses on developing computational methods to solve various optimization problems. Advanced regression analysis, time series analysis and other techniques are used to support improved forecasting and decision making.

Prerequisites: Take BAN 610 BAN 615;
Offered: Every other year

BAN 661. Web Analytics and Web Intelligence.3 Credits.

This course focuses on the analysis of a variety of web metrics including tracking, traffic and visitor behavior, tactics and strategies to successfully market on the Web to make data-driven decisions. Business analytics tools and techniques are utilized to extract and analyze web-scale data to guide strategic decision making. Topics address solutions for measurably higher leads, sales, brand recognition, customer satisfaction or lower service costs.

Prerequisites: Take BAN 610;
Offered: Every year, Spring

BAN 662. Insurance Analytics.3 Credits.

This course leverages predictive modeling and analytics, optimization, and business intelligence to support data-driven decisions in the property-casualty insurance industry. Key topics include measuring underwriting performance, risk analysis and attributes of high performing insurance systems.

Prerequisites: Take BAN 615;
Offered: Every year, Summer

BAN 663. Programming for Data Analysis.3 Credits.

Students learn to program and use R for effective data analysis. Reading data, accessing R packages, writing functions, debugging, profiling code and organizing and commenting code also are covered. Working examples of topics in statistical data analysis are provided. The course also addresses installation and configuration of software as necessary for a statistical programming environment.

Offered: Every other year

BAN 664. Health Care Analytics.3 Credits.

This course provides a foundation on data analytics in health care and an understanding of the main concepts and issues. Contemporary tools and technologies are applied to develop an analytics solution to selected health care problems.

Prerequisites: Take CIS 620;
Offered: Every year, Fall

BAN 690. Business Analytics Capstone.3 Credits.

The capstone course in the MSBA program is designed to enable students to directly utilize what has been learned in the tools and applications courses to analyze and offer solutions for a major business challenge. A definition of the problem, analysis of options and a comprehensive presentation of findings and solutions are required components of the course.

Prerequisites: Take BAN 610 BAN 615 BAN 620 BAN 650 CIS 620 CIS 627 CIS 628;
Offered: Every year, Fall and Summer