Program Director: James Stamey

Associate Dean for Graduate Programs: Patsy Norman

Objectives

The Master of Science in Business Analytics (MSBA) is designed to provide graduates with the knowledge and skills to leverage analytics tools that assist businesses to overcome data-related challenges. The program is cross-disciplinary in nature, encompassing multiple fields of study within the School of Business and courses from the Department of Statistical Science in the College of Arts and Sciences.

Admission

Applicants must have a bachelor's degree from an accredited university or college. Applicants must present a grade point average and scores on the GMAT or GRE that are predictive of success in this program. Applicants must adhere to the general admissions requirements for graduate study at Baylor University. All applicants will need to demonstrate proficiency in Python and have completed at least one course in statistics/QBA. Additional admissions requirements can be found under Business School Admissions.

Curriculum

The MSBA is a 36-hour program with courses from MIS, STA, and various business disciplines. This degree is intended to prepare students for careers as professional business analysts by:

• Learning the fundamentals of information technology and statistics
• Learning tools to understand and visualize data
• Learning fundamental skills in modeling and analysis of multivariate data
• Learning tools for predictive data analysis and forecasting
• Improving programming skills to the professional level for data analytics
• Providing a framework to examine ethical implications of collecting and managing big data

Course List

Code	Title	Hours
Required Courses
STA 5300	Statistical Methods (Summer)	3
MIS 5340	Database Management Systems	3
MIS 5390	Ethics in Data Analytics	3
MIS 5322	Advanced Python for Analytics	3
MIS 5342	Business Intelligence	3
MIS 5343	Seminar in Data Visualization	3
STA 5384	Multivariate Statistical Methods	3
STA 5303	Applied Regression Analysis	3
Select three courses from the following		9
STA 5371	Methods in Data Mining and Management
STA 5362	Time Series Analysis
STA 4350	Statistical Machine Learning
STA 5373	Computational Statistical Methods
CSI 5352	Advanced Object-Oriented Development
CSI 5357	Cloud Computing
ECO 5347	Econometric Theory and Methods
ECO 5351	Data Science I
ECO 5352	Data Science II
ECO 5349	Causal Inference and Research Design
MKT 4360	Customer Analytics
STA 5V85	Practice in Statistics	3
Total Hours		36