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MSA Curriculum

The MSA curriculum emphasizes the use of advanced data management tools, applied statistics, and operations research techniques. Students use SAS, SQL, R, SPSS, Tableau, and other tools to analyze large real-world data sets to increase return on investment, improve customer retention, reduce fraud, and improve decision making.  As part of the MSA program, students complete a major team project using a large data set provided by a sponsoring organization. Students present their results and recommendations to the sponsoring organization in a formal executive decision briefing. Students with degrees in business, engineering, economics, statistics, mathematics, and the sciences will benefit the most from this degree. 

Key topics include the structured query language (SQL), multivariate statistics, clustering, data-mining, design of experiments, optimization methods, and predictive modeling. Teamwork, written and oral communication, presentation skills and state-of-the-art visualization techniques are stressed throughout the curriculum.

 Degree Requirements 
  • 36 hours of graduate level course work with a 3.0 average or above
  • Passing grade on the MSA Comprehensive Exam
  • Successful completion of a major project

A typical course list is shown here:

Summer Courses Hours
EXST 4087 - SAS Data Access & Programming 3
ISDS 7024 - Advanced Statistical Analysis 3
ISDS 7302 - Data Mining​ 3
Total 9

Fall Courses Hours
ISDS 7510 - Database Management with SQL and R 3
ISDS 7103 - Operations Research
EXST 7087 - Survival Analysis and Non-linear models 3
EXST 7037 - Multivariate Statistics 3
ISDS 7990 - Practicum Project 3
Total 15
Spring Courses Hours
ISDS 7511 - Business Intelligence
ISDS 7990 – Practicum Project 3
Recommended Electives:                                                                                             
ISDS 7220 - Supply Chain Management
ISDS 7401 - Healthcare Informatics
ISDS 4118 - Web Analytics
Other Approved Electives:
CSC  4740  - Big Data Tech
ECON 4633 - Time Series  
EXST 7036  - Categorical Data Analysis 
EXST 7152  - Advanced Topics in Statistical Modeling
ISDS 7070  - SPECIAL TOPIC / PROJECT (topics vary; permission of department)​
* students are required to ensure that they have appropriate prerequisites for electives taken outside the department.​

Total 12

Practicum Project 

The practicum project is a team-based effort in which students work with leading organizations to solve real analytics problems. 

  • Teams include two-three students and one faculty member.
  • The teams work to understand the business problem and then clean and analyze the data.
  • The projects begin in the fall and end in the spring with a presentation to the sponsoring organization.
  • Past projects included the following industries: automotive, energy, government, healthcare, higher education, sports, and telecommunications.
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