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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 7511 - Business Intelligence 3
ISDS 7103 - Operations Research 3
EXST 7087 - Survival Analysis and Non-linear models 3
MKT 7716 - Multivariate Statistics 3
Total 15
Spring Courses Hours
ISDS 7990 – Practicum Project 6
Approved Electives
Choose 2: ISDS 7220, ISDS 7401, ISDS 7540, MKT 7110, MKT 7130​
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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