The Master of Science in Applied Statistics

Gain hands-on experience and learn advanced business intelligence skills while working on real-world projects.

The Master of Science in Applied Statistics program at Manderson prepares graduates for careers as trained statisticians capable of leveraging data analysis and other technical skills in any number of fields.

The program averages 15 graduates per year and offers teaching and research assistantships with competitive stipends, including partial tuition.

A key focal point of the program is the opportunity to utilize the Marillyn A. Hewson Data Analytics Lab, which allows of the use of cutting-edge data analysis technology in a collaborative environment, as well as other services and functions of the Institute of Data and Analytics at Culverhouse.

Students do not need a business degree to earn an MS in Applied Statistics. Learn more about the requirements of the Master of Science in Applied Statistics Program in the course catalog.

Program Info

The MS degree in Applied Statistics is a flexible program, allowing students to structure courses in a manner that complements their career objectives.

The program requires 30 hours, half of which are track-specific. There are two different tracks within this degree: Statistics and Analytics, with five required courses common to both tracks of study. This program offers general courses in:

• Classical statistical methods
• Mathematical statistics
• Regression
• Experimental design

As well as specialized courses in topics including:

• Data mining
• Quality control
• Multivariate analysis
• Statistical computing
• Linear models
• Nonparametric statistics.

Electives may be earned in additional coursework with the approval of a faculty advisor. The program of related courses may vary from student to student and depends on the student’s interests and academic background. When most of the coursework is completed, the student must pass a written comprehensive examination OR a professional exam such as the Actuarial P Exam, SAS Predictive Modeler Exam, or the ASQ Certified Quality Engineer Exam.

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