MASTER OF SCIENCE IN APPLIED STATISTICS

This program offers general courses in classical statistical methods, mathematical statistics, regression and experimental design, as well as specialized courses in topics including data mining, quality control, multivariate analysis, statistical computing, linear models and nonparametric statistics. The program is flexible, allowing students to structure courses in a manner that complements their career objectives.

  • The applied statistics program began over 25 years ago.
  • The program averages 15 graduates per year.
  • The program offers graduate teaching and research assistantships with competitive stipends, including partial tuition.
  • Opened in the fall of 2015, the Analytics Lab offers students cutting edge technology in a collaborative environment.
  • A business degree is not required to start earning your MS in Applied Statistics.

The M.S. degree in Applied Statistics requires 30 hours, half of which are track specific. There are two different tracks within this degree. These include: Statistics and Analytics. There are five required courses common to both tracks of study.

The 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.

  • ST 552 – Applied Regression Analysis
  • ST 553 – Applied Multivariate Analysis
  • ST 554 – Mathematical Statistics I
  • ST 555 – Mathematical Statistics II
  • ST 560 – Statistical Methods

Task Specific Courses

  • ST 521 – Statistical Data Management
  • ST 522 – Advanced Statistical Data Management
  • ST 531 – Knowledge Discovery & Data Mining I
  • ST 532 – Advanced Data Mining II
  • ST 575 – Statistical Quality Control
  • ST 561 – Design of Experiment

Statistics Electives

  • ST 591 – Independent Study
  • ST 597 – Special Topics

Statistics Track

  • ST 561- Design of Experiment

12 hours of approved electives are also required.

Analytics Track

  • ST 521 – Statistical Data Management
  • ST 522 – Advanced Statistical Data Management
  • ST 531 – Knowledge Discovery & Data Mining I
  • ST 532 – Advanced Data Mining II

Contacts

Program Coordinator
Dr. Cali Davis
348-1608
353 Alston Hall
Email: cdavis@culverhouse.ua.edu

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