The Master of Science in Applied Statistics and Analytics is a Master's program in data science.  It is a two-year program that is designed for students interested in a career that requires advanced knowledge and skills in statistics and data analytics.  The curriculum is interdisciplinary involving statistics, computer science, and other disciplines.  It is designed to provide students with advanced knowledge and real-world applications in data science, team work, and presentations that are essential in the workplace.

The M.S. in Applied Statistics and Analytics degree has two tracks:

  • Applied Statistics Track
  • Analytics Track

Students choose the track of study no later than the third semester in the program.

The program requires 30-36 credit hours; including 6 hours of pre-requisites, 27 hours of course work and 3 hours of practicum/internship.  

Practicum/internship may take place in a variety of different formats chosen by students.  It can be applied research projects supervised by a faculty advisor, an internal or external consulting project, an internship at a company, and so on.

Admission Requirements for M.S. in Applied Statistics & Analytics

To be admitted to the program, candidates must meet the following criteria:

  • Hold at least a four year undergraduate degree or equivalent degree from a college of university of recognized standing and meet the requirements for regular admission to the College of Graduate Studies.
  • Overall undergraduate average GPA of 3.0 or higher
  • Minimum of 12 semester hours of mathematics and/or statistics with an average GPA of 3.0 or higher which must include:
  • Calculus II
  • Linear Algebra
  • One course in statistics or probability
  • Minimum TOEFL for international students: See the page Information for Prospective Graduate Students for more information
  • General GRE is recommended.  If the student applies for a graduate assistantship, general GRE is required.  The GRE requirement may be waived by the Department in exceptional cases)

Program Requirements for the M.S. in Applied Statistics and Analytics

  • Required Prerequisite Courses (0-6 hours)
    • STA 580 - Applied Statistical Methods 1  3(3-0)
    • STA 584 - Mathematical Statistics 1  3(3-0)
  • Required Courses 1 (18 hours)
    • STA 575 - Statistical Programming for Data Management and Analysis  3(3-0)
    • STA 591 - Data Mining Techniques 1  3(3-0)
    • STA 675 - Advanced Statistical Data Management and Simulation  3(3-0)
    • STA 684 - Theory of Statistical Inference  3(3-0)
    • STA 686 - Multivariate Analysis  3(3-0)
    • STA 695 - Practicum/Internship  3(Spec)
  • Required Courses II  (9 hours) (Select of on the following tracks)
    • Applied Statistics Track
      • STA 5​82 - Experimental Designs  3(3-0)
      • STA 590 - Applied ​Statistical Methods II  3(3-0)
      • STA 678 - Categorical Data and​ Survival Analysis  3(3-0)
    • Analytics Track
      • ITC 51​0 - Software and Data Modeling  3(3-0)
      • ITC 686 - Big Data​ and Analytics  3(3-0)
      • STA 691 - Advanced Data Mining Techniques  3(3-0)
  • Elective Course (3-9 hours)
    • Students may select elective course work from a variety of options in Statistics, Computer Science, Mathematics, Geographic Information Systems, and disciplines in Business, Health Professions, and other areas.

Total Credit Hours: 30-36