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, teamwork, 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 30-33 credit hours; including 3 hours of pre-requisites, 27 hours of course work and 3 hours of practicum/internship or Plan B project.

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.

Applicants must meet all CMU Graduate Studies admission requirements. International students should take note of any special admission considerations required by the College of Graduate Studies, including TOEFL requirements.

Applicants must have completed a minimum of 12 semester hours of mathematics and/or statistics courses that include the following: MTH 133 (Calculus II) or the equivalent, one course in linear algebra, and one course in statistics or probability. A grade point average of 3.0 in mathematics and statistics course work is required.

Applicants must submit a Statement of Purpose of at least 100 words and not to exceed two pages. The Statement of Purpose should explain their relevant academic and professional experiences, discuss motivation for applying to the program, and describe their goals after completing the program.

Admission for the M.S. program does not require GRE or letters of recommendations. However, applicants interested in a Graduate Assistantship position must submit a Graduate Assistantship Application form along with General GRE scores and three letters of recommendation directly to the Department of Statistics, Actuarial and Data Sciences. Evaluation for Graduate Assistantships is based on the nature of previous coursework, grades, general GRE scores, and letters of recommendation. The deadline for applying for a Graduate Assistantship is February 15. Application materials received after February 15 are considered on a rolling basis until all positions are filled. Both admission to the program and awards of Graduate Assistantships are competitive. Click here to visit the Information for Prospective Graduate Students page and the process of admission and assistantships applications.
Students may transfer into the degree program up to fifteen credits of course work from another similar graduate degree program, provided that the student earned a grade of B or better in the course and the course content is equivalent to the course taught in the degree program and approved by the program advisor.
Required Prerequisite Courses (0- 3 hours)
  • STA 580 - Applied Statistical Methods I 3(3-0)
*Note: Students who have not taken courses similar to STA 580 with comparable contents and textbooks are required to take the pre-requisite courses.

Required Courses I (15 hours)
  • STA 575 - Statistical Programming for Data Management and Analysis 3(3-0) 
  • STA 581 – Mathematical Statistics for Data Science 3(3-0) 
  • STA 591 - Data Mining Techniques I 3(3-0) 
  • STA 675 - Advanced Statistical Data Management and Simulation 3(3-0) 
  • STA 686 - Multivariate Analysis 3(3-0)
*Note: With the approval of the program advisor, students who have taken courses similar to STA 575 and/or STA 591 with comparable contents and textbooks may be allowed to replace the course(s) with elective course(s).

Required Courses II (9 hours)
Select one of the following tracks:
  • Track 1: Applied Statistics: 
    • STA 582 - Experimental Designs 3(3-0) 
    • STA 590 - Applied Statistical Methods II 3(3-0) 
    • STA 678 - Categorical Data and Survival Analysis 3(3-0)
  • Track 2: Analytics: 
    • ITC 510 - Software and Data Modeling 3(3-0) 
    • ITC 686 - Big Data Analytics 3(3-0) 
    • STA 691 - Advanced Data Mining Techniques 3(3-0)
Electives (3 hours)
Select from the following:
  • GEO 501 - Principles and Applications of Geographic Information System 3(2-2) 
  • MTH 586 - Operations Research I 3(3-0) 
  • STA 583 - Nonparametric Statistics 3(3-0) 
  • STA 587 - Statistical Theory and Methods for Quality Improvement 3(3-0) 
  • STA 588 - Sampling Techniques 3(3-0) 
  • STA 589 - Time Series Forecasting 3(3-0) 
  • STA 592 - Six Sigma: Foundations and Techniques for Green Belts 3(3-0) 
  • STA 595 - Introduction to Bayesian Statistics 3(3-0) 
  • STA 682 - Linear Models 3(3-0) 
  • STA 696 - Special Topics in Statistics and Analytics 1-6(Spec) 
  • STA 697 - Independent Study 1-9(Spec)

Students in Track 1 can take the Required Courses II for Track 2 as electives. Students in Track 2 can take the required Courses II for Track 1 as electives.

Note 1: Graduate level courses in any discipline different from Mathematics or Statistics with approval of the program advisor may be used as elective courses.

Note 2: Students who are exempted from STA 575 and/or STA 591 under Required Courses I will take a total of 6 or 9 hours under electives.

Practicum Requirements (3 hours)
Select from the following:
  • STA 695 - Practicum/Internship 3(Spec) 
  • STA 698 – Plan B Project 3(Spec)
Total: 30-33 semester hours

An example of Course Work Map for M.S. in Applied Statistics and Analytics:
  • Applied Statistics Track
    • YEAR 1
      • Fall Semester: STA 575, STA 580, STA 581
      • Spring Semester: STA 590, STA 675
      • Summer: Internship or Plan B Paper
    • YEAR 2
      • Fall Semester: STA 591, STA 582, STA 686
      • Spring Semester: STA 678, Elective
  • Analytics Track
    • YEAR 1
      • Fall Semester: STA 575, STA 580, STA 581
      • Spring Semester: Elective, STA 675
      • Summer: Internship or Plan B Paper
    • YEAR 2
      • Fall Semester: ITC 510, STA 591, STA 686
      • Spring Semester: ITC 686, STA 691