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Why study applied statistics online through OSU?

This professional master’s degree is available entirely online, making it an attractive option for working professionals as well as traditional students. The M.S. in Applied Statistics at OSU focuses less on the mathematical underpinnings of statistics and instead emphasizes the practical application of statistical methodology. While this terminal degree is not intended as a precursor to doctoral studies, it does qualify you for working in industry and academia.



OSU uses Canvas for our learning management system and hosts your online courses and content. From lectures to discussions to submitting assignments, all course interaction is completed entirely online. All you need is the necessary discipline and access to computer capabilities. All instructors who teach online learning courses are the same quality faculty who teach on-campus courses.


Tips for Online Students



This degree requires 32 hours of coursework. It consists of two courses in analytics, two courses in experimental data analysis, two courses in applied mathematical statistics, one course in computer programming with SAS and R, a creative component capstone course and three electives.  


Courses are offered online annually. Courses within each sequence listed below must be taken in the listed order. Sequences of courses can be taken in any order or concurrently. See the course catalog for course descriptions.  


Plan of Study

Prior to enrollment in the 17th credit hour, all students must choose an advisor, committee members and fill out a plan of study online. The responsibility for doing so rests with the student and his/her advisor. A sample plan of study for students who wish to graduate in two years is below.


Course Sequence Fall Spring Fall Spring Summer
Analytics Stat 5543  Stat 5063      
Mathematical Statistics Stat 5253  Stat 5263      
Experimental Data Analysis    Stat 5023  Stat 5303    
Programming  Stat 5193        
Elective     Stat 5033     
Elective     Stat 5053     
 Elective        Stat 5073  
 Capstone         Stat 5002 

Grade Requirements

Students who receive more than two grades of C or below will be dismissed from the program. Students who receive a D in a course with a STAT prefix may be dismissed from the program.


Admissions Requirements

It is necessary to have an undergraduate degree, not necessarily in mathematics or statistics, to begin a program of study toward the M.S. degree in statistics. It is expected that some students will be admitted to the program who have either a bachelor's degree or a master's degree in some other field. However, the student should have a mathematical background which, as a minimum, is equivalent to these mathematics courses:


  • MATH 2144 Calculus I
  • MATH 2153 Calculus II
  • MATH 2163 Calculus III (Calculus of several variables)
  • STAT 5013 Statistics for Experimenters I or STAT 4013 Statistical Methods I

Students admitted to the program with deficiencies will be required to remedy such deficiencies. Prospective students are encouraged to remedy calculus deficiencies before applying. In addition to the above courses, each student is required to demonstrate competence in a computer programming language.


Other requirements are:

  • Transcripts
  • GRE scores
  • 2 letters of reference and CV are required
  • English Proficiency  scores, such as TOEFL scores, are required for international applicants
  • Teaching assistantships are not generally available for this program
  • Application Due Dates:
    • Domestic applications are due by July 1 (Fall entry), November 1 (Spring entry)
    • International application are due by July 1(Fall entry), November 1 (Spring entry)
    • Fall applicants wishing to remediate background deficiencies in the Summer prior to entry should contact the graduate coordinator


Oklahoma State University offers an affordable single rate for graduate students in online degree and certificate programs.

Cost details for in-state, online graduate students
Cost details for out-of-state online graduate students



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