The Ph.D. program in Statistics and Analytics is designed to prepare students for a career in research and teaching at the university level or in equivalent positions in non-academic environments. The program will provide students with comprehensive training in many areas including statistical theory, data analytics, computing, and application of statistical methods to problems in a wide range of fields.

Students entering the program typically have a strong undergraduate degree in statistics, mathematics, or a closely related discipline. Although some knowledge of undergraduate probability and statistics is expected, skills in mathematics and computer science are more important. The program is designed to strengthen and cultivate the growth of these skills essential for their careers, whether it be in academia or industry.

For students who are interested in teaching at universities, the program has a unique component of one semester of teaching internship. For students who are interested in industrial jobs, the program has a component of professional internship to provide students with work experience in a non-academic environment. These integrative experiences have allowed graduates of the program to find success in both academia and non-academic environments alike.

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 with a Bachelor's degree must have successfully completed 20 semester hours of mathematics and statistics including Introduction to Probability and Statistics (equivalent to STA 382), Linear Algebra (equivalent to MTH 223), Multivariate Calculus (equivalent to MTH 233), and Advanced Calculus (equivalent to MTH 532). A minimum GPA of 2.7 overall (or 3.0 in the final sixty semester hours of graded coursework toward the bachelor's degree) and 3.0 in mathematics and statistics is required.

Applicants with a master’s degree in statistics or mathematics equivalent to the master’s degree at Central Michigan University must have a minimum GPA of 3.0 in their graduate work.

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.

Applicants must provide general GRE examination scores and three letters of recommendation directly to the Department of Statistics, Actuarial and Data Sciences. Click here to visit the Information for Prospective Graduate Students page and the process of admission and assistantships applications.

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.
The list of coursework below is for students who have an undergraduate degree satisfying the admission requirements. For students who enter the program with a master's degree, up to 30 hours of relevant graduate coursework may be counted towards the program requirements depending on individual’s background in consultation with an academic advisor. The required minimum number of 45 credit hours will not be affected.

A student with a bachelor's degree must have earned at least 50 of the total 75 hours at the 600 level or above. Those entering with a master's degree must have earned at least 35 hours at the 600 level or above taken at CMU. At least 15 hours of the coursework must be earned at the 700 level or above, excluding the dissertation and the internship credits.
Part I: Required Courses (48 hours)
Core Courses (30 hours)
  • STA 575 – Statistical Programming for Data Management and Analysis 3(3-0) 
  • STA 582 - Experimental Designs 3(3-0) 
  • STA 584 - Mathematical Statistics I 3(3-0) 
  • STA 590 - Applied Statistical Methods II 3(3-0) 
  • STA 591 - Data Mining Techniques I 3(3-0) 
  • STA 675 - Advanced Statistical Data Management and Simulation 3(3-0) 
  • STA 682 - Linear Models 3(3-0) 
  • STA 684 - Theory of Statistical Inference 3 (3-0) 
  • STA 686 - Multivariate Analysis 3(3-0) 
  • STA 691 - Advanced Data Mining Techniques 3(3-0)
Core Electives (18 hours)
Select 18 hours from the following:
  • STA 580 – Applied Statistical Methods I 3(3-0) 
  • STA 588 – Sampling Techniques 3(3-0) 
  • STA 589 – Time Series Forecasting 3(3-0) 
  • STA 678 - Categorical Data and Survival Analysis 3(3-0) 
  • STA 694 - Theory and Applications of Bayesian Statistics 3(3-0) 
  • STA 696 - Special Topics in Statistics and Analytics 1-6(Spec) 
  • STA 697 - Independent Study 1-9(Spec) 
  • STA 782 - Generalized Linear Models 3(3-0) 
  • STA 784 - Theory of Estimation 3(3-0) 
  • STA 785 – Distribution Theory and Applications 3(3-0) 
  • STA 796 – Special Topics in Advanced Statistics and Analytics 1-6(Spec) 
  • STA 797 - Independent Study 1-9(Spec)
Part II: Elective Courses (12 hours)
Graduate level courses in Computer Science, Actuarial Science, Mathematics or any discipline related to student’s research work. These courses are required to be approved by the academic advisor or the dissertation advisor. In general, the electives are to enhance student’s research work or to broaden advanced knowledge in statistics and/or analytics. Examples are EGR 600, CPS 685, ITC 510, ITC 630, ITC 686, MTH 632, MTH 634, MTH 636, MTH 761, MTH 762.

Part III: Qualifying Examination
Prior to conducting dissertation research work, a Ph.D. candidate must pass two qualifying exams in the areas of Theoretical Statistics and Applied Statistics. A maximum of two attempts in each area are allowed. A second failure in one area eliminates the student from the Ph.D. Program.

Internship (3 hours)
Students are required to take three (3) hours of internship. Students can choose either teaching internship or non-teaching professional internship.
  • STA 794 - Internship: College Teaching in Statistics 3-6(Spec) 
  • STA 795 - Advanced Practicum/Internship 3-6(Spec)
  • Dissertation (12 hours)
    • STA 898 - Dissertation 1-30 (Spec) 
Total: 75 semester hours

*An Example of Course Work Map for Ph.D. in Statistics and Analytics for students with a Bachelor degree:
  • YEAR 1
    • Fall Semester: STA 575, STA 580
    • Spring Semester: STA 590, STA 675
  • YEAR 2
    • Fall Semester: STA 582, STA 584
    • Spring Semester: Elective, STA 684
    • Summer: Theory Stat Exam
  • YEAR 3
    • Fall Semester: STA 591, STA 682
    • January: App Stat Exam
    • Spring Semester: Elective, STA 691
    • Summer: Internship
  • YEAR 4
    • Fall Semester: Elective, STA 686
    • Spring Semester: Elective, STA 898 (6)
    • Summer: STA 898 (3)
  • YEAR 5
    • Fall Semester: Elective, STA 898 (6)
    • Spring Semester: Dissertation Defense