Statistics and Analytics, Ph.D.
Minimum Totals for Graduation: 75 hours
The Ph.D. degree is a content-based degree program in Statistics, Actuarial and Data Sciences. Coursework is broadly distributed across the various areas of statistics and analytics. The Ph.D. degree is designed to: a) train well-prepared teachers to teach college level statistics and analytics, and conduct independent research effectively in their areas of expertise or b) prepare students with advanced knowledge and applications in statistics, actuarial and data sciences to work effectively in non-academic environments. Students have an opportunity to take a teaching internship or a non-teaching internship.
Admission Requirements, Retention & Termination Standards
Admission Requirement Snapshot
GPA: 2.7 (see Item 2 below)
Entrance Exam: GRE Application
Deadline: February 15 for consideration for assistantships
See Admission Requirement Details Below
Admission
Applicants must meet all CMU Graduate Studies admission requirements. International students should take note of any special admission considerations required by the Office 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 must have a minimum GPA of 3.0 in their graduate work.
Applicants must submit general GRE examination scores and three letters of recommendation directly to the Department of Statistics, Actuarial and Data Sciences.
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.
Both admission to the program and awards of Graduate Assistantships are competitive, with evaluation based on the nature of previous coursework, grades, general GRE scores, and letters of recommendation. Applicants interested in a Graduate Assistantship position must submit a Graduate Assistantship Application directly to the Statistics, Actuarial and Data Sciences Department.
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.
Program Requirements
Successful completion of the Ph.D., including coursework, internship, and dissertation, requires a minimum of 75 semester hours of graduate work beyond the bachelor's degree. Up to 30 hours of relevant graduate work may be transferred for students entering with a master’s degree. In order to obtain the Ph.D. degree the student must have a GPA of 3.0 (B) or better. 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.
Coursework
The program requires a minimum of 60 hours of coursework excluding internship and the dissertation credit beyond the bachelor's degree or 30 hours of such coursework after the master's degree. At least 15 hours of the coursework must be earned at the 700 level or above, excluding the dissertation and the internship credits. These hours are distributed among core courses and elective courses. The minimum hours that are required in each category is specified in parentheses. An advisor will assist a student in the selection of the courses. Courses in which a student earns or has earned a grade below C (2.0) do not count toward meeting any graduate degree requirements.
Students who enter with a bachelor's degree and have satisfied any of the course requirements prior to entering the program may be excused from that course requirement. For this to be approved, the student must complete the Course Requirement Waiver Form supplied by the department. However, the required total 75 credit hours will not be affected.
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, in consultation with an academic advisor. The required minimum number of 45 credit hours will not be affected.
For graduate students who transfer from a comparable graduate program, up to 15 hours of the relevant graduate work may be transferred, in consultation with an academic advisor. The transferred hours will be counted towards the required total 75 credit hours.
The list of coursework below is for students who have an undergraduate degree satisfying the admission requirements.
Program Requirements
Required Core 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 | 1-15(Spec) |
Elective Courses (12 hours)
Graduate level courses in Computer Science, Actuarial Science, Mathematics or any discipline related to the 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.
Total: 75 semester hours
Qualifying Examination
In the Ph.D. qualifying examinations, students are expected to demonstrate a broad knowledge of the topics and be able to integrate concepts and explain them at an appropriate level. Prior to conducting dissertation research work, a Ph.D. student must pass two qualifying exams given by the department in the areas of 1) Theoretical Statistics and 2) Applied Statistics.
Full-time students entering with a bachelor’s degree must pass both examinations by the end of their seventh semester counting from the semester they enter the Ph.D. program. If a student takes a leave of absence, then those semesters do not count towards the seven semesters.
Full-time students entering with a master’s degree must pass both examinations by the end of their fifth semester counting from the semester they enter the Ph.D. program. If a student takes a leave of absence, then those semesters do not count towards the five semesters.
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 a teaching internship or a non-teaching professional internship. Students must earn credits for the internship by registering for STA 794 for the teaching internship or STA 795 for the non-teaching professional internship. The teaching internship can only be taken after passing all the qualifying examinations.
For students who plan to take a teaching internship, prior to seeking a faculty teaching internship supervisor, the student is required to consult with his/her academic advisor. Teaching internship courses are at the undergraduate level, generally at the 400 level or below offered in the Department of Statistics, Actuarial and Data Sciences.
For students who plan to take a non-teaching professional internship, the student must consult with the internship faculty coordinator to arrange their internship with an external company (agency) and must complete a written contract with the company (agency) prior to registering for the non-teaching professional internship.
| STA 794 | Internship: College Teaching | 3(Spec) |
| STA 795 | Advanced Practicum/Internship | 3(Spec) |
Dissertation (12 hours)
Upon successful completion of the qualifying examinations, the student will select a dissertation supervisor. A dissertation supervisor must be a graduate faculty member in the Department of Statistics, Actuarial and Data Sciences. The student will form a dissertation committee of at least three graduate faculty members in consultation with the dissertation supervisor. This dissertation committee will be chaired by the supervisor(s) and must include at least two (2) other graduate faculty members. Two members of the dissertation committee must be from the Department of Statistics, Actuarial and Data sciences. A completed doctoral dissertation must be approved by the dissertation committee, and by the College of Graduate Studies.
Students are required to register for 12 hours of STA 898 (Dissertation) .The dissertation must consist of original work and can combine scholarly, analytical, creative and expository skills. It could consist of research on a topic in statistics, actuarial science or data science and their applications. Before starting the dissertation work, the project prospectus must be approved by the dissertation committee, and by the College of Graduate Studies.
Upon completion of coursework, qualifying examination, internship, and dissertation, the candidate for the Ph.D. degree must pass a final oral examination, which is a dissertation defense in a colloquium format. The student's dissertation committee determines whether the student passes the oral examination.
The dissertation must be prepared according to the regulations prescribed in the College of Graduate Studies most recent edition of the Preparation Guide to Doctoral Dissertations, Theses, Field Studies, and Plan B Papers and must be submitted to Dissertations Abstracts International.