College of Liberal Arts & Sciences
PhD in Statistics (prior to 2023)
Application Found Here
Updated 6/27/2023
The Doctor of Philosophy program in statistics requires a minimum of 76 s.h. of graduate credit, including work completed for the MS degree.
The Graduate College requires a minimum g.p.a. of 3.00 to graduate with a PhD degree; however, the Department of Statistics and Actuarial Science requires a higher g.p.a. of at least 3.40 to earn the PhD in statistics. This includes all courses used to meet degree requirements plus additional courses that are relevant to a student's program.
PhD students complete required course work, including four courses in one of four concentration areas: biostatistics, probability/mathematical statistics, data science, or actuarial science/financial mathematics (see "Concentration Areas" below for area descriptions and course lists). They may take course work or seminars in other departments to relate an area of specialization to other fields of knowledge, to acquire the ability to use electronic digital computing equipment, or to learn non-English language skills necessary for reading scientific journals and communicating with scholars in other languages.
PhD Qualifying Procedure
Students enter the PhD program in one of two tracks:
Statistics—After passing the MS final examination, a student who will choose either biostatistics, probability/mathematical statistics, or data science as the selected concentration
area, can request, by notifying the director of graduate studies, to go through the PhD
qualifying procedure. Upon this request, the faculty evaluates the student's body of work which includes the MS final examination in statistics, course work, and evidence for research potential. Usually, students need to have achieved A in at least one 7000 level course, have completed at least 1 s.h. of STAT:6990 Readings in Statistics (and is enrolled in a second semester of STAT:6990), and have identified a faculty member who agreed to serve as the student’s PhD advisor to get admitted. In exceptional cases, a student may petition to go through the PhD qualifying procedure early, or be admitted to the PhD program directly. However, passing the MS final exam is required before any student can take the PhD comprehensive exam (see the section below on the PhD comprehensive exam).
Actuarial Science—After successfully passing the MS final examination in actuarial science (in exceptional cases, a student may petition to go through the PhD qualifying procedure early), a student who will choose actuarial science/financial mathematics as the selected concentration area, can request, by notifying the director of graduate studies, to go through the PhD qualifying procedure. Upon this request, the faculty evaluates the student's body of work and assesses the student's potential for research. The body of work will include the MS final examination in actuarial science, professional examinations passed, and course work. This evaluation and assessment results in one of two decisions—the student is officially admitted into the PhD program in the actuarial science/financial mathematics concentration area, or the student is not admitted into the PhD program.
Students complete the program by passing the PhD final (comprehensive) examination and writing and defending a dissertation. Students usually complete the program three years after earning the MS degree.
A program that does not conform to the requirements described below but is of high quality may be approved by the department chair.
If a PhD student in statistics registers for 6 s.h. or more (not including STAT:6990 Readings in Statistics and STAT:7990 Reading Research) in a semester, then at least 2 s.h. of these need to be from course(s) offered by the statistics department. (This rule is intended to discourage students from taking too many non-statistical courses, especially after they start doing research for their dissertation.
The Ph.D. with a major in statistics requires the following coursework.
Actuarial Science/Financial Mathematics Concentration Area
Actuarial science/financial mathematics emphasizes the theory of actuarial science, finance, and risk management. It is excellent preparation for academic positions in universities that offer actuarial science programs and for positions in the insurance, pension, and financial industries.
One of these sequences from the M.S. in actuarial science program:
Course Numbers | Title | Hours |
STAT:4100-4101 | Mathematical Statistics I-II | 6 |
STAT:5100-5101 | Statistical Inference I-II | 6 |
All of these from the M.S. in actuarial science program:
Course Numbers | Title | Hours |
ACTS:4130 | Quantitative Methods for Actuaries | 3 |
ACTS:4180 | Life Continencies I | 3 |
ACTS:4280 | Life Contingencies II | 3 |
STAT:6300 | Probability and Stochastic Proceses I | 3 |
All of these:
Course Numbers | Title | Hours |
DATA:7350 | High-Dimensional Probabilty for Data Science | 3 |
STAT:5120 | Mathematical Methods for Statistics | 3 |
STAT:7100 | Advanced Inference I | 3 |
STAT:7101 | Advanced Inference II | 3 |
STAT:7200 | Linear Models | 4 |
STAT:7300 | Foundations of Probability I | 3 |
STAT:7400 | Computer Intensive Statistics | 3 |
STAT:7500 | Statistical Machine Learning | 3 |
STAT:7990 | Reading Research | 19 |
STAT:7190, STAT:7290, and STAT:7390 | Seminars (required 2) | 2 |
At least four of these; at least one must be at the Ph.D. level (numbered 7000 or above):
Course Numbers | Title | Hours |
ACTS:6200 / DATA:6200 | Predictive Analytics | 3 |
ACTS:7730 | Advanced Topics in Actuarial Science/Financial Math | 3 |
STAT:4560 | Statistics for Risk Modeling I | 3 |
STAT:4561 | Statistics for Risk Modeling II | 3 |
STAT:6301 | Probability and Stochastic Processes II | 3 |
STAT:7301 | Foundations of Probability II | 3 |
STAT:7560 | Time Series Analysis | 3 |
FIN:7110 | Finance Theory I | 3 |
FIN:7130 | Finance Theory II | 3 |
Biostatistics Concentration Area
Biostatistics emphasizes exposure to various biostatistical methods, such as survival analysis, categorical data analysis, and longitudinal data analysis. It prepares students for consulting and other positions in industry.
All of these from the M.S. in statistics program:
Course Numbers | Title | Hours |
DATA:5400 / STAT:5400 | Computing in Statistics | 3 |
STAT:5090 | ALPHA Seminar | 1 |
STAT:5100 | Statistical Inference I | 3 |
STAT:5101 | Statistical Inference II | 3 |
STAT:5200 | Applied Statistics I | 4 |
STAT:5201 | Applied Statistics II | 3 |
STAT:6220 | Statistical Consulting | 3 |
STAT:6300 | Probability and Stochastic Processes I | 3 |
STAT:6990 | Readings in Statistics (two consecutive enrollments) | 2 |
All of these:
Course Numbers | Title | Hours |
STAT:5120 | Mathematical Methods for Statistics | 3 |
STAT:7100 | Advanced Inference I | 3 |
STAT:7101 | Advanced Inference II | 3 |
STAT:7200 | Linear Models | 4 |
STAT:7300 | Foundations of Probability I | 3 |
STAT:7400 | Computer Intensive Statistics | 3 |
STAT:7990 | Reading Research | 18 |
STAT:7190, STAT:7290, and STAT:7390 2 | Seminars (select 2) | 2 |
At least four of these; at least one must be at the Ph.D. level (numbered 7000 or above):
Course Numbers | Title | Hours |
DATA:7350 | High-Dimensional Probabilty for Data Science | 3 |
STAT:6530 | Environmental and Spatial Statistics | 3 |
STAT:7510 | Analysis of Categorical Data | 3 |
STAT:7570 | Survival Data Analysis | 3 |
BIOS:6650 | Causal Inference | 3 |
BIOS:6720 | Machine Learning for Biomedical Data | 3 |
BIOS:7240 | High-Dimensional Data Analysis | 3 |
BIOS:7310 | Longitudinal Data Analysis | 3 |
Data Science Concentration Area
The data science track emphasizes the theory, methodology, and application of techniques for working with and learning from data. This concentration area prepares students to develop new methods for visualizing and modeling data, managing reproducible data analysis workflows, and collaborating with scientists and other data stakeholders. It is excellent preparation for students interested in academic, industrial, or government positions that involve data visualization, modeling, and analysis.
All of these from the M.S. in statistics program:
Course Numbers | Title | Hours |
DATA:5400 / STAT:5400 | Computing in Statistics | 3 |
STAT:5090 | ALPHA Seminar | 1 |
STAT:5100 | Statistical Inference I | 3 |
STAT:5101 | Statistical Inference II | 3 |
STAT:5200 | Applied Statistics I | 4 |
STAT:5201 | Applied Statistics II | 3 |
STAT:6220 | Statistical Consulting | 3 |
STAT:6300 | Probability and Stochastic Processes I | 3 |
STAT:6990 | Readings in Statistics (two consecutive enrollments) | 2 |
All of these:
Course Numbers | Title | Hours |
DATA:4540 / STAT:4540 | Statistical Learning | 3 |
DATA:4580 / STAT:4580 | Data Visualization and Data Technologies | 3 |
DATA:7350 | High-Dimensional Probability for Data Science | 3 |
STAT:5120 | Mathematical Methods for Statistics | 3 |
STAT:7100 | Advanced Inference I | 3 |
STAT:7200 | Linear Models | 4 |
STAT:7400 | Computer Intensive Statistics | 3 |
STAT:7500 | Statistical Machine Learning | 3 |
STAT:7990 | Reading Research | 18 |
STAT:7190, STAT:7290, and STAT:7390 | Seminars (select 2) | 2 |
At least two of these; at least one must be at the Ph.D. level (numbered 7000 or above):
Course Numbers | Title | Hours |
DATA:6200 / ACTS:6200 | Predictive Analytics | 3 |
DATA:4750 | Probabilistic Statistical Learning | 3 |
STAT:6530 | Environmental and Spatial Statistics | 3 |
STAT:6560 | Applied Time Series Analysis | 3 |
STAT:6970 | Topics in Statistics | 3 |
STAT:7101 | Advanced Inference II | 3 |
STAT:7300 | Foundations of Probability I | 3 |
STAT:7510 | Analysis of Categorial Data | 3 |
STAT:7520 | Bayesian Analysis | 3 |
STAT:7560 | Time Series Analysis | 3 |
Probability/Mathematical Statistics Concentration Area
Probability/mathematical statistics emphasizes a broad, solid foundation in techniques and underpinnings of mathematical statistics. Its focus on breadth and depth is intended to produce well-rounded, knowledgeable scholars. It is excellent preparation for academic positions in mathematical statistics and industrial or government positions that require broadly trained statisticians with a strong understanding of statistical theory.
All of these from the M.S. in statistics program:
Course Numbers | Title | Hours |
STAT:5090 | ALPHA Seminar | 1 |
STAT:5100 | Statistical Inference I | 3 |
STAT:5101 | Statistical Inference II | 3 |
STAT:5200 | Applied Statistics I | 4 |
STAT:5201 | Applied Statistics II | 3 |
STAT:5400 | Computing in Statistics | 3 |
STAT:6220 | Statistical Consulting | 3 |
STAT:6300 | Probability and Stochastic Processes I | 3 |
STAT:6990 | Readings in Statistics (two consecutive enrollments) | 2 |
All of these:
Course Numbers | Title | Hours |
STAT:5120 | Mathematical Methods for Statistics | 3 |
STAT:7100 | Advanced Inference I | 3 |
STAT:7101 | Advanced Inference II | 3 |
STAT:7200 | Linear Models | 4 |
STAT:7300 | Foundations of Probability I | 3 |
STAT:7400 | Computer Intensive Statistics | 3 |
STAT:7990 | Reading Research | 18 |
STAT:7190, STAT:7290, and STAT:7390 2 | Seminars (select 2) | 2 |
At least four of these; at least one must be at the Ph.D. level (numbered 7000 or above):
Course Numbers | Title | Hours |
DATA:7350 | High-Dimensional Probabilty for Data Science | 3 |
STAT:6301 | Probability and Stochastic Processes II | 3 |
STAT:7301 | Foundations of Probability II | 3 |
STAT:7500 | Statistical Machine Learning | 3 |
STAT:7520 | Bayesian Analysis | 3 |
STAT:7560 | Time Series Analysis | 3 |
BIOS:6650 | Causal Inference | 3 |
BIOS:7240 | High-Dimensional Data Analysis | 3 |
Committee
The candidate chooses a committee of at least four members, which is approved by the advisor. At least four of the faculty members must be University of Iowa tenure-track faculty members. At least three of the faculty members must be from the major department (defined as faculty members who hold any appointment in the major department), and University of Iowa tenure-track faculty members.
The department may request the Graduate College dean's permission to replace one of the four committee members by a recognized scholar of professorial rank from another academic institution.
After passing the MS final exam and within 12-18 months (12 months is ideal, 18 months is acceptable) of being admitted to the PhD program, the candidate should present a written and oral prospectus to the committee, which serves as the PhD Comprehensive Exam. The prospectus describes the problems the student is considering for the thesis, an extensive review of relevant background materials, open problems of interest and ideas for solving the problems, and any preliminary results. Failure to successfully complete the prospectus within 18 months of being admitted to the PhD program will jeopardize the continuation of a student's financial support.
PhD final exam (defense of the dissertation)
Students should plan to defend their dissertation within 24-30 months (24 months is ideal, 30 months is
acceptable) of passing the PhD comprehensive exam. Failure to successfully defend the dissertation within 30 months of
passing the PhD comprehensive exam or within 5 years of starting the graduate program at the University of Iowa, whichever data comes first, will jeopardize the continuation of a student's financial support.
Each PhD committee member will sign the examination report as satisfactory, reservations, or unsatisfactory. A vote of "Reservations" should only be used when a faculty member feels that the deficiencies displayed by the student were modest, and can be readily rectified. In the event of a report with two or more votes of "Reservations," the actions required of the student, by the committee, that are necessary to correct the deficiencies must be recorded and submitted to the Graduate College with the examination report form. The statement must specify the time allowed for completion of the aforementioned actions. For instance, if additional course work is required, a list of suitable courses must be presented. If the candidate needs to rewrite their research prospectus, the deficient areas must be identified, etc. If the candidate satisfies the required actions in the specified period of time, the comprehensive exam will be recorded as "Satisfactory" as of that date. If the actions are not satisfied on time, or if the actions are not of sufficient quality, the comprehensive exam will be recorded as "Unsatisfactory" as of that date. The candidate will not be admitted to the PhD final examination (dissertation) of the dissertation until a grade of "Satisfactory" has been recorded for the comprehensive exam.
In the case of a report of unsatisfactory on a comprehensive examination, the committee may grant the candidate permission to attempt a reexamination not sooner than four months after the first examination. The examination may be repeated only once, at the option of the department.
Application for Degree
The student must file an application for an anticipated degree with the Registrar not later than ten weeks after the start of the semester or one week after the start of the summer session in which the degree will be conferred. The department will send in the information required (date, time, location or venue, committee member, title of diserations, etc.) The student must have the application signed by his or her advisor. Failure to file the Application for Degree by the deadline will result in postponement of graduation to a subsequent session.
PhD Timeline
The timeline below describes the key milestones in the PhD program. Meeting these milestones on time constitutes "adequate progress" toward the PhD degree. See also the sample schedule below. Note that the year numbers refer to those entering the program with a baccalaureate degree. Students who enter after some amount of graduate study elsewhere may in effect be starting in year 2 or year 3.
Year 1
- Complete at least 18 semester hours of coursework with a GPA of at least 3.4, including courses needed to prepare for the MS Final Examination.
Year 2
- Take the MS Final Examination before classes start in the fall. If necessary, re-take the exam in January.
- Complete at least 18 s.h. of coursework, including all prerequisites to STAT:7100 (22S:253), STAT:7200 (22S:255), and STAT:7300 (22S:203) with a GPA of at least 3.4 -- in essence meeting the requirements of the MS program.
- Satisfactorily complete and present the creative component by mid-spring.
- Begin working on identifying a potential dissertation advisor and dissertation topic.
Year 3
- Pass the comprehensive examination. (In certain cases where it was not possible to take the needed 7000-level courses by the end of the second year, this may need to be deferred to the fourth year.)
- Complete at least 15 s.h. of courses with a GPA of 3.4 of higher, including a seminar course [STAT:7190 (22S:291), STAT:7290 (22S:295), or STAT:7390 (22S:293)].
- Identify the dissertation advisor, dissertation topic, and dissertation committee.
Year 4
- Complete most remaining core and concentration-area courses with a GPA of 3.4 or higher, a seminar course [STAT:7190 (22S:291), STAT:7290 (22S:295), or STAT:7390 (22S:293)], and 3-6 s.h. of STAT:7990 (22S:299) Reading Research.
- Present the dissertation prospectus. Present the dissertation prospectus. Note that students cannot provide food or beverages at the prospectus meeting.
Year 5
- Complete all course requirements, including remaining hours of STAT:7990 (22S:299) Reading Research, with a GPA of at least 3.4.
- Complete the dissertation, including meeting dissertation deposit deadlines.
- File the Application for Degree during the final semester.
- Defend the dissertation. Note that students cannot provide food or beverages at the dissertation defense meeting.