College of Liberal Arts & Sciences

# PhD in Statistics

## Application Found Here

Updated 02/10/2022

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 successfully passing both the MS final examination in statistics and the creative component (in exceptional cases, a student may petition to go through the PhD qualifying procedure early), 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 and assesses the student's potential for research. The body of work will include the MS final examination in statistics, the creative component, and course work. This evaluation and assessment results in one of three decisions—the student is officially admitted into the PhD program; the student must reapply to go through the PhD qualifying procedure after accumulating a larger body of work for evaluation; or the student is not admitted into the PhD program.

**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 | 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 |

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: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 |

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 |

DATA:7350 | High-Dimensional Probability for Data Science | 3 |

STAT:4540 | Statistical Learning | 3 |

STAT:4580 | Data Visualization and Data Technologies | 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 | 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 |

## PhD Final Examination

Students typically take the PhD final (comprehensive) examination at the beginning of the third year of graduate study, during the week before fall classes begin. Students who do not succeed the first time they take the exam may repeat it once. Ordinarily, this second opportunity to pass the exam will occur one year later, during the week before fall classes begin. However, a student who performs well on one area of the exam but not the other may, in consultation with their advisor and the Director of Graduate Studies, petition the department to move up their second opportunity to the week before the next spring semester's classes begin. The department's decision on whether to grant this petition will take into account any extenuating circumstances.

The comprehensive examination consists of a written core examination and an oral examination in two of the following four areas:

statistical inference (topics in STAT:5100 Statistical Inference I, STAT:5101 Statistical Inference II, and STAT:7100 Advanced Inference I);

linear models (topics in STAT:7200 Linear Models);

probability (topics in STAT:6300 Probability and Stochastic Processes I and STAT:7300 Foundations of Probability I); and

statistical computing (topics in STAT:5400 Computing in Statistics, and STAT:7400 Computer Intensive Statistics).

Ph.D. students in the actuarial science/financial mathematics concentration area have the option of taking only one of the four examinations listed above and an actuarial science/financial mathematics examination designed by their advisor and approved by the director of graduate studies.

## PhD Committee

Upon passing the PhD final examination, 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.

## Prospectus

Within 18 months of passing the PhD final exam, the candidate should present a written and oral prospectus to the committee. The prospectus describes the problems the student is considering for the thesis, relevant background material, ideas for solving the problems, and any preliminary results. Failure to successfully complete the prospectus within 24 months of passing the PhD final exam will jeopardize the continuation of a student's financial support.

## 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 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.