PhD Program

The program described below is for students beginning prior to fall 2016. The current set of requirements is available in the Graduate Student Handbook.

The goal of the Statistics PhD program is to train students to conduct original methodological and/or theoretical research in statistics and to apply advanced statistical methods to scientific problems. Students are expected to take advanced graduate classes in the theory and applications of statistics and other relevant classes.

The Ph.D. program requires a Qualifying Exam, a Ph.D. Comprehensive Exam and a Final Oral Exam. The Ph.D. requires 90 hours of graduate credit, including a dissertation. At least 45 hours must be completed at UNL after the filing of the program of studies which must be approved by the student’s PhD graduate committee. The Ph.D. program will normally include at least 12 hours and at most 55 hours of dissertation research. (In Statistics, 20-25 hours is typical.) In addition there are specific course requirements and a research tool requirement.

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PhD Qualifying Exam

Entrance into the Department's Ph.D. program is determined by the Ph.D. Qualifying Exam. The same exam serves as both the Masters Exam and the Ph.D. Qualifying exam, though qualifying for the Ph.D. program requires a higher level of performance than passing at the Masters level.

The Statistics Ph.D. Qualifying Examination is intended to verify mastery of tasks that require integration among core courses, (STAT 882-883, 802, and 970). The exam is offered twice a year: 1) in January, during the week prior to the start of spring semester classes and 2) in August, prior to starting of semester classes and after final exams. The exam has two parts. The first is a closed-book exam of 5 hours. The second is an open-book exam of 5 hours. Your advisor or the chair of the Graduate Exam Committee (GEC) can supply additional information on the exam. Exam results will be given to the students within two weeks.

General Policies for the Ph.D. Qualifying exam

A student either qualifies for the PhD (high pass), passes for the MS or fails the entire exam. The Graduate Exam Committee (GEC) is responsible for soliciting questions from the faculty, and preparing and grading the exam. The GEC will inform the candidate of his/her exam score within a period of two weeks from the last day of the exam. If a student qualifies to pursue the PhD, the exam is valid for 2 years for admission to the PhD program. The exam may be taken twice and a third time if the student passes but does not qualify on the second try.

Course Requirements for the Ph.D. Degree

Each Ph.D. student in Statistics must take Stat 971 (Statistical Modeling), Stat 980 (Advanced Probability) and Stat 982 and Stat 983 (Advanced Inference I and II ). Also, the student must take 12 additional hours of 900 level classes, excluding STAT 970, STAT 997 and STAT 999.

Each student must complete Stat 971, 980, 982 and 983 with a grade of at least B in each. If a student completes any of these courses with a grade below B, his/her Supervisory Committee may either require the student to repeat certain courses or administer extra written exam(s) in area(s) where weakness is felt.

Administrative Procedures

  1. After a student has passed the Department's Ph.D. Qualifying Exam, but before he or she has earned 45 credit hours, the student forms a Ph.D. Supervisory Committee. The student must choose an Advisor, who will chair the Supervisory Committee and direct the dissertation. A form listing the Ph.D. Supervisory Committee must be filed with the Graduate Studies Office.
  2. A Program of Studies form must be filed with the Graduate Studies Office before the student has earned 45 credit hours. This form is completed with the advice and consent of the student's Supervisory Committee.
  3. Once a student has passed the Ph.D. Comprehensive Exam and satisfied the language requirement, the student must file the Admission to Candidacy form with the Graduate Studies Office. This form must be filed no later than seven months prior to graduation.

Research Tool Requirement

All Ph.D. students are expected to be proficient in at least one statistical computing language such as SAS, S-Plus, R, Statistica, SPSS, IMSL, etc. In addition, the student must complete a research tool requirement as described in the Department of Statistics Graduate Student Handbook.

PhD Comprehensive Exam

The students PhD Supervisory Committee will determine the timing and the content of the PhD Comprehensive Exam.


Students will write an original research dissertation, under the direction of their advisor and Supervisory Committee. The PhD program usually includes between 12-55 hours of dissertation research.

Final Oral Exam

After the PhD dissertation is completed, all students must complete an oral exam – their thesis defense. The thesis defense is open to the public. Complete details are available on the Graduate Studies website.

Seminar Participation

Seminars and colloquia are a valuable part of a student's training. Regular participation in all departmental colloquia and seminars in the student's area of interest is expected of all Ph.D. candidates. The student's advisor will help direct the seminar participation.

Deadlines for Current PhD Students

  • Doctoral committee: All students must form their supervisory committee prior to the completion of 45 credit hours (usually at the start of their third year in the program). Your committee must consist of at least four graduate faculty, or non-graduate faculty approved to perform specified graduate faculty duties. One committee member must be an NU graduate faculty member from outside the department.
  • Program of studies: After forming the doctoral committee, students will complete a PhD program of studies. Changes may be submitted in writing at a later date, with approval of your advisor.
  • Application for candidacy: After you’ve has completed your PhD comprehensive exam (not the qualifying exam!), you must apply for candidacy at least 7 months before your final dissertation defense.
  • Application for graduation: The graduation application is usually due early in the semester.
    • December 2014 graduates: September 27
  • Oral exam form: You should also file an application for oral examination form at least 2 weeks before their dissertation defense. The two designated readers must read the dissertation and approve the form, as well as the doctoral committee advisor. The dissertation defense should also be scheduled before submitting the application.
    • December 2014 graduates: November 13
  • Dissertation defense: After submitting the oral exam form, you’ll receive final instructions and a checklist from graduate studies. All dissertation defenses should be completed at least 2 weeks before the end of the semester, including Finals Week.
    • December 2014 graduates: December 4

All necessary forms and deadlines are on the Graduate Studies homepage.
Exact deadlines will change from semester to semester.

Joint PhD programs with other Departments

  1. Statistics and Agronomy
  2. Statistics and Horticulture
  3. Statistics and Natural Resources
  4. Statistics and Economics

Course Requirements

All PhD students are required to take:
Prereqs: STAT 802, STAT 882, STAT 883, STAT 970 and take Statistics MS Comprehensive Exam prior to start of STAT 971.
Statistical modeling beyond the “general linear model” normally-distributed data, fixed-effects-only case. Focus on, but not limited to, the theory and practice of generalized and mixed linear models. Issues include translation of study design to plausible models, inference space, data and model scale, conditional vs. marginal models, correlated data, zero-inflated data, likelihood-based estimation and inference.
This course is a prerequisite for: STAT 950, STAT 971
Credit Hours: 3
Course Delivery: Classroom
Prereqs: STAT 883
This course requires command of material covered in MATH 325 or equivalent.
Construction of probability spaces, random variables and expectations, monotone and dominated convergence theorems, Fatou's lemma, modes of convergence, Kolmogorov law of large numbers, central limit theory, conditional probability given a sigma field.
This course is a prerequisite for: STAT 981, STAT 984
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs: STAT 883
Uniformly minimum variance unbiased estimators, decision-theoretic Bayes estimation, frequentist testing (likelihood ratio tests, Neyman-Pearson lemma, uniformly most powerful tests), Bayes testing and Bayes factors, nonparametric tests, multiple comparisons procedures.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs: STAT 823, STAT 883.
Model selection including sparsity methods and their oracle properties, information methods, cross-validation and stochastic search. Basic theory of kernel methods for regression.  Classification: linear and quadratic discriminants, Bayes classifier, nearest neighbor methods, kernel methods for classification. Introduction to neural networks and recursive partitioning. Model averaging methods and measures of complexity. Cluster analysis.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom

Each student must complete these courses with a grade of at least B in each. If a student earns a grade below B in any of these courses, his/her Supervisory Committee may either require the student to repeat the course or administer an extra written exam(s) in that area(s). Students must also take 12 additional hours of 900 level courses, excluding STAT 970, STAT 997, and STAT 999.

PhD Minor in Statistics

Students who wish to complete a PhD minor in Statistics must:

  1. Complete 16 credits of 800/900 level Statistics courses.
  2. Have a Statistics Faculty Member serve on their Supervisory Committee.
  3. Complete any additional requirements as determined by their Supervisory Committee.