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Ph.D. in Statistics

Our doctoral program in statistics gives future researchers preparation to teach and lead in academic and industry careers.

Program Description

Degree type.

approximately 5 years

The relatively new Ph.D. in Statistics strives to be an exemplar of graduate training in statistics. Students are exposed to cutting edge statistical methodology through the modern curriculum and have the opportunity to work with multiple faculty members to take a deeper dive into special topics, gain experience in working in interdisciplinary teams and learn research skills through flexible research electives. Graduates of our program are prepared to be leaders in statistics and machine learning in both academia and industry.

The Ph.D. in Statistics is expected to take approximately five years to complete, and students participate as full-time graduate students.  Some students are able to finish the program in four years, but all admitted students are guaranteed five years of financial support.  

Within our program, students learn from global leaders in statistics and data sciences and have:

20 credits of required courses in statistical theory and methods, computation, and applications

18 credits of research electives working with two or more faculty members, elective coursework (optional), and a guided reading course

Dissertation research

Coursework Timeline

Year 1: focus on core learning.

The first year consists of the core courses:

• SDS 384.2 Mathematical Statistics I
• SDS 383C Statistical Modeling I
• SDS 387 Linear Models
• SDS 384.11 Theoretical Statistics
• SDS 383D Statistical Modeling II
• SDS 386D Monte Carlo Methods

In addition to the core courses, students of the first year are expected to participate in SDS 190 Readings in Statistics. This class focuses on learning how to read scientific papers and how to grasp the main ideas, as well as on practicing presentations and getting familiar with important statistics literature.

At the end of the first year, students are expected to take a written preliminary exam. The examination has two purposes: to assess the student’s strengths and weaknesses and to determine whether the student should continue in the Ph.D. program. The exam covers the core material covered in the core courses and it consists of two parts: a 3-hour closed book in-class portion and a take-home applied statistics component. The in-class portion is scheduled at the end of the Spring Semester after final exams (usually late May). The take-home problem is distributed at the end of the in-class exam, with a due-time 24 hours later. 

Year 2: Transitioning from Student to Researcher

In the second year of the program, students take the following courses totaling 9 credit hours each semester:

• Required: SDS 190 Readings in Statistics (1 credit hour)
• Required: SDS 389/489 Research Elective* (3 or 4 credit hours) in which the student engages in independent research under the guidance of a member of the Statistics Graduate Studies Committee
• One or more elective courses selected from approved electives ; and/or
• One or more sections of SDS 289/389/489 Research Elective* (2 to 4 credit hours) in which the student engages in independent research with a member(s) of the Statistics Graduate Studies Committee OR guided readings/self-study in an area of statistics or machine learning. 
• Internship course (0 or 1 credit hour; for international students to obtain Curricular Practical Training; contact Graduate Coordinator for appropriate course options)
• GRS 097 Teaching Assistant Fundamentals or NSC 088L Introduction to Evidence-Based Teaching (0 credit hours; for TA and AI preparation)

* Research electives allow students to explore different advising possibilities by working for a semester with a particular professor. These projects can also serve as the beginning of a dissertation research path. No more than six credit hours of research electives can be taken with a single faculty member in a semester.

Year 3: Advance to Candidacy

Students are encouraged to attend conferences, give presentations, as well as to develop their dissertation research. At the end of the second year or during their third year, students are expected to present their plan of study for the dissertation in an Oral candidacy exam. During this exam, students should demonstrate their research proficiency to their Ph.D. committee members. Students who successfully complete the candidacy exam can apply for admission to candidacy for the Ph.D. once they have completed their required coursework and satisfied departmental requirements. The steps to advance to candidacy are:

• Discuss potential candidacy exam topics with advisor
• Propose Ph.D. committee: the proposed committee must follow the Graduate School and departmental regulations on committee membership for what will become the Ph.D. Dissertation Committee
•   Application for candidacy

Year 4+: Dissertation Completion and Defense

Students are encouraged to attend conferences, give presentations, as well as to develop their dissertation research. Moreover, they are expected to present part of their work in the framework of the department's Ph.D. poster session.

Students who are admitted to candidacy will be expected to complete and defend their Ph.D. thesis before their Ph.D. committee to be awarded the degree. The final examination, which is oral, is administered only after all coursework, research and dissertation requirements have been fulfilled. It is expected that students will be prepared to defend by the end of their fifth year in the doctoral program.

General Information and Expectations for All Ph.D. students

• 2023-24 Student Handbook
• Annual Review At the end of every spring semester, students in their second year and beyond are expected to fill out an annual review form distributed by the Graduate Program Administrator. 
• Seminar Series All students are expected to attend the SDS Seminar Series
• SDS 189R Course Description (when taken for internship)
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Attending Conferences 

Students are encouraged to attend conferences to share their work. All research-related travel while in student status require prior authorization.

• Request for Travel Authorization (both domestic and international travel)
• Request for Authorization for International Travel  

Cornell University does not offer a separate Masters of Science (MS) degree program in the field of Statistics. Applicants interested in obtaining a masters-level degree in statistics should consider applying to Cornell's MPS Program in Applied Statistics.

Choosing a Field of Study

There are many graduate fields of study at Cornell University. The best choice of graduate field in which to pursue a degree depends on your major interests. Statistics is a subject that lies at the interface of theory, applications, and computing. Statisticians must therefore possess a broad spectrum of skills, including expertise in statistical theory, study design, data analysis, probability, computing, and mathematics. Statisticians must also be expert communicators, with the ability to formulate complex research questions in appropriate statistical terms, explain statistical concepts and methods to their collaborators, and assist them in properly communicating their results. If the study of statistics is your major interest then you should seriously consider applying to the Field of Statistics.

There are also several related fields that may fit even better with your interests and career goals. For example, if you are mainly interested in mathematics and computation as they relate to modeling genetics and other biological processes (e.g, protein structure and function, computational neuroscience, biomechanics, population genetics, high throughput genetic scanning), you might consider the Field of Computational Biology . You may wish to consider applying to the Field of Electrical and Computer Engineering if you are interested in the applications of probability and statistics to signal processing, data compression, information theory, and image processing. Those with a background in the social sciences might wish to consider the Field of Industrial and Labor Relations with a major or minor in the subject of Economic and Social Statistics. Strong interest and training in mathematics or probability might lead you to choose the Field of Mathematics . Lastly, if you have a strong mathematics background and an interest in general problem-solving techniques (e.g., optimization and simulation) or applied stochastic processes (e.g., mathematical finance, queuing theory, traffic theory, and inventory theory) you should consider the Field of Operations Research .

Residency Requirements

Students admitted to PhD program must be "in residence" for at least four semesters, although it is generally expected that a PhD will require between 8 and 10 semesters to complete. The chair of your Special Committee awards one residence unit after the satisfactory completion of each semester of full-time study. Fractional units may be awarded for unsatisfactory progress.

Your Advisor and Special Committee

The Director of Graduate Studies is in charge of general issues pertaining to graduate students in the field of Statistics. Upon arrival, a temporary Special Committee is also declared for you, consisting of the Director of Graduate Studies (chair) and two other faculty members in the field of Statistics. This temporary committee shall remain in place until you form your own Special Committee for the purposes of writing your doctoral dissertation. The chair of your Special Committee serves as your primary academic advisor; however, you should always feel free to contact and/or chat with any of the graduate faculty in the field of Statistics.

The formation of a Special Committee for your dissertation research should serve your objective of writing the best possible dissertation. The Graduate School requires that this committee contain at least three members that simultaneously represent a certain combination of subjects and concentrations. The chair of the committee is your principal dissertation advisor and always represents a specified concentration within the subject & field of Statistics. The Graduate School additionally requires PhD students to have at least two minor subjects represented on your special committee. For students in the field of Statistics, these remaining two members must either represent (i) a second concentration within the subject of Statistics, and one external minor subject; or, (ii) two external minor subjects. Each minor advisor must agree to serve on your special committee; as a result, the identification of these minor members should occur at least 6 months prior to your A examination.

Some examples of external minors include Computational Biology, Demography, Computer Science, Economics, Epidemiology, Mathematics, Applied Mathematics and Operations Research. The declaration of an external minor entails selecting (i) a field other than Statistics in which to minor; (ii) a subject & concentration within the specified field; and, (iii) a minor advisor representing this field/subject/concentration that will work with you in setting the minor requirements. Typically, external minors involve gaining knowledge in 3-5 graduate courses in the specified field/subject, though expectations can vary by field and even by the choice of advisor. While any choice of external minor subject is technically acceptable, the requirement that the minor representative serve on your Special Committee strongly suggests that the ideal choice(s) should share some natural connection with your choice of dissertation topic.

The fields, subjects and concentrations represented on your committee must be officially recognized by the Graduate School ; the Degrees, Subjects & Concentrations tab listed under each field of study provides this information. Information on the concentrations available for committee members chosen to represent the subject of Statistics can be found on the Graduate School webpage . 

Statistics PhD Travel Support

The Department of Statistics and Data Science has established a fund for professional travel for graduate students. The intent of the Department is to encourage travel that enhances the Statistics community at Cornell by providing funding for graduate students in statistics that will be presenting at conferences. Please review the Graduate Student Travel Award Policy website for more information. 

Completion of the PhD Degree

In addition to the specified residency requirements, students must meet all program requirements as outlined in Program Course Requirements and Timetables and Evaluations and Examinations, as well as complete a doctoral dissertation approved by your Special Committee. The target time to PhD completion is between 4 and 5 years; the actual time to completion varies by student.

Students should consult both the Guide to Graduate Study and Code of Legislation of the Graduate Faculty (available at www.gradschool.cornell.edu ) for further information on all academic and procedural matters pertinent to pursuing a graduate degree at Cornell University.

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The department encourages research in both theoretical and applied statistics. Faculty members of the department have been leaders in research on a multitude of topics that include statistical inference, statistical computing and Monte-Carlo methods, analysis of missing data, causal inference, stochastic processes, multilevel models, experimental design, network models and the interface of statistics and the social, physical, and biological sciences. A unique feature of the department lies in the fact that apart from methodological research, all the faculty members are also heavily involved in applied research, developing novel methodology that can be applied to a wide array of fields like astrophysics, biology, chemistry, economics, engineering, public policy, sociology, education and many others.

Two carefully designed special courses offered to Ph.D. students form a unique feature of our program. Among these, Stat 303 equips students with the  basic skills necessary to teach statistics , as well as to be better overall statistics communicators. Stat 399 equips them with generic skills necessary for problem solving abilities.

Our Ph.D. students often receive substantial guidance from several faculty members, not just from their primary advisors, and in several settings. For example, every Ph.D. candidate who passes the qualifying exam gives a 30 minute presentation each semester (in Stat 300 ), in which the faculty ask questions and make comments. The Department recently introduced an award for Best Post-Qualifying Talk (up to two per semester), to further encourage and reward inspired research and presentations.

PhD Program Requirements

PhD Program Admissions Process

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PhD in Statistics

Program description.

The Ph.D. program in statistics prepares students for a career pursuing research in either academia or industry.  The program provides rigorous classroom training in the theory, methodology, and application of statistics, and provides the opportunity to work with faculty on advanced research topics over a wide range of theory and application areas. To enter, students need a bachelor’s degree in mathematics, statistics, or a closely related discipline. Students graduating with a PhD in Statistics are expected to:

• Demonstrate an understanding the core principles of Probability Theory, Estimation Theory, and Statistical Methods.
• Demonstrate the ability to conduct original research in statistics.
• Demonstrate the ability to present research-level statistics in a formal lecture

Requirements for the Ph.D. (Statistics Track)

Course Work A Ph.D. student in our department must complete sixteen courses for the Ph.D. At most, four of these courses may be transferred from another institution. If the Ph.D. student is admitted to the program at the post-Master’s level, then eight courses are usually required.

Qualifying Examinations First, all Ph.D. students in the statistics track must take the following two-semester sequences: MA779 and MA780 (Probability Theory I and II), MA781 (Estimation Theory) and MA782 (Hypothesis Testing), and MA750 and MA751 (Advanced Statistical Methods I and II). Then, to qualify a student to begin work on a PhD dissertation, they must pass two of the following three exams at the PhD level: probability, mathematical statistics, and applied statistics. The probability and mathematical statistics exams are offered every September and the applied statistics exam is offered every April.

• PhD Exam in Probability: This exam covers the material covered in MA779 and MA780 (Probability Theory I and II).
• PhD Exam in Mathematical Statistics: This exam covers material covered in MA781 (Estimation Theory) and MA782 (Hypothesis Testing).
• PhD Exam in Applied Statistics: This exam covers the same material as the M.A. Applied exam and is offered at the same time, except that in order to pass it at the PhD level a student must correctly solve all four problems.

Note: Students concentrating in probability may choose to do so either through the statistics track or through the mathematics track. If a student wishes to do so through the mathematics track, the course and exam requirements are different. Details are available here .

Dissertation The dissertation is the major requirement for a Ph.D. student. After the student has completed all course work, the Director of Graduate Studies, in consultation with the student, selects a three-member dissertation committee. One member of this committee is designated by the Director of Graduate Studies as the Major Advisor for the student. Once completed, the dissertation must be defended in an oral examination conducted by at least five members of the Department.

The Dissertation and Final Oral Examination follows the   GRS General Requirements for the Doctor of Philosophy Degree .

Satisfactory Progress Toward the Degree Upon entering the graduate program, each student should consult the Director of Graduate Studies (Prof. David Rohrlich) and the Associate Director of the Program in Statistics (Prof. Konstantinos Spiliopoulos). Initially, the Associate Director of the Program in Statistics will serve as the default advisor to the student. Eventually the student’s advisor will be determined in conjunction with their dissertation research. The Associate Director of the Program in Statistics, who will be able to guide the student through the course selection and possible directed study, should be consulted often, as should the Director of Graduate Studies. Indeed, the Department considers it important that each student progress in a timely manner toward the degree. Each M.A. student must have completed the examination by the end of their second year in the program, while a Ph.D. student must have completed the qualifying examination by the third year. Students entering the Ph.D. program with an M.A. degree must have completed the qualifying examination by October of the second year. Failure to meet these deadlines may jeopardize financial aid. Some flexibility in the deadlines is possible upon petition to the graduate committee in cases of inadequate preparation.

Students enrolled in the Graduate School of Arts & Sciences (GRS) are expected to adhere to a number of policies at the university, college, and departmental levels. View the policies on the Academic Bulletin and GRS website .

Residency Post-BA students must complete all of the requirements for a Ph.D. within seven years of enrolling in the program and post-MA students must complete all requirements within five years. This total time limit is set by the Graduate School. Students needing extra time must petition the Graduate School. Also, financial aid is not guaranteed after the student’s fifth year in the program.

Financial Aid

As with all Ph.D. students in the Department of Mathematics and Statistics, the main source of financial aid for graduate students studying statistics is a Teaching Fellowship. These awards carry a stipend as well as tuition remission for six courses per year. Teaching Fellows are required to assist a faculty member who is teaching a course, usually a large lecture section of an introductory statistics course. Generally, the Teaching Fellow is responsible for conducting a number of discussion sections consisting of approximately twenty-five students each, as well as for holding office hours and assisting with grading. The Teaching Fellowship usually entails about twenty hours of work per week. For that reason, Teaching Fellows enroll in at most three courses per semester. A Teaching Fellow Seminar is conducted to help new Teaching Fellows develop as instructors and to promote the continuing development of experienced Teaching Fellows.

Other sources of financial aid include University Fellowships and Research Assistantships. The University Fellowships are one-year awards for outstanding students and are service-free. They carry stipends plus full tuition remission. Students do not need to apply for these fellowships. Research Assistantships are linked to research done with individual faculty, and are paid for through those faculty members’ grants. As a result, except on rare occasions, Research Assistantships typically are awarded to students in their second year and beyond, after student and faculty have had sufficient time to determine mutuality of their research interests.

Regular reviews of the performance of Teaching Fellows and Research Assistants in their duties as well as their course work are conducted by members of the Department’s Graduate Committee.

Ph.D. Program Milestones

The department considers it essential that each student progress in a timely manner toward completion of the degree. The following are the deadlines for achieving the milestones described in the Degree Requirements and constitute the basis for evaluating satisfactory progress towards the Ph.D. These deadlines are not to be construed as expected times to complete the various milestones, but rather as upper bounds. In other words,   a student in good standing expecting to complete   the degree within the five years of guaranteed funding will meet these milestones by the much e arlier target dates indicated below.   Failure to achieve these milestones in a timely manner may affectfinancial aid.

• Target: April of Year 1
• Deadline: April of Year 2
• Target: Spring of Year 2 post-BA/Spring of Year 1 post-MA
• Deadline: End of Year 3 post-BA/Fall of Year 2 post-MA
• Target: Spring of Year 2
• Deadline: End of Year 3
• Target: Spring of Year 2 or Fall of Year 3 post-BA/October of Year 2 post-MA
• Deadline: End of Year 3 post-BA/October of Year 2 post-MA
• Target: end of Year 3
• Deadline: End of Year 4
• Target: End of Year 5
• Deadline: End of Year 6

If you have any questions regarding our PhD program in Statistics, please reach out to us at [email protected]

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PhD Program

Wharton’s PhD program in Statistics provides the foundational education that allows students to engage both cutting-edge theory and applied problems. These include problems from a wide variety of fields within Wharton, such as finance, marketing, and public policy, as well as fields across the rest of the University such as biostatistics within the Medical School and computer science within the Engineering School.

Major areas of departmental research include: analysis of observational studies; Bayesian inference, bioinformatics; decision theory; game theory; high dimensional inference; information theory; machine learning; model selection; nonparametric function estimation; and time series analysis.

Students typically have a strong undergraduate background in mathematics. Knowledge of linear algebra and advanced calculus is required, and experience with real analysis is helpful. Although some exposure to undergraduate probability and statistics is expected, skills in mathematics and computer science are more important. Graduates of the department typically take positions in academia, government, financial services, and bio-pharmaceutical industries.

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PhD Program information

The Statistics PhD program is rigorous, yet welcoming to students with interdisciplinary interests and different levels of preparation. Students in the PhD program take core courses on the theory and application of probability and statistics during their first year. The second year typically includes additional course work and a transition to research leading to a dissertation. PhD thesis topics are diverse and varied, reflecting the scope of faculty research interests. Many students are involved in interdisciplinary research. Students may also have the option to pursue a designated emphasis (DE) which is an interdisciplinary specialization:  Designated Emphasis in Computational and Genomic Biology ,  Designated Emphasis in Computational Precision Health ,  Designated Emphasis in Computational and Data Science and Engineering . The program requires four semesters of residence.

Normal progress entails:

Year 1 . Perform satisfactorily in preliminary coursework. In the summer, students are required to embark on a short-term research project, internship, graduate student instructorship, reading course, or on another research activity. Years 2-3 . Continue coursework. Find a thesis advisor and an area for the oral qualifying exam. Formally choose a chair for qualifying exam committee, who will also serve as faculty mentor separate from the thesis advisor.  Pass the oral qualifying exam and advance to candidacy by the end of Year 3. Present research at BSTARS each year. Years 4-5 . Finish the thesis and give a lecture based on it in a department seminar.

Program Requirements

• Qualifying Exam

Course work and evaluation

Preliminary stage: the first year.

Effective Fall 2019, students are expected to take four semester-long courses for a letter grade during their first year which should be selected from the core first-year PhD courses offered in the department: Probability (204/205A, 205B,), Theoretical Statistics (210A, 210B), and Applied Statistics (215A, 215B). These requirements can be altered by a member of the PhD Program Committee (in consultation with the faculty mentor and by submitting a graduate student petition ) in the following cases:

• Students primarily focused on probability will be allowed to substitute one semester of the four required semester-long courses with an appropriate course from outside the department.
• Students may request to postpone one semester of the core PhD courses and complete it in the second year, in which case they must take a relevant graduate course in their first year in its place. In all cases, students must complete the first year requirements in their second year as well as maintain the overall expectations of second year coursework, described below. Some examples in which such a request might be approved are described in the course guidance below.
• Students arriving with advanced standing, having completed equivalent coursework at another institution prior to joining the program, may be allowed to take other relevant graduate courses at UC Berkeley to satisfy some or all of the first year requirements

Requirements on course work beyond the first year

Students entering the program before 2022 are required to take five additional graduate courses beyond the four required in the first year, resulting in a total of nine graduate courses required for completion of their PhD. In their second year, students are required to take three graduate courses, at least two of them from the department offerings, and in their third year, they are required to take at least two graduate courses. Students are allowed to change the timing of these five courses with approval of their faculty mentor. Of the nine required graduate courses, students are required to take for credit a total of 24 semester hours of courses offered by the Statistics department numbered 204-272 inclusive. The Head Graduate Advisor (in consultation with the faculty mentor and after submission of a graduate student petition) may consent to substitute courses at a comparable level in other disciplines for some of these departmental graduate courses. In addition, the HGA may waive part of this unit requirement.

Starting with the cohort entering in the 2022-23 academic year , students are required to take at least three additional graduate courses beyond the four required in the first year, resulting in a total of seven graduate courses required for completion of their PhD. Of the seven required graduate courses, five of these courses must be from courses offered by the Statistics department and numbered 204-272, inclusive. With these reduced requirements, there is an expectation of very few waivers from the HGA. We emphasize that these are minimum requirements, and we expect that students will take additional classes of interest, for example on a S/U basis, to further their breadth of knowledge. 

For courses to count toward the coursework requirements students must receive at least a B+ in the course (courses taken S/U do not count, except for STAT 272 which is only offered S/U).  Courses that are research credits, directed study, reading groups, or departmental seminars do not satisfy coursework requirements (for courses offered by the Statistics department the course should be numbered 204-272 to satisfy the requirements). Upper-division undergraduate courses in other departments can be counted toward course requirements with the permission of the Head Graduate Advisor. This will normally only be approved if the courses provide necessary breadth in an application area relevant to the student’s thesis research.

First year course work: For the purposes of satisfactory progression in the first year, grades in the core PhD courses are evaluated as: A+: Excellent performance in PhD program A: Good performance in PhD program A-: Satisfactory performance B+: Performance marginal, needs improvement B: Unsatisfactory performance First year and beyond: At the end of each year, students must meet with his or her faculty mentor to review their progress and assess whether the student is meeting expected milestones. The result of this meeting should be the completion of the student’s annual review form, signed by the mentor ( available here ). If the student has a thesis advisor, the thesis advisor must also sign the annual review form.

Guidance on choosing course work

Choice of courses in the first year: Students enrolling in the fall of 2019 or later are required to take four semesters of the core PhD courses, at least three of which must be taken in their first year. Students have two options for how to schedule their four core courses:

• Option 1 -- Complete Four Core Courses in 1st year: In this option, students would take four core courses in the first year, usually finishing the complete sequence of two of the three sequences.  Students following this option who are primarily interested in statistics would normally take the 210A,B sequence (Theoretical Statistics) and then one of the 205A,B sequence (Probability) or the 215A,B sequence (Applied Statistics), based on their interests, though students are allowed to mix and match, where feasible. Students who opt for taking the full 210AB sequence in the first year should be aware that 210B requires some graduate-level probability concepts that are normally introduced in 205A (or 204).
• Option 2 -- Postponement of one semester of a core course to the second year: In this option, students would take three of the core courses in the first year plus another graduate course, and take the remaining core course in their second year. An example would be a student who wanted to take courses in each of the three sequences. Such a student could take the full year of one sequence and the first semester of another sequence in the first year, and the first semester of the last sequence in the second year (e.g. 210A, 215AB in the first year, and then 204 or 205A in the second year). This would also be a good option for students who would prefer to take 210A and 215A in their first semester but are concerned about their preparation for 210B in the spring semester.  Similarly, a student with strong interests in another discipline, might postpone one of the spring core PhD courses to the second year in order to take a course in that discipline in the first year.  Students who are less mathematically prepared might also be allowed to take the upper division (under-graduate) courses Math 104 and/or 105 in their first year in preparation for 205A and/or 210B in their second year. Students who wish to take this option should consult with their faculty mentor, and then must submit a graduate student petition to the PhD Committee to request permission for  postponement. Such postponement requests will be generally approved for only one course. At all times, students must take four approved graduate courses for a letter grade in their first year.

After the first year: Students with interests primarily in statistics are expected to take at least one semester of each of the core PhD sequences during their studies. Therefore at least one semester (if not both semesters) of the remaining core sequence would normally be completed during the second year. The remaining curriculum for the second and third years would be filled out with further graduate courses in Statistics and with courses from other departments. Students are expected to acquire some experience and proficiency in computing. Students are also expected to attend at least one departmental seminar per week. The precise program of study will be decided in consultation with the student’s faculty mentor.

Remark. Stat 204 is a graduate level probability course that is an alternative to 205AB series that covers probability concepts most commonly found in the applications of probability. It is not taught all years, but does fulfill the requirements of the first year core PhD courses. Students taking Stat 204, who wish to continue in Stat 205B, can do so (after obtaining the approval of the 205B instructor), by taking an intensive one month reading course over winter break.

Designated Emphasis: Students with a Designated Emphasis in Computational and Genomic Biology or Designated Emphasis in Computational and Data Science and Engineering should, like other statistics students, acquire a firm foundation in statistics and probability, with a program of study similar to those above. These programs have additional requirements as well. Interested students should consult with the graduate advisor of these programs. 

Starting in the Fall of 2019, PhD students are required in their first year to take four semesters of the core PhD courses. Students intending to specialize in Probability, however, have the option to substitute an advanced mathematics class for one of these four courses. Such students will thus be required to take Stat 205A/B in the first year,  at least one of Stat 210A/B or Stat 215A/B in the first year, in addition to an advanced mathematics course. This substitute course will be selected in consultation with their faculty mentor, with some possible courses suggested below. Students arriving with advanced coursework equivalent to that of 205AB can obtain permission to substitute in other advanced probability and mathematics coursework during their first year, and should consult with the PhD committee for such a waiver.

During their second and third years, students with a probability focus are expected to take advanced probability courses (e.g., Stat 206 and Stat 260) to fulfill the coursework requirements that follow the first year. Students are also expected to attend at least one departmental seminar per week, usually the probability seminar. If they are not sufficiently familiar with measure theory and functional analysis, then they should take one or both of Math 202A and Math 202B. Other recommended courses from the department of Mathematics or EECS include:

Math 204, 222 (ODE, PDE) Math 205 (Complex Analysis) Math 258 (Classical harmonic analysis) EE 229 (Information Theory and Coding) CS 271 (Randomness and computation)

The Qualifying Examination 

The oral qualifying examination is meant to determine whether the student is ready to enter the research phase of graduate studies. It consists of a 50-minute lecture by the student on a topic selected jointly by the student and the thesis advisor. The examination committee consists of at least four faculty members to be approved by the department.  At least two members of the committee must consist of faculty from the Statistics and must be members of the Academic Senate. The chair must be a member of the student’s degree-granting program.

Qualifying Exam Chair. For qualifying exam committees formed in the Fall of 2019 or later, the qualifying exam chair will also serve as the student’s departmental mentor, unless a student already has two thesis advisors. The student must select a qualifying exam chair and obtain their agreement to serve as their qualifying exam chair and faculty mentor. The student's prospective thesis advisor cannot chair the examination committee. Selection of the chair can be done well in advance of the qualifying exam and the rest of the qualifying committee, and because the qualifying exam chair also serves as the student’s departmental mentor (unless the student has co-advisors), the chair is expected to be selected by the beginning of the third year or at the beginning of the semester of the qualifying exam, whichever comes earlier. For more details regarding the selection of the Qualifying Exam Chair, see the "Mentoring" tab.  

Paperwork and Application. Students at the point of taking a qualifying exam are assumed to have already found a thesis advisor and to should have already submitted the internal departmental form to the Graduate Student Services Advisor ( found here ).  Selection of a qualifying exam chair requires that the faculty member formally agree by signing the internal department form ( found here ) and the student must submit this form to the Graduate Student Services Advisor.  In order to apply to take the exam, the student must submit the Application for the Qualifying Exam via CalCentral at least three weeks prior to the exam. If the student passes the exam, they can then officially advance to candidacy for the Ph.D. If the student fails the exam, the committee may vote to allow a second attempt. Regulations of the Graduate Division permit at most two attempts to pass the oral qualifying exam. After passing the exam, the student must submit the Application for Candidacy via CalCentral .

The Doctoral Thesis

The Ph.D. degree is granted upon completion of an original thesis acceptable to a committee of at least three faculty members. The majority or at least half of the committee must consist of faculty from Statistics and must be members of the Academic Senate. The thesis should be presented at an appropriate seminar in the department prior to filing with the Dean of the Graduate Division. See Alumni if you would like to view thesis titles of former PhD Students.

Graduate Division offers various resources, including a workshop, on how to write a thesis, from beginning to end. Requirements for the format of the thesis are rather strict. For workshop dates and guidelines for submitting a dissertation, visit the Graduate Division website.

Students who have advanced from candidacy (i.e. have taken their qualifying exam and submitted the advancement to candidacy application) must have a joint meeting with their QE chair and their PhD advisor to discuss their thesis progression; if students are co-advised, this should be a joint meeting with their co-advisors. This annual review is required by Graduate Division.  For more information regarding this requirement, please see  https://grad.berkeley.edu/ policy/degrees-policy/#f35- annual-review-of-doctoral- candidates .

Teaching Requirement

For students enrolled in the graduate program before Fall 2016, students are required to serve as a Graduate Student Instructor (GSI) for a minimum of 20 hours (equivalent to a 50% GSI appointment) during a regular academic semester by the end of their third year in the program.

Effective with the Fall 2016 entering class, students are required to serve as a GSI for a minimum of two 50% GSI appointment during the regular academic semesters prior to graduation (20 hours a week is equivalent to a 50% GSI appointment for a semester) for Statistics courses numbered 150 and above. Exceptions to this policy are routinely made by the department.

Each spring, the department hosts an annual conference called BSTARS . Both students and industry alliance partners present research in the form of posters and lightning talks. All students in their second year and beyond are required to present a poster at BSTARS each year. This requirement is intended to acclimate students to presenting their research and allow the department generally to see the fruits of their research. It is also an opportunity for less advanced students to see examples of research of more senior students. However, any students who do not yet have research to present can be exempted at the request of their thesis advisor (or their faculty mentors if an advisor has not yet been determined).

Mentoring for PhD Students

Initial Mentoring: PhD students will be assigned a faculty mentor in the summer before their first year. This faculty mentor at this stage is not expected to be the student’s PhD advisor nor even have research interests that closely align with the student. The job of this faculty mentor is primarily to advise the student on how to find a thesis advisor and in selecting appropriate courses, as well as other degree-related topics such as applying for fellowships.  Students should meet with their faculty mentors twice a semester. This faculty member will be the designated faculty mentor for the student during roughly their first two years, at which point students will find a qualifying exam chair who will take over the role of mentoring the student.

Research-focused mentoring : Once students have found a thesis advisor, that person will naturally be the faculty member most directly overseeing the student’s progression. However, students will also choose an additional faculty member to serve as a the chair of their qualifying exam and who will also serve as a faculty mentor for the student and as a member of his/her thesis committee. (For students who have two thesis advisors, however, there is not an additional faculty mentor, and the quals chair does NOT serve as the faculty mentor).

The student will be responsible for identifying and asking a faculty member to be the chair of his/her quals committee. Students should determine their qualifying exam chair either at the beginning of the semester of the qualifying exam or in the fall semester of the third year, whichever is earlier. Students are expected to have narrowed in on a thesis advisor and research topic by the fall semester of their third year (and may have already taken qualifying exams), but in the case where this has not happened, such students should find a quals chair as soon as feasible afterward to serve as faculty mentor.

Students are required to meet with their QE chair once a semester during the academic year. In the fall, this meeting will generally be just a meeting with the student and the QE chair, but in the spring it must be a joint meeting with the student, the QE chair, and the PhD advisor. If students are co-advised, this should be a joint meeting with their co-advisors.

If there is a need for a substitute faculty mentor (e.g. existing faculty mentor is on sabbatical or there has been a significant shift in research direction), the student should bring this to the attention of the PhD Committee for assistance.

PhD Student Forms:

Important milestones: .

Each of these milestones is not complete until you have filled out the requisite form and submitted it to the GSAO. If you are not meeting these milestones by the below deadline, you need to meet with the Head Graduate Advisor to ask for an extension. Otherwise, you will be in danger of not being in good academic standing and being ineligible for continued funding (including GSI or GSR appointments, and many fellowships). 

†Students who are considering a co-advisor, should have at least one advisor formally identified by the end of the second year; the co-advisor should be identified by the end of the fall semester of the 3rd year in lieu of finding a Research Mentor/QE Chair.

Expected Progress Reviews: 

* These meetings do not need to be held in the semester that you take your Qualifying Exam, since the relevant people should be members of your exam committee and will discuss your research progress during your qualifying exam

** If you are being co-advised by someone who is not your primary advisor because your primary advisor cannot be your sole advisor, you should be meeting with that person like a research mentor, if not more frequently, to keep them apprised of your progress. However, if both of your co-advisors are leading your research (perhaps independently) and meeting with you frequently throughout the semester, you do not need to give a fall research progress report.

Department of Statistics and Data Science

Ph.d. program.

Fields of study include the main areas of statistical theory (with emphasis on foundations, Bayes theory, decision theory, nonparametric statistics), probability theory (stochastic processes, asymptotics, weak convergence), information theory, bioinformatics and genetics, classification, data mining and machine learning, neural nets, network science, optimization, statistical computing, and graphical models and methods.

With this background, graduates of the program have found excellent positions in universities, industry, and government. See the list of alumni for examples.

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Statistics and Data Science

Wharton’s phd program in statistics and data science provides the foundational education that allows students to engage both cutting-edge theory and applied problems. these include theoretical research in mathematical statistics as well as interdisciplinary research in the social sciences, biology and computer science..

Wharton’s PhD program in Statistics and Data Science provides the foundational education that allows students to engage both cutting-edge theory and applied problems. These include problems from a wide variety of fields within Wharton, such as finance, marketing, and public policy, as well as fields across the rest of the University such as biostatistics within the Medical School and computer science within the Engineering School.

Major areas of departmental research include:

• analysis of observational studies;
• Bayesian inference, bioinformatics;
• decision theory;
• game theory;
• high dimensional inference;
• information theory;
• machine learning;
• model selection;
• nonparametric function estimation; and
• time series analysis.

Students typically have a strong undergraduate background in mathematics. Knowledge of linear algebra and advanced calculus is required, and experience with real analysis is helpful. Although some exposure to undergraduate probability and statistics is expected, skills in mathematics and computer science are more important. Graduates of the department typically take positions in academia, government, financial services, and bio-pharmaceutical industries.

For information on courses and sample plan of study, please visit the University Graduate Catalog .

Get the Details.

Visit the Statistics and Data Science website for details on program requirements and courses. Read faculty and student research and bios to see what you can do with a Statistics PhD.

Statistics and Data Science Doctoral Coordinator 

Dr. Bhaswar Bhattacharya Associate Professor of Statistics and Data Science Associate Professor of Mathematics (secondary appointment) Email: [email protected] Phone: 215-573-0535

PhD Program

Advanced undergraduate or masters level work in mathematics and statistics will provide a good background for the doctoral program. Quantitatively oriented students with degrees in other scientific fields are also encouraged to apply for admission. In particular, the department has expanded its research and educational activities towards computational biology, mathematical finance and information science. The doctoral program normally takes four to five years to complete.

Doctoral Program in Statistics

Statistics phd minor.

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PhD in Statistics

The STEM-designated PhD in Statistics program provides advanced training in topics including probability, linear models, time series analysis, Bayesian statistics, inference, reliability, statistics in law and regulatory policy and much more.

Nearly all GW statistics PhD graduates have secured job placements in the statistics or data science industry, with employers  including Amazon, Facebook and Capital One. During the program, PhD students work closely with faculty on original research in their area of interest. 

The degree provides training in theory and applications and is suitable for both full-time and part-time students. Most graduate courses are offered in the early evening to accommodate student schedules. 

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Application Requirements

Prospective PhD students typically have earned a master’s degree in statistics or a related discipline. Students need a strong background in mathematics, including courses in advanced calculus, linear algebra and mathematical statistics.

Complete Application Requirements

"GW encouraged me to tap into expertise from within as well as outside the university while researching my dissertation topic. I learned about the value of collaboration throughout my doctoral studies. Collaboration is so important in science, and it’s been instrumental in our success at Emmes."

Anne Lindblad PhD ’90 President, The Emmes Company

Students in their first semester of the PhD in Statistics program must meet with the program director  prior to signing up for classes. Students should continue to seek advice from the advisor throughout the program, particularly when determining whether any previous coursework can be applied toward their degree.

General Examinations

The general examination consists of two parts: a qualifying examination and an examination to determine the student's readiness to carry out the proposed dissertation research.

Each PhD candidate is required to take and pass the PhD qualifying exam. The written exam is given at the beginning of the fall semester each year. It consists of two papers:

• Inference: STAT 6202 and 8263
• Probability: STAT 6201 and 8257

The written exam is required for the first attempt. If a student cannot pass it, then there are two options for the second attempt.

• Option #1 for the second attempt : after approximately a year, the student will retake the written exam (see above for exam description).
• Option #2 for the second attempt : within approximately half a year, based on the scope of the written exam (see above for exam description), the student must demonstrate satisfactory improvements through (open-book, take-home) problem solving and an oral exam (with questions and answers).

No more than two attempts are permitted.

After passing the qualifying examination, the candidate should select a dissertation advisor. In consultation with the advisor, the candidate should pass a readiness examination, usually consisting of a research proposal and an oral examination. A committee of at least two professors should administer the readiness examination.

Dissertation

Students are required to complete a written dissertation that should be defended before an examination committee of at least four examiners. The dissertation should contain original scholarly research and must comply with all other GW rules and regulations. For more guidance on dissertation process, review the CCAS PhD Student Handbook . For formatting and submission guidelines, visit the Electronic Theses and Dissertations Submission website .

Past Theses

Course Requirements 

The program requires 72 credit hours, of which at least 48 must be from coursework and at least 12 must be from dissertation research. Up to 24 credit hours may be transferred from a prior master’s degree (contrary to general GW doctoral program requirements , which allow up to 30 transfer credit hours).

Statistics & Data Science

Dietrich college of humanities and social sciences, ph.d. programs, our ph.d. programs enable students to pursue a wide range of research opportunities, including constructing and implementing advanced methods of data analysis to address crucial cross-disciplinary questions, along with developing the fundamental theory that supports these methods..

Unique opportunities for our Ph.D. students include:

• We host four cross-disciplinary joint Ph.D. programs for students who want to specialize in machine learning , public policy , neuroscience , and the link between engineering and policy .
• Our faculty have deep involvement in a range of important, data-rich scientific collaborations, including in the areas of genetics, neuroscience, astronomy, and the social sciences. This allows students to have easy access to both the crucial questions in these fields, and to the data that can provide the answers.
• Students begin work on their Advanced Data Analysis Project in the second semester. This year-long, faculty/student collaboration, distinct from the thesis, provides an immediate intensive research experience.
• Carnegie Mellon is home to the first Machine Learning Department . Many of our faculty maintain joint appointments with this Department and they (and our students) have strong connections to this exciting and growing area of research.

The programs leading to the degree of   Doctor of Philosophy in Statistics   seek to strike a balance between theoretical and applied statistics. The Ph.D. program prepares students for university teaching and research careers, and for industrial and governmental positions involving research in new statistical methods. Four to five years are usually needed to complete all requirements for the Ph.D. degree.

These pages present the requirements for each of our Ph.D. programs.

The page   "Core Ph.D. Requirements"   lays out the requirements for all Ph.D. students, while each of the four joint programs are described under the Joint Ph.D. Degrees pages. Our Ph.D. students can also earn a   Master of Science in Statistics   as an intermediate step towards their ultimate goal.

Joint Ph.D. Programs

Statistics/machine learning, statistics/public policy, statistics/engineering and public policy, statistics/neural computation  .

Department of Statistics

Last update: 11/10/23

PhD Degree in Statistics

The Department of Statistics offers an exciting and recently revamped PhD program that involves students in cutting-edge interdisciplinary research in a wide variety of fields. Statistics has become a core component of research in the biological, physical, and social sciences, as well as in traditional computer science domains such as artificial intelligence and machine learning. The massive increase in the data acquired, through scientific measurement on one hand and through web-based collection on the other, makes the development of statistical analysis and prediction methodologies more relevant than ever.

Our graduate program prepares students to address these issues through rigorous training in scientific computation, and in the theory, methodology, and applications of statistics. The course work includes four core sequences:

• Probability (STAT 30400, 38100, 38300)
• Mathematical statistics (STAT 30400, 30100, 30210)
• Applied statistics (STAT 34300, 34700, 34800)
• Computational mathematics and machine learning (STAT 30900, 31015/31020, 37710).

All students must take the Applied Statistics and Theoretical Statistics sequence. In addition it is highly recommended that students take a third core sequence based on their interests and in consultation with the Department Graduate Advisor (DGA). At the start of their second year, the students take two preliminary examinations. All students must take the Applied Statistics Prelim. For the second the students can choose to take either the Theoretical Statistics or the Probability prelim. Students planning to take the Probability prelim should take the Probability sequence as their third sequence.

Incoming first-year students have the option of taking any or all of these exams; if an incoming student passes one or more of these, then he/she will be excused from the requirement of taking the first-year courses in that subject. During the second and subsequent years, students can take more advanced courses, and perform research, with world-class faculty in a wide variety of research areas .

In recent years, a large majority of our students complete the PhD within four or five years of entering the program. Students who have significant graduate training before entering the program can (and do) obtain their doctor's degree in three years.

Most students receiving a doctorate proceed to faculty or postdoctoral appointments in research universities. A substantial number take positions in government or industry, such as in research groups in the government labs, in communications, in commercial pharmaceutical companies, and in banking/financial institutions. The department has an excellent track record in placing new PhDs.

Prerequisites for the Program

A student applying to the PhD program normally should have taken courses in advanced calculus, linear algebra, probability, and statistics. Additional courses in mathematics, especially a course in real analysis, will be helpful. Some facility with computer programming is expected. Students without background in all of these areas, however, should not be discouraged from applying, especially if they have a substantial background, through study or experience, in some area of science or other discipline involving quantitative reasoning and empirical investigation. Statistics is an empirical and interdisciplinary field, and a strong background in some area of potential application of statistics is a considerable asset. Indeed, a student's background in mathematics and in science or another quantitative discipline is more important than his or her background in statistics.

To obtain more information about applying, see the Guide For Applicants .

Students with questions may contact Yali Amit for PhD Studies, Mei Wang for Masters Studies, and Keisha Prowoznik for all other questions, Bahareh Lampert (Dean of Students in the Physical Sciences Division), or Amanda Young (Associate Director, Graduate Student Affairs) in UChicagoGRAD.

Handbook for PhD Students in Statistics

Information for first and second year phd students in statistics.

• Graduate Studies

Ph.D. Program

The PhD program prepares students for research careers in theory and application of probability and statistics in academic and non-academic (e.g., industry, government) settings.  Students might elect to pursue either the general Statistics track of the program (the default), or one of the four specialized tracks that take advantage of UW’s interdisciplinary environment: Statistical Genetics (StatGen), Statistics in the Social Sciences (CSSS), Machine Learning and Big Data (MLBD), and Advanced Data Science (ADS). 

Admission Requirements

For application requirements and procedures, please see the graduate programs applications page .

Recommended Preparation

The Department of Statistics at the University of Washington is committed to providing a world-class education in statistics. As such, having some mathematical background is necessary to complete our core courses. This background includes linear algebra at the level of UW’s MATH 318 or 340, advanced calculus at the level of MATH 327 and 328, and introductory probability at the level of MATH 394 and 395. Real analysis at the level of UW’s MATH 424, 425, and 426 is also helpful, though not required. Descriptions of these courses can be found in the UW Course Catalog . We also recognize that some exceptional candidates will lack the needed mathematical background but succeed in our program. Admission for such applicants will involve a collaborative curriculum design process with the Graduate Program Coordinator to allow them to make up the necessary courses. 

While not a requirement, prior background in computing and data analysis is advantageous for admission to our program. In particular, programming experience at the level of UW’s CSE 142 is expected.  Additionally, our coursework assumes familiarity with a high-level programming language such as R or Python. 

Graduation Requirements 

This is a summary of the department-specific graduation requirements. For additional details on the department-specific requirements, please consult the  Ph.D. Student Handbook .  For previous versions of the Handbook, please contact the Graduate Student Advisor .  In addition, please see also the University-wide requirements at  Instructions, Policies & Procedures for Graduate Students  and  UW Doctoral Degrees .  

General Statistics Track

• Core courses: Advanced statistical theory (STAT 581, STAT 582 and STAT 583), statistical methodology (STAT 570 and STAT 571), statistical computing (STAT 534), and measure theory (either STAT 559 or MATH 574-575-576).  
• Elective courses: A minimum of four approved 500-level classes that form a coherent set, as approved in writing by the Graduate Program Coordinator.  A list of elective courses that have already been pre-approved or pre-denied can be found here .
• M.S. Theory Exam: The syllabus of the exam is available here .
• Research Prelim Exam. Requires enrollment in STAT 572. 
• Consulting.  Requires enrollment in STAT 599. 
• Applied Data Analysis Project.  Requires enrollment in 3 credits of STAT 597. 
• Statistics seminar participation: Students must attend the Statistics Department seminar and enroll in STAT 590 for at least 8 quarters. 
• Teaching requirement: All Ph.D. students must satisfactorily serve as a Teaching Assistant for at least one quarter. 
• General Exam. 
• Dissertation Credits.  A minimum of 27 credits of STAT 800, spread over at least three quarters. 
• Passage of the Dissertation Defense. 

Statistical Genetics (StatGen) Track

Students pursuing the Statistical Genetics (StatGen) Ph.D. track are required to take BIOST/STAT 550 and BIOST/STAT 551, GENOME 562 and GENOME 540 or GENOME 541. These courses may be counted as the four required Ph.D.-level electives. Additionally, students are expected to participate in the Statistical Genetics Seminar (BIOST581) in addition to participating in the statistics seminar (STAT 590). Finally, students in the Statistics Statistical Genetics Ph.D. pathway may take STAT 516-517 instead of STAT 570-571 for their Statistical Methodology core requirement. This is a transcriptable program option, i.e., the fact that the student completed the requirements will be noted in their transcript.

Statistics in the Social Sciences (CSSS) Track

Students in the Statistics in the Social Sciences (CSSS) Ph.D. track  are required to take four numerically graded 500-level courses, including at least two CSSS courses or STAT courses cross-listed with CSSS, and at most two discipline-specific social science courses that together form a coherent program of study. Additionally, students must complete at least three quarters of participation (one credit per quarter) in the CS&SS seminar (CSSS 590). This is not a transcriptable option, i.e., the fact that the student completed the requirements will not be noted in their transcript.

Machine Learning and Big Data Track

Students in the Machine Learning and Big Data (MLBD) Ph.D. track are required to take the following courses: one foundational machine learning course (STAT 535), one advanced machine learning course (either STAT 538 or STAT 548 / CSE 547), one breadth course (either on databases, CSE 544, or data visualization, CSE 512), and one additional elective course (STAT 538, STAT 548, CSE 515, CSE 512, CSE 544 or EE 578). At most two of these four courses may be counted as part of the four required PhD-level electives. Students pursuing this track are not required to take STAT 583 and can use STAT 571 to satisfy the Applied Data Analysis Project requirement. This is not a transcriptable option, i.e., the fact that the student completed the requirements will not be noted in their transcript. 

Advanced Data Science (ADS) Track

Students in the Advanced Data Science (ADS) Ph.D. track are required to take the same coursework as students in the Machine Learning and Big Data track. They are also not required to take STAT 583 and can use STAT 571 to satisfy the Applied Data Analysis Project requirement. The only difference in terms of requirements between the MLBD and the ADS tracks is that students in the ADS track must also register for at least 4 quarters of the weekly eScience Community Seminar (CHEM E 599). Also, unlike the MLBD track, the ADS is a transcriptable program option, i.e., the fact that the student completed the requirements will be noted in their transcript. 

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PhD in Statistics

Phd in statistics program.

The PhD in Statistics prepares students professional leadership in statistical research, teaching and collaboration as faculty at colleges and universities and as researchers at government institutions or in the private sector.

Coursework Requirements

MS in Statistics

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PhD Student Handbook

Fall 2024 Semester PhD Courses

For the most updated information on Statistics PhD courses, please go to Vergil . 

Spring 2024 Semester PhD Courses

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Statistics (ms, phd).

The Department of Statistics offers programs leading to Master of Science (M.S.) in Statistics and Doctor of Philosophy (Ph.D.) degrees. (The Department also offers a Professional M.S. in Biostatistics). All programs include training in statistical application and theory, and give students sufficient flexibility to pursue their special interests as well as time to take courses in other departments at the University of Connecticut.

Master of Science

The M.S. in statistics program normally requires 31 credits. While it is possible to complete the M.S. degree within a year, most students will need three to four semesters. The core courses of the program cover mathematical statistics, linear models, design of experiments, and applied statistics. The program also requires one to two courses in areas of application. The plan of study may be formulated with related work in almost any area, e.g., Biology, Economics, Nutrition, and Psychology. Students are encouraged to participate in statistical consulting projects done by members of the Department. To make acceptable progress through the program, three semesters of calculus and a semester of linear algebra in college are necessary. A background in statistics will be helpful, but is not assumed.

Master of Science Required Courses

The final requirement is passing the Master’s Examination which is a written test on basic understanding of course materials. There is no thesis requirement. In order to be considered for a possible switch to the Ph.D. program or for financial support, a M.S. in Statistics student must first clear the Ph.D. Qualifying Examination.

Doctor of Philosophy

The Ph.D. program emphasizes development of the ability to generate novel results in statistical methods, statistical theory, or probability. Individuals with a Bachelor’s degree in any major, with a background in mathematics and statistics are encouraged to apply. The course work typically consists of at least 16 graduate level courses that cover a wide range of topics, including mathematical statistics, linear models, statistical inference, applied statistics, real analysis, and probability. After completing the necessary course work and a sequence of examinations, a Ph.D. candidate must complete a dissertation that makes an original contribution to the field of statistics or probability. The dissertation may be predominantly development of novel statistical methodology for an area of application.

Doctor of Philosophy Requirements

For students entering the program after a Bachelor’s Degree, typically 16 to 18 courses are required. An individual plan of study is developed by the student and their Advisory Committee. Knowledge of a sequence of core courses is required for all Ph.D. students. These courses are:

Additional credits can be earned from the list of elective courses. In general, Ph.D. students are required to elect one to two courses from other departments. However, it is sufficient to take one graduate level course from the Department of Mathematics. Each elected course must be approved by the major advisor of a student. Under certain circumstances, the major advisor can exempt the student from the above requirement, if the student has had internships or Research Assistantships in interdisciplinary areas. The Department has no requirement on foreign languages. The first formal requirement for the Ph.D. degree is passing the Ph.D. Qualifying Examination which is a written test on certain basic courses. The second requirement is passing the General Examination that consists of an oral test on aspects of Applied Statistics, Linear Models, Probability Theory and Statistics and a presentation of a thesis research proposal. The preparation of a dissertation then follows which must present an original contribution to the general area of Statistics and/or Probability. The final requirement is a defense of the Ph.D. dissertation before an audience of interested members of the Department. The Department expects every Ph.D. student to strive to finish their study within four years. For students arriving without a M.S. degree in Mathematics or Statistics, the Department may provide up to five years of financial support. For those arriving with such a degree, the Department may provide up to four years of financial support.

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Fully Funded PhD Programs in Statistics

Last updated May 14, 2022

As part of our series  How to Fully Fund Your PhD , here is a list of universities that fully fund PhD students in Statistics. PhD in Statistics can lead to a variety of careers in consulting, academia, a variety of industries, and more.

“Full funding” is a financial aid package for full-time students that includes full tuition remission as well as an annual stipend or salary during the entire program, which is usually 3-6 years. Funding usually comes with the expectation that students will teach or complete research in their field of study. Not all universities fully fund their doctoral students, which is why researching the financial aid offerings of many different programs, including small and lesser-known schools both in the U.S. and abroad, is essential.

The  ProFellow database  for graduate and doctoral study also spotlights external funding opportunities for graduate school, including dissertation research, fieldwork, language study, and summer work experiences.

Would you like to receive the full list of more than 1000+ fully funded programs in 60 disciplines? Download the FREE Directory of Fully Funded Graduate Programs and Full Funding Awards !

Columbia University, PhD in Statistics

(New York, NY): All students in the Ph.D. program receive, for up to five years, a funding package consisting of tuition, fees, and a stipend. These fellowships are awarded in recognition of academic achievement and in expectation of scholarly success; they are contingent upon the student remaining in good academic standing. Summer support, while not guaranteed, is generally provided.

Ohio State University, PhD in Statistics

(Columbus, OH): Students who are offered the funding at the time of admission either via a Fellowship or Graduate Teaching Associateship are typically guaranteed funding through the duration of their program (up to five years if needed for a Ph.D. student or two years for a master’s student) provided that the student continues to make appropriate progress toward the degree and carries out assigned duties satisfactorily.

Stanford University, PhD in Statistics

(Stanford, CA): Students accepted to the Ph.D. program are offered financial support. All tuition expenses are paid and there is a fixed monthly stipend determined to be sufficient to pay living expenses. Financial support can be continued for five years, department resources permitting, for students in good standing.

University of Chicago, PhD in Statistics

(Chicago, IL): In recent years our department has been able to provide full support (tuition, most fees, health insurance, and a stipend) for most of its Ph.D. students, and we expect to do so for the foreseeable future. Ordinarily, students are supported for at least four years. Support is not tied to working with a particular faculty member. At present, most fifth-year students receive full support, and most Ph.D. students receive summer support.

University of Nevada, Reno, PhD in Statistics and Data Science

(Reno, NV): All students accepted to the Statistics and Data Science Ph.D. program receive an annual stipend of $17,000, a tuition waiver, and a subsidized medical plan. Students may also pursue departmental and University-wide scholarships.

University of Texas at Austin, PhD in Statistics

(Austin, TX): It is our intention that each PhD Statistics student will be fully financially supported for four academic years, the duration of his/her program of study. There are in general three types of support: academic employment, graduate fellowships, and grants.

University of Texas at San Antonio, PhD in Applied Statistics

(San Antonio, TX): Full-time students admitted to the Ph.D. program are usually awarded fellowships that include a waiver of tuition, a stipend to help cover living expenses, and some health care benefits. The stipend is likely to vary but could be in an amount up to $25,000 annually.

Duke University, PhD in Statistical Science

(Durham, NC): About half of the financial aid specified in your acceptance letter will be given to you without you having to do anything except maintain good academic standing. The other half is contingent upon you being a teaching assistant (TA) or research assistant (RA) within the department.

Need some tips for the application process? See my article  How To Get Into a Fully Funded PhD Program: Contacting Potential PhD Advisors .

Also, sign up to discover and bookmark more than 1800 professional and academic fellowships in the  ProFellow database .

© Victoria Johnson 2020, all rights reserved.

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About the PhD in Biostatistics Program

The PhD in Biostatistics provides training in the theory of probability and statistics in biostatistical methodology. The program is unique in its emphasis on the foundations of statistical reasoning and data science. Students complete rigorous training in real analysis-based probability and statistics, equivalent to what is provided in most departments of mathematical statistics and in advanced data science.

PhD candidates are required to pass a comprehensive written examination covering coursework completed at the end of their first year. Research leading to a thesis may involve development of new theory and methodology, or it may be concerned with applications of statistics and probability to problems in public health, medicine or biology.

Application Fee Waivers: We are able to offer a limited number of application fee waivers. Learn about the eligibility criteria and how to apply for a waiver .

PhD in Biostatistics Program Highlights

Conduct and publish original research.

on the theory and methodology of biostatistics

Apply innovative theory and methods

to the solution of public health problems

Serve as an expert biostatistician

on collaborative teams of investigators addressing key public health questions

Teach biostatistics effectively

to health professionals and scientists as well as to graduate students in biostatistics

What Can You Do With a PhD In Biostatistics?

Visit the Graduate Employment Outcomes Dashboard to learn about Bloomberg School graduates' employment status, sector, and salaries. We have over 750 global alumni working in academia, government, and industry.

Sample Careers and Next Steps

• Tenure Track Faculty (e.g. Assistant Professor)
• Postdoctoral Fellow
• Data Scientist
• Statistician
• Biostatistician
• Machine Learning Engineer
• Mathematical Statistician
• Principal Investigator

Curriculum for the PhD in Biostatistics

Browse an overview of the requirements for this PhD program in the JHU  Academic Catalogue  and explore all course offerings in the Bloomberg School  Course Directory .

Admissions Requirements

For general admissions requirements, please visit the How to Apply page. This specific program also requires:

Prior Coursework

Calculus and linear algebra; accepted applicants are also strongly encouraged to take real analysis before matriculating

Standardized Test Scores

Standardized test scores are  not required and not reviewed  for this program. If you have taken a standardized test such as the GRE, GMAT, or MCAT and want to submit your scores, please note that they will not be used as a metric during the application review.  Applications will be reviewed holistically based on all required application components.

Vivien Thomas Scholars Initiative

The  Vivien Thomas Scholars Initiative (VTSI)  is an endowed fellowship program at Johns Hopkins for PhD students in STEM fields. It provides full tuition, stipend, and benefits while also providing targeted mentoring, networking, community, and professional development opportunities. Students who have attended a historically Black college and university (HBCU) or other minority serving institution (MSI) for undergraduate study are eligible to apply. To be considered for the VTSI, you will need to submit a SOPHAS application ,VTSI supplementary materials, and all supporting documents (letters, transcripts, and test scores) by December 1, 2024. VTSI applicants are eligible for an  application fee waiver , but the fee waiver must be requested by November 15, 2024 and prior to submission of the SOPHAS application.

Per the Collective Bargaining Agreement (CBA) with the JHU PhD Union, the minimum guaranteed 2025-2026 academic year stipend is $50,000 for all PhD students with a 4% increase the following year. Tuition, fees, and medical benefits are provided, including health insurance premiums for PhD student’s children and spouses of international students, depending on visa type. The minimum stipend and tuition coverage is guaranteed for at least the first four years of a BSPH PhD program; specific amounts and the number of years supported, as well as work expectations related to that stipend will vary across departments and funding source. Please refer to the CBA to review specific benefits, compensation, and other terms.

Need-Based Relocation Grants

Students who  are admitted to PhD programs at JHU starting in Fall 2023 or beyond can apply to receive a need-based grant to offset the costs of relocating to be able to attend JHU.   These grants provide funding to a portion of incoming students who, without this money, may otherwise not be able to afford to relocate to JHU for their PhD program. This is not a merit-based grant. Applications will be evaluated solely based on financial need.  View more information about the need-based relocation grants for PhD students .

Questions about the program? We're happy to help. 

Academic Administrator Mary Joy Argo 410-614-4454 [email protected]

• All previous cycle years

The SED is an annual census of research doctorate recipients from U.S. academic institutions that collects information on educational history, demographic characteristics, graduate funding source and educational debts, and postgraduation plans.

Survey Info

• tag for use when URL is provided --> Methodology
• tag for use when URL is provided --> Data
• tag for use when URL is provided --> Analysis

The Survey of Earned Doctorates is an annual census conducted since 1957 of all individuals receiving a research doctorate from an accredited U.S. institution in a given academic year. The SED is sponsored by the National Center for Science and Engineering Statistics (NCSES) within the National Science Foundation (NSF) and by three other federal agencies: the National Institutes of Health, Department of Education, and National Endowment for the Humanities. The SED collects information on the doctoral recipient’s educational history, demographic characteristics, and postgraduation plans. Results are used to assess characteristics of the doctoral population and trends in doctoral education and degrees.

Areas of Interest

• STEM Education
• Science and Engineering Workforce

Survey Administration

The 2022 survey was conducted by RTI International under contract to NCSES.

Survey Details

Featured Survey Analysis

Doctorate Recipients from U.S. Universities: 2022

SED Overview

Data highlights, the number of research doctorates conferred by u.s. institutions, which began a sharp 15-month decline in spring 2020 due to the covid-19 pandemic, rebounded in 2022 with the highest number of research doctorates awarded in any academic year to date.

Over the past 20 years, most of the growth in the number of doctorates earned by both men and women has been in science and engineering (S&E) fields 

Methodology

Survey description, technical notes, technical tables, questionnaires, view archived questionnaires, featured analysis, related content, related collections, survey contact.

For additional information about this survey or the methodology, contact

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Phd-Study-In-Usa

• PhD Funding in the USA – A Guide for 2024

PhD Funding in the USA

Written by Ben Taylor

Many of the world’s top research universities are based in the USA, so it’s no surprise that it’s an extremely popular destination for PhD students.

Although the USA has a reputation for being an expensive place to study, there are also some fantastic opportunities for PhD funding (including many fully-funded PhD programmes for international students).

This page will give you an introduction to the cost of a typical doctorate in the USA, as well as a guide to some of the most generous forms of PhD funding available at American universities.

On this page

American phd funding – what you need to know first.

As we’ve already mentioned, the USA has an expensive reputation – but you shouldn’t let that put you off.

There’s a reason why such a large number of American universities can be found among the top-ranked in the world: many institutions have huge budgets and endowments, allowing them to offer generous fully-funded PhD scholarships to graduate students (regardless of nationality).

These are a few key points to bear in mind when beginning your search for PhD funding in the USA:

• Public universities in the United States differentiate between in-state and out-of-state when it comes to fees, so you won’t necessarily be charged more than an out-of-state domestic student if you’re an international student
• Private universities don’t distinguish between domestic and international students
• It’s common for universities to offer ‘full-ride’ PhD scholarships to talented grad students
• The Fulbright Commission administers several funding schemes for international students to complete their research in the USA
• Federal student loans are available to US nationals

The cost of a PhD in the USA

With a huge range of universities offering PhD programmes in the USA it’s no surprise that American PhD fees vary a lot. They also tend to be exaggerated or otherwise misreported based on very high figures for prestigious Ivy League universities. These aren’t typical.

Actual fees vary between public and private institutions and sometimes depend on a students’ residency status:

• Public institutions charge an average of $12,394 per year for in-state students on graduate programmes. Be aware that fees for out-of-state students (including international students) are higher than this.
• Private institutions charge an average of $26,621 per year for all students on graduate programmes.

These figures are based on data published by the US National Center for Education Statistics . As a general rule, public institutions will be cheaper than private institutions, but will charge a higher out-of-state fee to international students. This can mean that the actual difference in fees is smaller than it seems above. Private institutions, on the other hand, may have more funding available.

The best way to get a sense of the tuition fees you will actually pay for a US PhD is to look up a few programmes in your subject and compare their prices. Just make sure you’re comparing the same thing: some universities will list fees per year, whereas others may list fees per semester or per credit.

In-state vs out-of-state

US universities don’t distinguish between international students and domestic fees in the same way as the UK. But public universities do differentiate between students from inside or outside their state. This is because ‘in-state’ students have their education partly subsidised by their state government. As an international student you’ll pay the same fee as a US student from ‘out-of-state’.

Living costs

The sheer size of the USA makes it almost impossible to offer accurate figures for student living costs across all 50 states. So we haven’t. You should definitely include this in your research and preparation though. Some parts of the USA are much more affordable than others. Your university’s international office may be able to help provide a sense of typical graduate student expenses for rent, groceries and travel.

See our guide to living in the USA during a PhD for more advice.

Other expenses

American universities will usually charge additional fees for processing graduate school applications. You’ll also need to budget for admissions tests, language tests and your visa.

Fulbright Postgraduate Scholarships

The US-UK Fulbright Commission is an organisation dedicated to fostering research connections between the United States and the United Kingdom.

Every year they offer postgraduate scholarships to talented British students to help them study at an American university (and vice versa).

A Fulbright Postgraduate Award offers the following benefits:

• A contribution towards your tuition fees (this could cover the first year of fees or fully-fund the entire degree, depending on the award and institution)
• Health insurance cover
• Visa sponsorship

Fulbright Scholars will also gain valuable networking opportunities through a global alumni organisation, as well as support during their studies from the Institute of International Education (IIE).

There are a range of Fulbright Postgraduate Awards available, with some providing a fully-funded PhD degree and others only offering a one-year tuition fee waiver. You can check out the Fulbright Postgraduate Scholarships on their website.

Eligibility for Fulbright Postgraduate Awards

The main eligibility requirement for a US-UK Fulbright Award is, unsurprisingly, that you must be a British citizen. However, if you’re a foreign national settled in the UK you may also be able to apply.

You’ll also need an undergraduate result of at least a 2.1 (although a 2.2 may be accepted on a case-by-case basis).

As the primary goal of the US-UK Fulbright Commission is to foster new connections between the countries, the ideal candidate won’t have spent more than six months in the United States already.

Applying for a Fulbright Postgraduate Award

The application process for a Fulbright Award usually opens in August, with a deadline in early November.

You’ll need to make an online application with the following documents/details:

• Academic transcripts
• Passport photo
• Personal statement
• Research objectives

You’ll also need to complete a separate application to the university you want to do your PhD at.

Shortlisted candidates will be invited to attend an interview in the following February.

Other Fulbright PhD scholarships

The above information focuses on the US-UK Fulbright Commission, which is part of a much larger network of organisations devoted to helping talented international students attend American universities.

Fulbright-Nehru Doctoral Fellowships , for example, offer Indian students the chance to complete a funded research placement (six to nine months) in the USA.

The Fulbright Foreign Student Program provides Nigerian doctoral students with the opportunity to conduct PhD research in the United States.

Fulbright Germany’s Doktorand:innenprogramm (PhD student programme) is a similar scheme to help German researchers complete work in the USA.

You can view Fulbright programmes by country on the Bureau of Educational and Cultural Affairs website.

University PhD scholarships

It’s actually very common for US universities to provide fully-funded PhD programmes for international students, and relatively rare for successful candidates on graduate programmes to be entirely self-funding. The ‘sticker price’ for a US PhD may seem high, but it’s probably not the price you’ll end up paying.

Funding will take various forms. ‘Full-ride’ PhD scholarships will cover fees, living costs and other expenses. Other common options include partial fee discounts or full fee waivers.

In general, private universities will have more funding than public universities (though they will also have higher fees). You can search some of the PhD funding available using an official tool provided by Education USA . These results aren’t exhaustive though: make sure you also check with the university you are considering.

We’ve done some of the leg-work for you and produced a list of international PhD scholarships available at some of the top American universities, which you can check out below.

Assistantships

As well as awarding direct funding, it’s common for US universities to offer assistantship positions to their graduate students. These are effectively a form of employment with the university : you will fulfil a selection of responsibilities in exchange for a stipend or a fee waiver.

Common types of assistantship include:

• Graduate teaching assistantships – These involve teaching and mentoring undergraduate students on courses related to your subject. Responsibilities may include leading discussion groups, supervising essays and helping with course admin. Graduate students doing this kind of work are sometimes referred to as ‘TAs’ (teaching assistants) or ‘adjunct faculty’. Find out more about graduate teaching assistantships .
• Research assistantships – These involve helping faculty with their research. Responsibilities may include collecting and recording routine data, monitoring experiments or helping set up equipment.
• Administrative assistantships – These involve clerical, administrative and secretarial work for the university or graduate programme. Responsibilities may include data entry and management, assisting with meetings and other activities or helping with other routine office tasks.
• Fellowships – These don’t involve additional work but may be conditional on maintaining a certain standard for your academic work or pursuing particular directions with your research.

Graduate teaching assistantships and research assistantships are the most common types of assistantship, but it’s worth checking to see what different universities offer.

Federal grants and aid

National science foundation (nsf) graduate research fellowship program (grfp).

The National Science Foundation’s GRFP is a long-established federal grant scheme for talented STEM graduate students in the USA, providing the opportunity of a fully-funded PhD. Past fellows include over 40 Nobel laureates.

The GRFP offers the following financial benefits over a three-year period:

• $37,000 annual stipend
• Tuition fee allowance of $12,000 (paid directly to the university)

Applicants for the NSF GRFP must be:

• American citizens, permanent residents or nationals
• Graduate students beginning a research-based Masters or PhD degree in a STEM subject
• Embarking on Masters or PhD study for the first time

As you might expect, competition for these prestigious fellowships is high, with around 12,000 applications for 2,000 places.

There are four main elements to an NSF GRFP application:

• Graduate research plan statement
• Two or three reference letters

The deadline for submitting these documents is usually mid to late October, with the results announced at the beginning of April.

You can find out more on the NSF GRFP website .

Federal Student Aid for US students

If you’re a US citizen, you may be able to receive financial aid from the government to help fund your studies. Generally, international students are not eligible to apply except in very specific circumstances .

You’ll also need to have financial need, but there is no income cut-off to qualify for financial aid. Rather, there are several factors considered when assessing your application.

Unlike undergraduate students, Masters and PhD applicants are considered independent for financial aid purposes, meaning only your own income and assets are taken into account, as opposed to your parents’.

The types of federal aid available for postgraduate students include:

#1 Federal loans

Loans available for Masters students include Direct Unsubsidized Loans and Direct PLUS Loans .

For Direct Unsubsidized Loans , your university determines how much money you’re eligible to receive, up to an upper limit that depends on your personal circumstances. Find out more about Direct Unsubsidized Loan limits. Interest rates are currently set at 7.05% for the 2023-24 year.

Direct PLUS Loans don’t award a set amount. Instead, you can borrow up to the full cost of your Masters programme, minus any other forms of financial support you are receiving for it. Interest rates are set at 8.05% for the 2023-24 year.

To apply, you’ll need to be studying a course at 50% intensity or more (part-time programmes are eligible for direct plus loans, provided you study on a ‘half-time’ basis or greater). You’ll also need a good credit history to apply a Direct PLUS loan. You won’t normally be able to receive a Direct PLUS Loan if you have a record of credit default or overdue debt for existing loans. In some cases, a parent or other US citizen may endorse your application as a guarantor.

As a Masters student you won’t repay your loan until six months after you cease to be enrolled on your course. Note that this repayment period will normally still come into effect if you exit your graduate programme early.

Actual repayment plans vary, but you can view a set of guides from the US Department of Education .

#2 Work-study

Federal work study provides part-time jobs for US students who have financial need, to help them cover their living costs and tuition fees.

Roles can be on or off campus, and where possible related to your field of study. Off-campus jobs are generally for nonprofit organisations or public agencies, and must be performed in the public interest.

Postgraduate students may be paid by the hour or by salary, depending on the type of role performed. How many hours you’re allowed to work will be determined by your university’s financial aid office.

Federal work-study is generally not available for international students, but there are other ways to earn money alongside your studies. We cover this in our guide to working in the USA as a student .

Applying for financial aid

To apply for financial aid, you’ll need to submit a Free Application for Federal Student Aid (FAFSA) form. Filling in the FAFSA involves creating an online account and receiving a unique FSA ID.

You should have access to the following documents and information when filling in the FAFSA:

• Your social security number
• Your driving license number (if you have one)
• Your Alien Registration Number (of you are not a US citizen)
• Tax documents or tax returns for yourself and your spouse (if married)
• Records of any untaxed income, savings, cash or investments

The FAFSA form for becomes available for course starting the following year on 1 October annually. So if you’re planning to study a Masters or PhD starting in Autumn 2024, you’ll be able to fill in the FAFSA from 1 October 2023 .

The FAFSA deadline for 2023-24 is 30 June 2024 .

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Master of Science in Data Science

Purdue University's online Master's in Data Science will mold the next generation of data science experts and data engineers to help meet unprecedented industry demand for skilled employees. The interdisciplinary nature of the degree allows students to work with Purdue's well renowned faculty in their fields, and customize the program tailored towards specific areas of data science.

Ready to Become a Boilermaker?

Learn more about the master of science in data science.

Data Science is a rapidly growing area within a number of different sectors and jobs. Meet the growing demand for data science experts with Purdue University’s online Master’s in Data Science.

Delivered through an online and flexible modality, select from different courses and pathways tailored towards your specific interest. Course topics include programming, data analysis, data engineering, statistics, machine learning, natural language processing, and more.

The cost of attending Purdue varies depending on where you choose to live, enrollment in a specific program or college, food and travel expenses, and other variables. The  Office of the Bursar  website shows estimated costs for the current aid year for students by semester and academic year. These amounts are used in determining a student’s estimated eligibility for financial aid. You can also use our  tuition calculator  to estimate tuition costs.

Program Specifics

Earn an online Master’s in Data Science from Purdue University. Professionals will learn from a wide range of topics from computer programming, data mining, machine learning, natural language processing, data engineering, statistics, and regression.

Course Topics:

• Programming
• Data Science
• Machine Learning
• Data Mining, Analysis, and Visualization
• Spatial Data
• Statistics and Algebra
• Natural Language Processing
• Data Engineering
• Organizational and Change Management
• Project Management
• Information Technology

Career Outcomes

Top Job Titles

• Software Engineer
• Data Scientist
• Machine Learning Engineer
• Research Scientist
• Data Analyst
• Quantitative Analyst

Top Industries

Source: LightcastTM (2023). Unique job postings for July 2022-2023. Projected growth for years 2023-2033.

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Are you ready to join the Purdue  innovators  and  changemakers  always striving to make giant leaps forward in our industries and fields? Start your application today!

You are not alone in taking your next giant leap. Get your questions answered, receive application help, or plan your degree journey by speaking with an enrollment counselor. Request more information today.