statistics phd programs

Best Statistics Programs

Ranked in 2022, part of Best Science Schools

With a graduate degree, statisticians may find jobs

With a graduate degree, statisticians may find jobs working with data in many sectors, including business, government, academia, public health, technology and other science fields. These are the best schools for statistics. Each school's score reflects its average rating on a scale from 1 (marginal) to 5 (outstanding), based on a survey of academics at peer institutions. Read the methodology »

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Graduate Student Handbook (Coming Soon: New Graduate Student Handbook)

Phd program overview.

The PhD program prepares students for research careers in probability and statistics in academia and industry. Students admitted to the PhD program earn the MA and MPhil along the way. The first year of the program is spent on foundational courses in theoretical statistics, applied statistics, and probability. In the following years, students take advanced topics courses. Research toward the dissertation typically begins in the second year. Students also have opportunities to take part in a wide variety of projects involving applied probability or applications of statistics.

Students are expected to register continuously until they distribute and successfully defend their dissertation. Our core required and elective curricula in Statistics, Probability, and Machine Learning aim to provide our doctoral students with advanced learning that is both broad and focused. We expect our students to make Satisfactory Academic Progress in their advanced learning and research training by meeting the following program milestones through courseworks, independent research, and dissertation research:

By the end of year 1: passing the qualifying exams;

By the end of year 2: fulfilling all course requirements for the MA degree and finding a dissertation advisor;

By the end of year 3: passing the oral exam (dissertation prospectus) and fulfilling all requirements for the MPhil degree

By the end of year 5: distributing and defending the dissertation.

We believe in the Professional Development value of active participation in intellectual exchange and pedagogical practices for future statistical faculty and researchers. Students are required to serve as teaching assistants and present research during their training. In addition, each student is expected to attend seminars regularly and participate in Statistical Practicum activities before graduation.

We provide in the following sections a comprehensive collection of the PhD program requirements and milestones. Also included are policies that outline how these requirements will be enforced with ample flexibility. Questions on these requirements should be directed to ADAA Cindy Meekins at [email protected] and the DGS, Professor John Cunningham at [email protected] .

Applications for Admission

• Our students receive very solid training in all aspects of modern statistics. See Graduate Student Handbook for more information.
• Our students receive Fellowship and full financial support for the entire duration of their PhD. See more details here .
• Our students receive job offers from top academic and non-academic institutions .
• Our students can work with world-class faculty members from Statistics Department or the Data Science Institute .
• Our students have access to high-speed computer clusters for their ambitious, computationally demanding research.
• Our students benefit from a wide range of seminars, workshops, and Boot Camps organized by our department and the data science institute .
• Suggested Prerequisites: A student admitted to the PhD program normally has a background in linear algebra and real analysis, and has taken a few courses in statistics, probability, and programming. Students who are quantitatively trained or have substantial background/experience in other scientific disciplines are also encouraged to apply for admission.
• GRE requirement: Waived for Fall 2024.
• Language requirement: The English Proficiency Test requirement (TOEFL) is a Provost's requirement that cannot be waived.
• The Columbia GSAS minimum requirements for TOEFL and IELTS are: 100 (IBT), 600 (PBT) TOEFL, or 7.5 IELTS. To see if this requirement can be waived for you, please check the frequently asked questions below.
• Deadline: Jan 8, 2024 .
• Application process: Please apply by completing the Application for Admission to the Columbia University Graduate School of Arts & Sciences .
• Timeline: P.hD students begin the program in September only.  Admissions decisions are made in mid-March of each year for the Fall semester.

Frequently Asked Questions

• What is the application deadline? What is the deadline for financial aid? Our application deadline is January 5, 2024 .
• Can I meet with you in person or talk to you on the phone? Unfortunately given the high number of applications we receive, we are unable to meet or speak with our applicants.
• What are the required application materials? Specific admission requirements for our programs can be found here .
• Due to financial hardship, I cannot pay the application fee, can I still apply to your program? Yes. Many of our prospective students are eligible for fee waivers. The Graduate School of Arts and Sciences offers a variety of application fee waivers . If you have further questions regarding the waiver please contact  gsas-admissions@ columbia.edu .
• How many students do you admit each year? It varies year to year. We finalize our numbers between December - early February.
• What is the distribution of students currently enrolled in your program? (their background, GPA, standard tests, etc)? Unfortunately, we are unable to share this information.
• How many accepted students receive financial aid? All students in the PhD 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. Teaching and research experience are considered important aspects of the training of graduate students. Thus, graduate fellowships include some teaching and research apprenticeship. PhD students are given funds to purchase a laptop PC, and additional computing resources are supplied for research projects as necessary. The Department also subsidizes travel expenses for up to two scientific meetings and/or conferences per year for those students selected to present. Additional matching funds from the Graduate School Arts and Sciences are available to students who have passed the oral qualifying exam.
• Can I contact the department with specific scores and get feedback on my competitiveness for the program? We receive more than 450 applications a year and there are many students in our applicant pool who are qualified for our program. However, we can only admit a few top students. Before seeing the entire applicant pool, we cannot comment on admission probabilities.
• What is the minimum GPA for admissions? While we don’t have a GPA threshold, we will carefully review applicants’ transcripts and grades obtained in individual courses.
• Is there a minimum GRE requirement? No. The general GRE exam is waived for the Fall 2024 admissions cycle. 
• Can I upload a copy of my GRE score to the application? Yes, but make sure you arrange for ETS to send the official score to the Graduate School of Arts and Sciences.
• Is the GRE math subject exam required? No, we do not require the GRE math subject exam.
• What is the minimum TOEFL or IELTS  requirement? The Columbia Graduate School of Arts and Sciences minimum requirements for TOEFL and IELTS are: 100 (IBT), 600 (PBT) TOEFL, or 7.5 IELTS
•  I took the TOEFL and IELTS more than two years ago; is my score valid? Scores more than two years old are not accepted. Applicants are strongly urged to make arrangements to take these examinations early in the fall and before completing their application.
• I am an international student and earned a master’s degree from a US university. Can I obtain a TOEFL or IELTS waiver? You may only request a waiver of the English proficiency requirement from the Graduate School of Arts and Sciences by submitting the English Proficiency Waiver Request form and if you meet any of the criteria described here . If you have further questions regarding the waiver please contact  gsas-admissions@ columbia.edu .
• My transcript is not in English. What should I do? You have to submit a notarized translated copy along with the original transcript.

Can I apply to more than one PhD program? You may not submit more than one PhD application to the Graduate School of Arts and Sciences. However, you may elect to have your application reviewed by a second program or department within the Graduate School of Arts and Sciences if you are not offered admission by your first-choice program. Please see the application instructions for a more detailed explanation of this policy and the various restrictions that apply to a second choice. You may apply concurrently to a program housed at the Graduate School of Arts and Sciences and to programs housed at other divisions of the University. However, since the Graduate School of Arts and Sciences does not share application materials with other divisions, you must complete the application requirements for each school.

How do I apply to a dual- or joint-degree program? The Graduate School of Arts and Sciences refers to these programs as dual-degree programs. Applicants must complete the application requirements for both schools. Application materials are not shared between schools. Students can only apply to an established dual-degree program and may not create their own.

With the sole exception of approved dual-degree programs , students may not pursue a degree in more than one Columbia program concurrently, and may not be registered in more than one degree program at any institution in the same semester. Enrollment in another degree program at Columbia or elsewhere while enrolled in a Graduate School of Arts and Sciences master's or doctoral program is strictly prohibited by the Graduate School. Violation of this policy will lead to the rescission of an offer of admission, or termination for a current student.

When will I receive a decision on my application? Notification of decisions for all PhD applicants generally takes place by the end of March.

Notification of MA decisions varies by department and application deadlines. Some MA decisions are sent out in early spring; others may be released as late as mid-August.

Can I apply to both MA Statistics and PhD statistics simultaneously?  For any given entry term, applicants may elect to apply to up to two programs—either one PhD program and one MA program, or two MA programs—by submitting a single (combined) application to the Graduate School of Arts and Sciences.  Applicants who attempt to submit more than one Graduate School of Arts and Sciences application for the same entry term will be required to withdraw one of the applications.

The Graduate School of Arts and Sciences permits applicants to be reviewed by a second program if they do not receive an offer of admission from their first-choice program, with the following restrictions:

• This option is only available for fall-term applicants.
• Applicants will be able to view and opt for a second choice (if applicable) after selecting their first choice. Applicants should not submit a second application. (Note: Selecting a second choice will not affect the consideration of your application by your first choice.)
• Applicants must upload a separate Statement of Purpose and submit any additional supporting materials required by the second program. Transcripts, letters, and test scores should only be submitted once.
• An application will be forwarded to the second-choice program only after the first-choice program has completed its review and rendered its decision. An application file will not be reviewed concurrently by both programs.
• Programs may stop considering second-choice applications at any time during the season; Graduate School of Arts and Sciences cannot guarantee that your application will receive a second review.
• What is the mailing address for your PhD admission office? Students are encouraged to apply online . Please note: Materials should not be mailed to the Graduate School of Arts and Sciences unless specifically requested by the Office of Admissions. Unofficial transcripts and other supplemental application materials should be uploaded through the online application system. Graduate School of Arts and Sciences Office of Admissions Columbia University  107 Low Library, MC 4303 535 West 116th Street  New York, NY 10027
• How many years does it take to pursue a PhD degree in your program? Our students usually graduate in 4‐6 years.
• Can the PhD be pursued part-time? No, all of our students are full-time students. We do not offer a part-time option.
• One of the requirements is to have knowledge of linear algebra (through the level of MATH V2020 at Columbia) and advanced calculus (through the level of MATH V1201). I studied these topics; how do I know if I meet the knowledge content requirement? We interview our top candidates and based on the information on your transcripts and your grades, if we are not sure about what you covered in your courses we will ask you during the interview.
• Can I contact faculty members to learn more about their research and hopefully gain their support? Yes, you are more than welcome to contact faculty members and discuss your research interests with them. However, please note that all the applications are processed by a central admission committee, and individual faculty members cannot and will not guarantee admission to our program.
• How do I find out which professors are taking on new students to mentor this year?  Applications are evaluated through a central admissions committee. Openings in individual faculty groups are not considered during the admissions process. Therefore, we suggest contacting the faculty members you would like to work with and asking if they are planning to take on new students.

For more information please contact us at [email protected] .

For more information please contact us at  [email protected]

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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.

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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This program has a rich tradition of creating groundbreaking statistical methods and conducting innovative applied statistics, bridging theory and practice and supporting knowledge discovery and decision-making through meaningful data extraction and analysis. Statistics is an indispensable pillar of modern science, including data science and artificial intelligence.

You can take advantage of the department’s flexible research options and work with your faculty of choice. You can leverage cross-department collaboration with biology, chemistry, medical sciences, economics, computer science, government, and public health to pursue your intellectual interests. You will become part of a close-knit, friendly department that offers many extra learning opportunities both inside and outside the program.

Examples of student projects include developing statistical methods to forecast infectious diseases from online search data, delineating causality from association, building a software package for evaluating redistricting plans in 50 states, leveraging machine learning algorithms for model-free inference, and employing a randomization-based inference framework to study peer effects. 

Graduates have secured faculty positions in institutions such as Stanford University; University of Pennsylvania; University of California, Berkeley; Johns Hopkins University; Carnegie Mellon University; Columbia University; and Georgia Institute of Technology. Others have begun careers at organizations such as Google, Apple, Etsy, Citadel, and the Boston Red Sox. 

Additional information on the graduate program is available from the Department of Statistics , and requirements for the degree are detailed in Policies .

Admissions Requirements

Please review admissions requirements and other information before applying. You can find degree program-specific admissions requirements below and access additional guidance on applying from the Department of Statistics .

Academic Background

Applicants should understand what the discipline of statistics entails and show evidence of involvement in applications or a strong theoretical interest.

The minimum mathematical preparation for admission is linear algebra and advanced calculus. Ideally, each student’s preparation should include at least one term each of mathematical probability and mathematical statistics. Additional study in statistics and related mathematical areas, such as analysis and measure theory, is helpful. In the initial stages of graduate study, students should give high priority to acquiring the mathematical level required to satisfy their objectives.

As statistics is so intimately connected with computation, computation is an important part of almost all courses and research projects in the department. Preferably, students should have programming experience relevant for statistical computation and simulation.

Standardized Tests

GRE General: Optional GRE Subject: Optional

Theses & Dissertations

Theses & Dissertations for Statistics

See list of Statistics faculty

APPLICATION DEADLINE

Questions about the program.

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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.

Apply online here .

Department of Statistics and Data Science

The Wharton School, University of Pennsylvania Academic Research Building 265 South 37th Street, 3rd & 4th Floors Philadelphia, PA 19104-1686

Phone: (215) 898-8222

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Doctoral Program

Program summary.

Students are required to

• master the material in the prerequisite courses ;
• pass the first-year core program;
• attempt all three parts of the qualifying examinations and show acceptable performance in at least two of them (end of 1st year);
• satisfy the depth and breadth requirements (2nd/3rd/4th year);
• successfully complete the thesis proposal meeting (winter quarter of the 3rd year);
• present a draft of their dissertation and pass the university oral examination (4th/5th year).

The PhD requires a minimum of 135 units. Students are required to take a minimum of nine units of advanced topics courses (for depth) offered by the department (not including literature, research, consulting or Year 1 coursework), and a minimum of nine units outside of the Statistics Department (for breadth). Courses for the depth and breadth requirements must equal a combined minimum of 24 units. In addition, students must enroll in STATS 390 Statistical Consulting, taking it at least twice.

All students who have passed the qualifying exams but have not yet passed the Thesis Proposal Meeting must take STATS 319 at least once each year. For example, a student taking the qualifying exams in the summer after Year 1 and having the dissertation proposal meeting in Year 3, would take 319 in Years 2 and 3. Students in their second year are strongly encouraged to take STATS 399 with at least one faculty member. All details of program requirements can be found in our PhD handbook (available to Stanford affiliates only, using Stanford authentication. Requests for access from non-affiliates will not be approved).

Statistics Department PhD Handbook

All students are expected to abide by the Honor Code and the Fundamental Standard .

Doctoral and Research Advisors

During the first two years of the program, students' academic progress is monitored by the department's Graduate Director. Each student should meet at least once a quarter with the Graduate Director to discuss their academic plans and their progress towards choosing a thesis advisor (before the final study list deadline of spring of the second year). From the third year onward students are advised by their selected advisor.

Qualifying Examinations

Qualifying examinations are part of most PhD programs in the United States. At Stanford these exams are intended to test the student's level of knowledge when the first-year program, common to all students, has been completed. There are separate examinations in the three core subjects of statistical theory and methods, applied statistics, and probability theory, which are typically taken during the summer at the end of the student's first year. Students are expected to attempt all three examinations and show acceptable performance in at least two of them. Letter grades are not given. Qualifying exams may be taken only once. After passing the qualifying exams, students must file for Ph.D. Candidacy, a university milestone, by the end of spring quarter of their second year.

While nearly all students pass the qualifying examinations, those who do not can arrange to have their financial support continued for up to three quarters while alternative plans are made. Usually students are able to complete the requirements for the M.S. degree in Statistics in two years or less, whether or not they have passed the PhD qualifying exams.

Thesis Proposal Meeting and Dissertation Reading Committee 

The thesis proposal meeting is intended to demonstrate a student's depth in some areas of statistics, and to examine the general plan for their research. In the meeting the student gives a 60-minute presentation involving ideas developed to date and plans for completing a PhD dissertation, and for another 60 minutes answers questions posed by the committee. which consists of their advisor and two other members. The meeting must be successfully completed by the end of winter quarter of the third year. If a student does not pass, the exam must be repeated. Repeated failure can lead to a loss of financial support.

The Dissertation Reading Committee consists of the student’s advisor plus two faculty readers, all of whom are responsible for reading the full dissertation. Of these three, at least two must be members of the Statistics Department (faculty with a full or joint appointment in Statistics but excluding for this purpose those with only a courtesy or adjunct appointment). Normally, all committee members are members of the Stanford University Academic Council or are emeritus Academic Council members; the principal dissertation advisor must be an Academic Council member. 

The Doctoral Dissertation Reading Committee form should be completed and signed at the Dissertation Proposal Meeting. The form must be submitted before approval of TGR status or before scheduling a University Oral Examination.

 For further information on the Dissertation Reading Committee, please see the Graduate Academic Policies and Procedures (GAP) Handbook section 4.8.

University Oral Examinations

The oral examination consists of a public, approximately 60-minute, presentation on the thesis topic, followed by a 60 minute question and answer period attended only by members of the examining committee. The questions relate to the student's presentation and also explore the student's familiarity with broader statistical topics related to the thesis research. The oral examination is normally completed during the last few months of the student's PhD period. The examining committee typically consists of four faculty members from the Statistics Department and a fifth faculty member from outside the department serving as the committee chair. Four out of five passing votes are required and no grades are given. Nearly all students can expect to pass this examination, although it is common for specific recommendations to be made regarding completion of the thesis.

The Dissertation Reading Committee must also read and approve the thesis.

For further information on university oral examinations and committees, please see the Graduate Academic Policies and Procedures (GAP) Handbook section 4.7 .

Dissertation

The dissertation is the capstone of the PhD degree. It is expected to be an original piece of work of publishable quality. The research advisor and two additional faculty members constitute the student's dissertation reading committee.

DEPARTMENT OF STATISTICS AND DATA SCIENCE

Phd program, phd program overview.

The doctoral program in Statistics and Data Science is designed to provide students with comprehensive training in theory and methodology in statistics and data science, and their applications to problems in a wide range of fields. The program is flexible and may be arranged to reflect students' interests and career goals. Cross-disciplinary work is encouraged. The PhD program prepares students for careers as university teachers and researchers and as research statisticians or data scientists in industry, government and the non-profit sector.

Requirements

Students are required to fulfill the Department requirements in addition to those specified by The Graduate School (TGS).

From the Graduate School’s webpage outlining the general requirements for a PhD :

In order to receive a doctoral degree, students must:

• Complete all required coursework. .
• Gain admittance to candidacy.
• Submit a prospectus to be approved by a faculty committee.
• Present a dissertation with original research. Review the Dissertation Publication page for more information.
• Complete the necessary teaching requirement
• Submit necessary forms to file for graduation
• Complete degree requirements within the approved timeline

PhD degrees must be approved by the student's academic program. Consult with your program directly regarding specific degree requirements.

The Department requires that students in the Statistics and Data Science PhD program:

• Meet the department minimum residency requirement of 2 years
• STAT 344-0 Statistical Computing
• STAT 350-0 Regression Analysis
• STAT 353-0 Advanced Regression (new 2021-22)
• STAT 415-0 I ntroduction to Machine Learning
• STAT 420-1,2,3 Introduction to Statistical Theory and Methodology 1, 2, 3
• STAT 430-1, STAT 430-2, STAT 440 (new courses in 2022-23 on probability and stochastic processes for statistics students)
• STAT 457-0 Applied Bayesian Inference

Students generally complete the required coursework during their first two years in the PhD program. *note that required courses changed in the 2021-22 academic year, previous required courses can be found at the end of this page.

• Pass the Qualifying Exam. This comprehensive examination covers basic topics in statistics and is typically taken in fall quarter of the second year.

Pass the Prospectus presentation/examination and be admitted for PhD candidacy by the end of year 3 . The statistics department requires that students must complete their Prospectus (proposal of dissertation topic) before the end of year 3, which is earlier than The Graduate School deadline of the end of year 4. The prospectus must be approved by a faculty committee comprised of a committee chair and a minimum of 2 other faculty members. Students usually first find an adviser through independent studies who will then typically serve as the committee chair. When necessary, exceptions may be made upon the approval of the committee chair and the director of graduate studies, to extend the due date of the prospectus exam until the end of year 4.

• Successfully complete and defend a doctoral dissertation. After the prospectus is approved, students begin work on the doctoral dissertation, which must demonstrate an original contribution to a chosen area of specialization. A final examination (thesis defense) is given based on the dissertation. Students typically complete the PhD program in 5 years.
• Attend all seminars in the department and participate in other research activities . In addition to these academic requirements, students are expected to participate in other research activities and attend all department seminars every year they are in the program.

Optional MS degree en route to PhD

Students admitted to the Statistics and Data Science PhD program can obtain an optional MS (Master of Science) degree en route to their PhD. The MS degree requires 12 courses: STAT 350-0 Regression Analysis, STAT 353 Advanced Regression, STAT 420-1,2,3 Introduction to Statistical Theory and Methodology 1, 2, 3, STAT 415-0 I ntroduction to Machine Learning , and at least 6 more courses approved by the department of which two must be 400 level STAT elective courses, no more than 3 can be non-STAT courses. For the optional MS degree, students must also pass the qualifying exam offered at the beginning of the second year at the MS level.

*Prior to 2021-2022, the course requirements for the PhD were:

• STAT 351-0 Design and Analysis of Experiments
• STAT 425 Sampling Theory and Applications
• MATH 450-1,2 Probability 1, 2 or MATH 450-1 Probability 1 and IEMS 460-1,2 Stochastic Processes 1, 2
• Six additional 300/400 graduate-level Statistics courses, at least two must be 400 -level

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 year (due May 1), students are expected to fill out the Annual Progress Review . 
• Seminar Series All students are expected to attend the SDS Seminar Series
• SDS 189R Course Description (when taken for internship)
• Internship Course Registration form
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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  

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]

• 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. 

Department of Technology, Operations, and Statistics | Doctoral Program in Statistics

Doctoral program in statistics.

• Program of Study

Program Requirements

• Doctoral Students and Their Research
• Statistics Faculty

Overview of the Doctoral Program in Statistics

The world’s financial markets produce an enormous stream of data, and the understanding of the techniques needed to analyze and extract information from this stream has become critical.   Doctoral work in statistics combines theory and methodology to deal with the large quantity of statistical data.  Here at Stern we use the theoretical and methodological orientation of a traditional statistics with a focus on the applications that are central to the concerns of a business school.  The PhD thesis work at Stern is a mathematically sophisticated enterprise that never loses sight of the real and practical problems of business.

Stern’s curriculum in statistics prepares students for academic positions by preparing them to conduct independent research.  The statistician must be knowledgeable of the basic issues of the intellectual areas in which his or her work will be applied. 

The most popular areas of student interest in the last few years have been mathematical finance, statistical modeling, data mining, stochastic processes, and econometrics.

Students have rigorous course work and participate in special topics seminars.  They work closely with the faculty and also present special PhD student seminars.

Clifford Hurvich Coordinator, Statistics Doctoral Program

Mission Our mission is the education of scholars who will produce first-rate statistics research and who will succeed as faculty members at first-rate universities.

Admissions and performance We enroll one or two students each year;  these are chosen from approximately 100 highly qualified applicants.

Advising and evaluation Each student will meet with a committee of faculty members yearly to assess progress through the program.

Research and interaction with faculty The Stern statistics faculty have a wide range of interests, but there is special emphasis on time series, statistical modeling, stochastic processes, and financial modeling.

PhD students in statistics take courses in statistical inference, stochastic processes, time series, regression analysis, and multivariate analysis.

In addition to course work, doctoral students also participate in research projects in conjunction with faculty members.  The students attend seminars, present seminars on their own work, and submit their work for publication.

The program culminates with the creation of the PhD thesis, through the stages of proposal, writing, and defense.

Most students finish in four to five years.

Statistics Program of Study

Statistics PhD students take their course work in the first two years of study.  These courses are taken within the Statistics Group (both as formal courses and also as independent study), within other departments at the Stern School, at NYU's Courant Institute, and at Columbia University.

In addition to their statistics courses, doctoral students in Statistics often take courses in mathematics, finance, market research, and econometrics.  The individual curriculum will be planned with the help of faculty advisers.

Questions about the PhD Program in Statistics?

Explore stern phd.

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Ph.d. program.

Statistical Science at Duke is the world's leading graduate research and educational environment for Bayesian statistics, emphasizing the major themes of 21st century statistical science: foundational concepts of statistics, theory and methods of complex stochastic modeling, interdisciplinary applications of statistics, computational statistics, big data analytics, and machine learning. Life as a Ph.D. student in Statistical Science at Duke involves immersion in a broad range of research experiences and emphasizes conceptual innovation, as well as building a deep and broad foundation in theory and methods.

Coupled with our core emphases in modeling, computation and the methodologies of modern statistical science is a broad range of interdisciplinary relationships with many other disciplines (biomedical sciences, environmental sciences, genomics, computer science, engineering, finance, neuroscience, social sciences, and others). The rich opportunities for students in interdisciplinary statistical research at Duke are complemented by opportunities for engagement in research in summer projects with nonprofit agencies, industry, and academia.

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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

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Department of Statistics

4c69b3a36a33a4c1c5b5cd3ef5360949.

• Open Positions

In our graduate program, we aim to develop statisticians not only for academia, but also ones who will become leaders in endeavors such as medicine, law, finance, technology, government, and industry. Our graduate program is a stepping stone to a successful career in statistics.

The application portal will open in early fall.  Applications to the PhD program are due December 1st, 2023.  On Monday, March 4th, 2024, we will host a Visit Day for students admitted to the PhD program.

Harvard University does not discriminate against applicants or students on the basis of race, color, national origin, ancestry or any other protected classification.

Program Directors :

Jun Liu - Joint Director of Graduate Studies (currently enrolled PhD students, all aspects of the graduate program)

Susan Murphy - Joint Director of Graduate Studies (PhD program admissions)

Mark Glickman - Director of Masters Studies (all aspects of the AB/AM and concurrent masters program)

Our past graduates have an outstanding placement record, having had their choice of careers in academia, banking and financial services, information technology, medical research, economic research and public policy. Several of our past Ph.D. students have made their own marks in the academic world of statistics through development of fundamental statistical methodology.

Courses we offer

The department offers a wide range of courses that provide graduate students with strong foundations in theoretical and applied statistics. Also offered is an array of 300-level seminar courses which are considered stepping stones to literature review and research in specific fields.

Excellence of our Graduate program

As a direct result of the aforementioned pedagogical and related efforts, our department was the recipient from the Graduate School of Arts and Sciences (GSAS) of the $25,000 GSAS Dean's Prize for Innovations in Graduate Education. Furthermore, seven years in a row our teaching fellows have won the  Derek Bok Award of Excellence in Teaching Undergraduates Students by Graduate Students , in its first seven years of existence (no other department has won more than twice in a row).

The environment

Students often find the department to be a home away from home, with frequent lunches, seminars, and meals with visiting speakers, workshop-style research seminars, and other events. Indeed, we take special pride in being perhaps the only department that has an endowed massage chair for graduate students (the first requested use of the Innovations Prize). The Department also has a big sister/big brother program to help new students get acclimated, especially international students.

For Additional Questions

For further information about these programs, you can explore this website. If you have general questions about the application process or the status of your application, the online application tool, submitting forms, GSAS deadlines, or applying to other programs, please contact the  GSAS Admissions Office .

If you have additional questions specifically about admission to the Statistics PhD program you can email our Student Programs Administrator, Kathleen Cloutier ( [email protected] ). 

Graduate Program Information

Learn more about the Statistics PhD program and requirements  

PhD Admissions

Learn more about the PhD program admissions process through GSAS  

Data Science Master's Degree

Offered through the John A. Paulson School of Engineering and Applied Sciences (SEAS)

AM Program The AM program is open to current GSAS Ph.D. students, and to undergraduates pursuing a concurrent fourth-year masters degree. GSAS admitted the last cohort of external AM students in statistics in the Fall of 2017.

Stats Graduate Courses

Graduate Courses Tree Stat 300: Research in Statistics Stat 303: The Art and Practice of Teaching Statistics  

PhD Resources and Support

Phd dissertations, biostatistics program, gsas admissions overview, still need assistance.

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 - Donald Bren School of Information & Computer Sciences

M.s. & ph.d. in statistics.

* Graduate application deadline is Dec. 15, submit your  online  application now! *

Individuals from a variety of backgrounds can make significant contributions to the field of statistics as long as they have sufficient background in statistics, mathematics, and computing.

Undergraduate preparation in statistics, mathematics, and computing should include multivariate calculus (the equivalent of UCI courses Mathematics 2A-B, 2D-E), linear algebra (121A), elementary analysis (140A-B), introductory probability and statistics (Statistics 120A-B-C), and basic computing (ICS 21).

For students with undergraduate majors outside of mathematics and statistics, it is possible to make up one or two missing courses during the first year in the program.

The UCI General Catalogue is the official guide to all degree and graduation requirements. For previous calendar years, please see here .

• Current Degree Requirements
• ICS Graduate Handbook

Statistics and Actuarial Science

Information for new graduate students in actuarial science, data science and statistics at the university of iowa..

Welcome New Graduate Students!

Information for NEW graduate students in Actuarial Science, Data Science and Statistics at the University of Iowa. 

Last Updated, May 31, 2024.                                   Additional  updates will be sent this summer!

Important Information for International Students

The Office of International Students and Scholars does an incredible job helping you settle into Iowa City and the University of Iowa.  They have webinars to help with:  

1. Getting Started and Making Travel Arrangements

2. Achieving Success: On-campus Involvement and Cultural Adjustment (undergraduate students)

3. Graduate Student Professionalization and Support

4. Understanding Orientation Expectations, Responsibilities, and Placement Tests (graduate students)

5. On-campus Housing Assignments and Move-in Tips (undergraduate students)

6. Student Employment

7. Money Matters - University Billing

Do you need to take the SPEC (Spoken Proficiency of English for the Classroom)?

All students for whom English is not a first language (as self-reported on their admissions application) and who have first-time appointments as graduate teaching assistants (TAs) are required to go through a testing process to assess their effectiveness in speaking English before they are assigned assistantship responsibilities. Beginning in Fall 2024, there will be a new test to assess communication in English in a classroom context called SPEC (Spoken Proficiency of English in the Classroom).  This is replacing ESPA and ELPT.  Details will be coming soon.

Any graduate student who is included in the following categories needs to have their oral English proficiency tested by the TAPE Program:

• Students whose first language is not English (i.e., learned another language first) as self-reported on their admissions application, and
• Have been appointed as a Teaching Assistant

Exemptions (may change):

• Students with an official valid (within the last two years) iBT Listening score of 25 and an iBT Speaking score of 26.
• Undergraduate degrees and/or     
• Continuous attendance of English-language schools since the age of 12 (or younger)
• Students who served as teaching assistants at other institutions of higher learning in which the language of instruction is English, if they were listed as the instructor of record for a course or led a discussion section in English for at least one year, with a year defined as either two academic semesters or three academic quarters.
• Requests for exceptions regarding the SPEC  can be submitted for evaluation to a committee consisting of the Director of ESL Programs, the Associate Dean for Administrative Affairs in the Graduate College, and a representative from University Human Resources.

Requests for exemption and exceptions must come from the department by the deadline, not the student.   Deadlines to register students for the SPEC are:

• March 1  

NOT Exemptions:

• Students who come from a country where English is one of the official languages.
• Students who are U.S. permanent residents or U.S. citizens whose first language is not English.

Testing Procedures & Results

 To be announced soon!

Graduate/Professional International Students Important Dates

July 12, 2024:  Earliest date you may enter the U.S. in F-1 or J-1 status. August 11, 2024:  Latest date by which you should arrive in Iowa City August 12 - 16, 2024: International Student Orientation August 26, 2024:  Classes begin.

Housing Information for All Students

The department has a housing webpage, please let us know if you have any questions or concerns. If you are looking for a roommate, please let us know and we can update this web page!

Looking for housing options ?

All US citizens that are financially supported (TA, RA) need to be here on August 21.

All students will register for classes the week before classes start.  International students must complete the required Orientation Program before  they can register for classes.    

____________________

Fall Classes Advising will be August 19-23

All NEW UI students must meet with their advisor prior to registration.  There is no worry about getting into any of the classes we teach.  

• IF you are an Actuarial Science MS or PhD student you will need to meet with Professor Shyamalkumar.  Email him after August 12 at [email protected] to set a time to meet to discuss what classes to take, it may be on Zoom or in his office (233 Schaeffer Hall).
• IF you are a Data Science MS, Statistics MS, or PhD student you will need to meet with Professor Boxiang Wang.  Email him after August 12 at [email protected]  to set a time to meet to discuss what classes to take, it may be on Zoom or in his office (261 Schaeffer Hall).

New Graduate College Welcome and Orientation, August 21

The Graduate College Fall 2024 Graduate Student Orientation event will take place on Wednesday, August 21, 2024.  A registration form will be sent to your UI email sometime this early summer from the Graduate College. All new doctoral and master’s students are invited to attend.  

New Teaching Assistant Orientation, August 22- required for all new supported students

Sponsored by the Center for Teaching

This event will introduce participants to the role of teaching assistant at the University of Iowa and prepare them for the first week of classes and beyond. 

Participants will discuss evidence-based teaching strategies for lesson planning, inclusive teaching, and more with Center for Teaching staff. Participants will also choose two workshops of interest to them out of several options; these will be facilitated synchronously by experienced TAs.  This is a virtual event for 9-noon.

• Sign up before August 21!

New Student Department Orientation, August 23 at 9 a.m., Room to be determined.

• All New Student Orientation —Group Introductions and General Policy Procedures.

New Supported Graduate Assistants Orientation, August 23 at 1 p.m., Room to be determined.

• Our Director of Graduate Studies will have a department review of expectations and your specific roles in our department. Teaching and grading assignments will be explained, as well as preparation, teaching tips, problems and questions, quizzes and exams, weekly meetings, grading, appropriate office use and the Sexual Harassment Prevention Education

Mailbox in 241 Schaeffer Hall 

All graduate students will have a mailbox in our main office.  The faculty do as well.  Please check your mailbox at least once a week!

Office Desk Assignment

Nearly all supported students will have a desk in one of our offices.  The assignment priority (in this order) includes Ph.D. and Fellowship candidates, research assistants, half-time teaching assistants, quarter-time teaching assistants and lastly graders.  Having a desk is a privilege and should be used only for university business.  Office assignments will be given to students on, August 23.  Keys are checked out ONLY after that time.  Please remember to keep the rooms clean and take out all trash to the large bins in the main hallways.

Set-up your University of Iowa Email

All University of Iowa students are required to activate their assigned uiowa.edu email address, as all official communication from university offices are now sent via email, rather than hard copy. This address usually follows the pattern [email protected]   (However, often a number is also attached.) 

To activate the account:

• Log on to  MyUI
• Click on My UIowa / My Email / Request Email Account
• Complete the specified steps.

Students who prefer to maintain only their work or home email addresses can do so by routing the uiowa.edu email to a work or home account. To do so, follow these steps:

• Click on My UIowa / My Email / Update Email Routing Address

Important Notes:

• If your uiowa.edu email address is routed to a different account, you will  not  need to change your address in ICON, as your messages will already forward to your routed address.
• Log on to MYUI.
• Click on My UIowa / My Email / Email Account Filter bulk mail.
• Make sure that none of the categories are checked.

Required Graduate Assistants Teaching Courses:

• ONLINE CLASS Requirement: Sexual Harassment Prevention Edu.  Use your HawkID and password to log into Employee Self Service. Click the Personal tab, next (under Learning and Development) click on Sexual Harassment Prevention Edu., follow instructions.
• ONLINE CLASS Requirement:  Federal Educational Rights and Privacy Act (FERPA), Use your HawkID and password to log into Employee Self Service. Click the Personal tab, next (under Learning and Development) next click on Available Online Icon Courses, next FERPA Training, then click on View Details twice and the last click will be to Enroll in this ICON Course Session.
• A six-hour orientation program will be required of all students who are certified at level A or B and are teaching for the first time.  This orientation helps new teaching assistants understand the culture of the U.S. classroom and treats topics such as student expectations, teacher-student relationships, and understanding and answering student questions. Discussion focuses on suggestions for maximizing comprehensibility in spoken English. This course meets twice for 3 hours early in the semester. Both meetings are held in the evening.

Administrative Department Staff:

Professor aixin tan (until july 1, 2024).

Director of Graduate Studies, Statistics and Data Science Graduate Advisor: [email protected]   (319) 335-0821.

Professor Boxiang Wang (beginning July 1, 2024)

Director of Graduate Studies, Statistics and Data Science Graduate Advisor: [email protected] (319) 335-2294.

Professor N.D. Shyamalkumar

Actuarial Science Graduate Advisor:  [email protected]    (319) 335-1980

Margie Ebert

Academic Services Coordinator ,  [email protected]  (319) 335-2082

Heather Roth

Administrative Services Coordinator  [email protected]   (319) 335-0712

Tammy Siegel

Department Administrator ,  [email protected] , (319) 335-0706

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Applying to the AMS Graduate Program 

Master your future. transform tomorrow.  , master's application deadlines.

Spring 2024 Application Deadlines:

• For international applicants:  all applications are due by  October 17, 2023
• For domestic applicants:  all applications are due by  December 1, 2023

Fall 2024 Application Deadlines:

• For international students:  all online applications are due by May 5, 2024
• For domestic applicants:  all online applications are due by  June 1, 2024

Doctorate Application Deadlines

– For international students:

• For those who are applying for financial support, all applications are due by December 15, 2023  to receive full consideration
• For those who are not applying for financial support, all applications are due by May 5, 2024

–  For domestic applicants:

• For those who are applying for financial support, all applications are due by  December 15, 2023  to receive full consideration
• For those who are not applying for financial support, all applications are due by June 1, 2024

Application Requirements

For admission to the graduate program in Applied Mathematics and Statistics, the minimum requirements are as follows:    A.  A bachelor's degree in mathematics, a natural science, engineering, an applied science, or a social science with a strong mathematics  background. At the minimum for the master’s program application, students should be fluent in Linear Algebra and Multivariate Calculus (Calc. III).    B.  A minimum overall cumulative grade point average of at least 3.0, and at least a 3.0 average in all courses in pertinent or related fields. Attention will be given to math-related courses and GPAs as well.    C. For Fall 2024 applications, the Graduate Record Examination (GRE) General Test is NOT required. However, you are most welcome to submit your GRE score should you have it. Any GRE scores should be reported by ETS (Educational Testing System) to the Graduate School using institutional code 2548 and department code 0702 .    D.  An applicant who is not a native or primary speaker of English must present a minimum score for either the TOEFL or IELTS tests as follows:

TOEFL iBT: Overall score of 90 for doctoral applicants and 80 for master’s applicants.

IELTS: Overall score of 6.5, with no subsection recommended to be below 6.

TOEFL scores should be reported by ETS to the Graduate School using institutional code 2548. Official IELTS score reports must be mailed to our department directly. Applicants who have earned a degree from an English language university or college, where all instruction is in English, may be admitted without taking the TOEFL/IELTS tests.

  E .  Three letters of reference and all transcripts of undergraduate and/or graduate study completed.   F.  The applicants must indicate at least one of the five graduate tracks   on the supplement in the application form and may also select another area of specialization that they would consider if not admitted to the first track.    G.  Applicants with domestic credentials must submit an official transcript from each undergraduate  college or university attended,  regardless of whether a degree was conferred .  Applicants must also submit an official  transcript  from each college or university relating to graduate-level work,  regardless of whether a degree was conferred.  

Applicants with international credentials must submit an official English translation of all coursework showing a complete course-by-course record, GPA, degree, and institution, in addition to the original documents. SBU graduate admissions personnel will evaluate coursework, GPA, degree requirements, and institutional equivalence. In some instances where the coursework, degree equivalency, GPA, and/or institution cannot be verified, a course-by-course evaluation from one of Stony Brook University's approved  NACES  members listed below, may be requested from the applicant. 

• World Education Services (WES)
• International Education Evaluations, Inc. (IEE)
• Education Credential Evaluators (ICE)

Unofficial copies for both domestic and international credentials are acceptable for an admission decision to be made. If admitted, the applicant must submit final official  transcripts /evaluations sent directly from the college/university or evaluation agency as noted above. 

Application Procedure 

Please read this entire webpage before you apply. General application information can be obtained at the  Graduate School website   or one can go straight to the  application website .

Note that the application portal status page will give several options to upload additional documents after the application has been submitted. Select the “Personal Statement” option from the dropdown menu and upload your personal statement.

Application files are reviewed by the department's Graduate Admissions Committee. Upon the recommendation of the Admissions Committee, the Graduate Program Director will authorize an offer of admission to either our M.S. or Ph.D. program with an initial placement in one of the department's five graduate tracks. All students admitted to the doctoral program will automatically be considered for financial support if the application is submitted by the due date for financial support. M.S. students are not eligible for support.

Provisional Admission: Occasionally, students with marginal grades but signs of greater academic potential are offered provisional admission to our graduate program. Their admission offer will stipulate that they must take courses in their first semester and earn at least a B average in them. Upon satisfying these conditions, they will be allowed to matriculate into regular M.S. or Ph.D. student status.

Department Contact

We are here for you if you have any questions. In this special time, the best way to reach us is through emails  and we do check them very frequently.

Our Graduate Program Director is Professor David Green: [email protected]

Our Graduate Program Coordinator is Mrs. Christine Rota: [email protected]

If you have any academic questions, please, email to the graduate program director of the program you are applying for. Application paperwork questions, please, address Mrs. Christine Rota.

The 2021 QuantNet Ranking of Best Financial Engineering Programs  - provides detailed information regarding Quantitative Finance masters programs in the US. It includes placement and admission statistics from top programs in the country, making it uniquely valuable to the quant finance community at large.

• Course Schedule
• Stat Track Overview 2021
• Stat Trk Overview 20
• Stattrackoverview 2022

• Academics /

Data Analytics Graduate Certificate

Deepen your analytics knowledge to inform strategic business decisions.

Get Started

No Application Required

Online and On Campus Options

Number of Required Courses

What You'll Learn

• Learn to select, apply, and interpret appropriate statistical analyses and data mining methods for real-world data problems.
• Master programming skills for business analytics. Gain basic skills with information management tools and cloud databases to store, analyze, and extract business-relevant information.
• Use data visualization to understand and communicate data analyses and report data findings effectively to diverse audiences.
• Apply your knowledge and skills to real-world business challenges in advertising, sports, health, media and emerging technologies.

Our Community at a Glance

Along with your diverse peers, you’ll develop the skills to discover new insights that solve challenges for your organization.

Average Age

Working Full Time

Students Outside the U.S.

Average Time to Complete

Certificate Courses

The professional graduate certificate in data analytics requires four courses or 16 credits.

You may choose from the following course groups, using the certificate course search.

• Introductory course (you may select up to 1 course; however, intro courses are not required for this certificate)
• Required statistics course (choose one course from select group)
• Certificate elective courses (choose 2–3 courses from select group)

Courses taken before the 2018–19 academic year do not apply toward this certificate.

Search for Courses

You can browse courses by term — fall, spring, or summer — in the DCE Course Search & Registration platform.

Upcoming Term: Summer 2024

Summer course registration is open through June 20. Learn more about how to register →

Fall 2024 courses and registration details will be live in June.

Earning Your Certificate

To meet the requirements for the certificate, you must:

• Complete the  four certificate courses for graduate credit .
• Earn at least a  B grade  in each course.
• Complete the courses within three years .

Learn more about  pursuing a certificate  and the process of  requesting your certificate .

Prerequisite Knowledge

Introductory statistics is recommended. Some courses require calculus and linear algebra. Business experience is a plus.

If you have a solid foundation in statistics, you may take an additional data analytics elective (for a total of three) in place of the introductory course option. If you have a limited statistical background, you should begin with an introductory course.

Affordability is core to our mission. When compared to our continuing education peers, it’s a fraction of the cost.

This graduate certificate stacks to the following degrees:

• Finance Master’s Degree Program
• Systems Engineering Master’s Degree Program

Harvard Division of Continuing Education

The Division of Continuing Education (DCE) at Harvard University is dedicated to bringing rigorous academics and innovative teaching capabilities to those seeking to improve their lives through education. We make Harvard education accessible to lifelong learners from high school to retirement.

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• Biomedical Sciences

Ph.D. Program

Students entering through the Integrated Biomedical Sciences program have the opportunity to study with research faculty from the School of Medicine and across USC.

All of our Ph.D. students enter through the Integrated Biomedical Sciences program that includes primary core courses and research rotations that allow you to decide the exact research you want to conduct.

Research Areas and Faculty Mentors

Choosing your research mentor and research area will be two of the biggest decisions you will make during your Ph.D. program. While we encourage you to have an idea of who you would like to work with before you apply, we also give you the opportunity to explore all your options. 

Admission and Application

Admission into our program is on a rolling basis with submissions opening in the Fall semester and decisions being made in the Spring semester.

Tuition and Financial Aid

Tuition and financial aid information for students applying to and entering the Biomedical Sciences Ph.D. program.

PREP Program

USC PREP seeks to increase the number of applicants to biomedical graduate programs from under-represented communities by offering the opportunity to work for a year in a biomedical research laboratory while preparing for graduate school in the biomedical sciences.

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Educational Programs

News & events, epidemiology, phd student profiles, alexander furuya.

• [email protected]

I am a Columbia University graduate student pursuing a PhD in Epidemiology at the Mailman School of Public Health. I have an extensive background in data analysis, statistical programming, and public health research. My goal is to understand social determinants of health among those in the LGBTQ+ community and immigrant communities, and I hope to identify effective interventions to improve health.

I currently work with Dr. Dustin Duncan in analyzing data form the Trying to Understand Relationships, Networks and Neighborhoods in Trans women of color (TURNNT) Cohort. Specifically, I am looking into determinants of HIV prevention and treatment and identifying factors that affect them.

Research Interests

• Social Epidemiology
• LGBTQ+ Health
• Health of the Aging Community
• Intervention Science
• HIV Treatment and Prevention
• Biostatistical Methodologies
• Chronic Disease Epidemiology
• [email protected]

I am a first year doctoral student, first year fellow on the Global HIV Implementation Science Research Training Fellowship with ICAP, and an infectious disease epidemiologist. I received a BS in Biological Sciences from the University of Michigan-Dearborn in 2014, an MPH in Epidemiological Methods and Applications from the University of Michigan in 2016, and prior to coming to Columbia, spent about seven years at the San Francisco Department of Public Health in the HIV Epidemiology Section. My research interests are centered around infectious disease prevention and treatment interventions, and I have past work pertaining to HIV care navigation, hepatitis C treatment, mpox vaccination, and COVID-19 coinfection among people with HIV. Apart from my role as an analyst, as a database administrator and developer, I designed, carried out, and evaluated a surveillance system modernization project to increase the accuracy, timeliness, and accessibility of HIV test results for department case investigators and outreach staff. My current projects relate to PrEP demand creation among women in South Africa and HIV care retention patterns in Côte d'Ivoire.

• Infectious Disease
• Health Interventions
• Implementation Science
• Global Health

Hoisum Nguyen

• [email protected]

Inspired by the stories of immigrants and social justice movements in the United States, Hoisum's research centralizes psychiatric and mental health outcomes with a particular focus on trauma and violence as it relates to firearms, racial/ethnic populations, LGBQIA+ communities, and financial means. Equipped with a Master’s in Public Health (MPH, Class of 2020) from Boston University in Epidemiology and Biostatistics, prior training in causal theories from UCLA (2021-2023), and previous work in suicide outcomes and emergency preparedness during the COVID-19 pandemic for the county of Santa Clara, CA (2020-2022), Hoisum aims to create research of consequence for policy formulation.

Hoisum is currently a Doctoral Candidate in Epidemiology, a pre-doctoral fellow in Psychiatric Epidemiology Training Fellow (PET-T32), and also a Robert Wood Johnson Health Policy Research Scholar (HPRS) receiving health policy and leadership training from Johns Hopkins University (Class of 2026).

• Mental and Psychiatric Health
• Violence and Trauma Epidemiology
• Firearms Violence
• Health Equity and Social Disparities
• Racial/Ethnic Community Health
• Health Policy

Adam Whalen

• [email protected]

I am a first-year pre-doctoral candidate in Epidemiology and a pre-doctoral fellow in the Advanced Training in Environmental Health and Data Science Training Program, jointly managed through the Department of Epidemiology and the Environmental Health Sciences Department. I received my BS in Biology and Public Health Science in 2015 from Santa Clara University, and my MPH in Epidemiology with a Certificate in Applied Biostatistics and Public Health Data Science from the Columbia University Mailman School of Public Health in 2021. Previously, I worked as a data analyst at the Department of Epidemiology and Population Health at the Albert Einstein College of Medicine, working on research projects related to Hispanic/Latino health as well as women living with HIV. As a member of the Spatial Epidemiology Lab at Columbia, my current research investigates how discrimination against transgender women of color and sexual minority men affects health outcomes. I also examine activity space exposure to different features of the bult and social environment and how they influence criminal legal system involvement, sleep, access to gender-affirming health care, and other outcomes. My research interests include social and spatial epidemiology, novel spatiotemporal methods including GPS-based activity space analysis and geofencing applications, injury and violence outcomes such as transportation and police violence, and sexual and gender minority health.

• Spatial Methods
• Injury/Violence
• Transportation
• Police violence
• Sexual and Gender Minority Health

Erin M. Annunziato

• [email protected]

I am a pre-doctoral fellow in the Substance Abuse Epidemiology T32 Training Program. I am interested in structural-level determinants contributing to substance use-related harms, including racial and ethnic disparities in substance use treatment and drug-related legal outcomes. My current research examines relationships between 1) state policies, such as drug monitoring programs, and legal outcomes, and 2) racial and ethnic disparities in substance use treatment access through the criminal legal system. I have a BS in Biology from Boston College and an MPH in Epidemiology from the Mailman School of Public Health.

• Drug policy
• Drug criminalization
• Racial and ethnic disparities
• Social epidemiology
• [email protected]
• Google Scholar

I am a second year pre-doctoral candidate in Epidemiology and a second year pre-doctoral fellow in the Advanced Training in Environmental Health and Data Science Training Program, jointly managed through the Department of Epidemiology and the Environmental Health Sciences Department. I earned a BS in Biology from Brooklyn College (CUNY) in 2019, and an MPH in Epidemiology with an Advanced Certificate in Public Health and Humanitarian Action from the Columbia University Mailman School of Public Health in 2021. Previously, I served as a clinical research coordinator at the NYU Grossman School of Medicine, Department of Neurology, where I managed all aspects of research and administration for the Stroke Division. My previous research has focused on a range of mental, neurological, and substance use issues in humanitarian settings. As a doctoral student, my research efforts are focused on evaluating neurodevelopmental outcomes amidst the complex landscape of mental health and substance use among adolescents and their caregivers in diverse conflict-affected settings. My research interests include global mental health, substance use epidemiology, child development, and disability advocacy. 

• Global Mental Health
• Substance Use Epidemiology
• Child Development
• Disability Advocacy

Nicole Itzkowitz

• [email protected]

I am a 2nd year PhD student in the Department of Epidemiology and a pre-doctoral fellow in the Advanced Training in Environmental Health and Data Science T32 Training Program. I entered the program in 2022 with an MSc in epidemiology from The London School of Hygiene and Tropical Medicine and a BA in public health from the University of Rochester. My research interests are broadly concerned with quantifying urban environmental and built environment exposures and exploring their relationship with injury and other non-communicable disease outcomes. My previous work at Imperial College focused on examining the causal relationship between acute noise pollution exposure and cardiovascular disease hospitalizations and creating a composite metric to estimate smoking behavior at small spatial resolutions. I am currently working with Dr. Andrew Rundle and the Built Environment and Health research group on several projects related to pedestrian and micromobility injuries and fatalities in the context of the built environment and alcohol use.

• Environmental Exposures
• Built Environment
• Non-communicable Disease 

College of Education

• Graduate Program

Educational Psychology - M.Ed.

Program overview.

Educational Psychology is an academic program in the Department of Educational Psychology, Leadership, & Counseling. The program equips students with a comprehensive knowledge of learning, motivation, development, and educational foundations. Additionally, students learn to apply quantitative and qualitative research skills in a manner that promotes educational improvement while valuing individual differences. Thus, educational psychology attracts students from various educational and professional backgrounds including education, psychology, human sciences, business, sports sciences, and health sciences.

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Program work within Educational Psychology is developed and guided by a strong conceptual framework, the standards from the National Council for the Accreditation of Teacher Education (NCATE), guidelines from the American Psychological Association (APA), American Educational Research Association (AERA), and National Association of School Psychologists (NASP) and the sound professional judgment of an experienced and caring faculty.

The master's program is designed to provide students with content knowledge that facilitates the application of research in educational psychology to educational settings. Teachers are especially encouraged to select the applied master's degree plan that is designed to prepare highly effective, culturally sensitive educators.

Degrees Offered

M.Ed., offered as a face-to-face or hybrid program.

Career Opportunities With This Degree

Most graduates teach in colleges or universities or are in positions conducting research.

Application Materials

College Transcripts – Unofficial transcripts can be uploaded to the Graduate School application . Information on submitting official transcripts will be provided to you by the Graduate School. Grade reports or unofficial transcripts from university web portals will not be accepted. Please redact the Social Security Number anywhere it appears on your transcript. If documents are written in a language other than English, a copy of a complete and official English translation must be provided with the original language records.

Required Supplemental Application Materials

GRE Scores, Resume, Three Professional Recommendations, Academic Writing Sample, Response to Applicant Statement Prompt. Download a comprehensive list of requirements.

Application Process

Please visit the Graduate Application Process for more information on how to apply.

This program requires official GRE scores. Scores must no more than 5 years old at the time of application. Official GRE scores must be sent from Educational Testing Services (ETS) to the Texas Tech Graduate School. To register for the examination please visit the GRE Testing website . Texas Tech University's code is 6827.

• Due to ongoing accessibility concerns, the Graduate School has suspended GRE test score requirements for applications through at least Summer 2025. For more information, please contact the Graduate School .

Semester in which the program can be started

It is recommended that students start in the fall but applications will be considered on a rolling basis.

Estimated Hours to Completion

45 credit hours

Allowable Transfer Hours

6 credit hours if completed in the last 7 years with a grade of B or better.

Financial Aid

TTU Graduate School and COE scholarships, research assistantships, student loans

To be competitive for funding support, the recommended deadline for Fall is December 1 st . However, applications received at other times will be reviewed.

Tuition & Fees

Use the Student Business Services Tuition Estimator to estimate your costs.

Chance Webb Academic Advisor/Admissions Office of Graduate Admissions & Enrollment [email protected] 806-834-6768

Research, Evaluation, Measurement, and Statistics

Educational psychology and foundations, school psychology.

• Delivery : Face-to-Face or Hybrid
• Hours to Completion: 45
• Now accepting applications for: All Semesters
• Maximum Transfer Hours: 6

Contact TTU

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