General Statement

The Mathematical Statistics Program offers M.A. and Ph.D. degrees in statistics and probability theory with areas of faculty specialization including stochastic processes, statistical decision theory, biostatistics, stochastic modeling, nonparametric inference, multivariate analysis, categorical data, time series analysis and large sample theory. Students may pursue a program of study emphasizing either theory or applications by appropriate choice of coursework and research topics. The program has been designed with sufficient flexibility to accommodate the student's background and interests.

Academic matters relating to the Mathematical Statistics Program are determined by the Statistics faculty of the Mathematics Department. The Department administers graduate programs in Mathematics (MATH) and Mathematical Statistics (STAT), and also cooperates with the program in Applied Mathematics and Scientific Computation (AMSC). Administrative support for all three programs is provided by the Department's Office of Graduate Studies. In particular, all teaching assistantships and most fellowships for students in the three programs are handled by the Mathematics Graduate Office.

During the first year a graduate student has the privilege of transferring among the three related graduate programs of MATH, STAT, and AMSC. After the first year, switching between programs is possible but not automatic, and requires approval of the programs involved.

Some general regulations of the Graduate School are listed in this brochure as well as specific policies of the Department. These policies should be carefully considered by all graduate students in planning their work towards an advanced degree. Additional information is available in the Office of Graduate Studies and in such publications as the Graduate Catalog and the Schedule of Classes.


Advising, Registration and Maintenance of Graduate Standing

Every student is expected to meet with an advisor each semester. Upon admission new students should follow the advising directions of the Departmental letter of admission (except those who will be graduate teaching assistants). The new teaching assistants complete advising and registration during the one week mandatory orientation program that takes place in August, the week before the start of classes. For currently enrolled students, registration takes place either electronically or through the Office of Graduate Studies every fall and spring for the following semester.

All Statistics Program faculty members can advise graduate students on their program and selection of courses. However, for the purpose of coordination and course planning it is expected that graduate students in Statistics will consult with the Statistics Program Director about their plans for immediate course selection and expected registration for following semesters. New graduate students will usually be advised by the Statistics Program Director.

The advisor and the student work together to formulate the appropriate course of study. The program should combine core material in statistics and probability, supporting material in mathematics and/or areas of application of statistics, and more specialized study in areas of particular interest to the student. There are no specific course requirements. However, a narrow, over-specialized program is undesirable, since statisticians must be able to apply their knowledge to a variety of problems and must have a wide range of skills at their disposal. The program is subject to the approval of the Director of the Statistics Program.

Core Courses: All students should plan to take STAT 650 and STAT 700-701. In addition, those with a weak background in probability and statistics should take STAT 410 in their first semester at Maryland.

M.A.--Thesis Option: In addition to the core courses, students elect other courses in statistics, mathematics or areas of application. This enables the student to set up an individualized program of study in applied statistics, mathematical statistics or applied probability. The student should plan on beginning thesis research in the second year.

M.A.--Non Thesis Option: These students take the departmental written comprehensive examination in statistics, probability, and a third area of statistics or mathematics. The program of study should include the core courses, a course sequence for the third part of the written examination, and other courses in statistics, mathematics or applied areas to complete the program. In addition, candidates choosing the non-thesis option for the M.A. must prepare a scholarly paper.

Ph.D.-- The doctoral student's program usually includes STAT 600-601-650, STAT 700-701 and a mathematics sequence. This is the core material for the three part Ph.D. written examination. In addition, doctoral students should plan on taking some more advanced courses, usually at least some subset of STAT 740-741 (Linear Statistical Models), STAT 710 (Advanced Statistics), and STAT 750 (Multivariate Analysis). Advanced students often take independent reading courses in their areas of research in addition to or instead of formal course work. Participation in the probability and statistics seminar and statistics workshop is required of all who plan to write a Ph.D. dissertation. In addition, these students must give a presentation in some area of current research in the field.

Any course may be repeated and the grade in the repeated course replaces the original grade in determining the overall average. As long as the overall average is at least B at the time of receiving the degree, grades of D, F and I may stand, but D and F count as 0 quality points in computing averages, and courses in which these grades are received cannot be used to fulfill degree requirements.

The Schedule of Classes should be consulted for pertinent dates for adding and dropping classes.

A full time graduate student must carry a combination of courses that adds up to at least 48 units each semester (excluding the summer sessions). For graduate assistants this requirement is reduced to a minimum of 24 units. A unit is defined as follows:

All 400 level courses: 4 units per credit hour.

All 600/700 level courses: 6 units per credit hour (except 799) 799: 12 units per credit hour 899: 18 units per credit hour

Each professor has an individual section number for a reading or research course. This section number is available in the Office of Graduate Studies. Students registering for an RIT (STAT 689), a reading course (STAT 698 or 798) or any 799/899 course should obtain the correct section number from that office.

Students are expected to make steady progress toward their degrees. For the M.A. degree, all requirements must be completed within five years from the date of admission. A student admitted to a Ph.D. program must be admitted to candidacy within five years from the date of admission. After admission to candidacy all requirements for the Ph.D. degree must be completed within four additional years. Minimal continuous registration is required of all students who have been admitted to candidacy for the Ph.D. degree.


Graduate Student Financial Support

Graduate teaching assistantships constitute the main form of financial aid offered by the Department. In addition to a stipend, graduate assistants receive a tuition scholarship for up to ten credits per semester and are eligible for health care benefits. See here for further information on duties of graduate assistants and renewal policies for fellowships and assistantships.


The Degree of Master of Arts

A student who receives a Master's degree in Mathematical Statistics should demonstrate a general understanding of the main branches of the subject and must have shown a high level of scholarship and ability. Two options are available for this degree: the M.A. with thesis and the M.A. without thesis. 

REQUIREMENTS APPLICABLE TO ALL M.A. STUDENTS

Residence Requirements: A full-time student must have two semesters in residence, a part-time student four semesters. All requirements for the M.A. degree must be completed within a period of five years.

Transfer of Credit: Up to 6 credits of graduate level work taken at another regionally accredited institution is permitted under the following provisions:

    (1) The faculty advisor and Program Director agree that the specific credits are acceptable in the student's program.
    (2) The grade of B or better was earned in the course offered. No courses with pass/fail grades will be accepted.
    (3) The credit was earned within the five year limit imposed for completing the Master's degree at the University of Maryland.
    (4) The course received graduate credit at the institution where it was taken, and has not been used to meet the requirements for any degree previously earned.

Diploma Application: Applications for Diploma should be made at the Records Office, Room 1101, Mitchell Building, early in the semester in which the degree is expected. The deadline for application is listed in the Schedule of Classes.

Approved Program Form: A student who has applied for a diploma must complete the Approved Program form obtained from the Office of Graduate Studies before the deadline listed in the Schedule of Classes. This form is returned to the Administrator of the Graduate Program who will forward it to the Graduate School.

Grade Point Average: The student must maintain an average of B or better in all courses taken, not just those listed in the Approved Program. For this purpose, the grades of D, F, and I count as 0 quality points, and courses with these grades cannot be used for degree requirements.

Incomplete: Any grade of incomplete in a course listed in the Approved Program must be removed. 

MINIMUM REQUIREMENTS FOR M.A. WITH THESIS

In addition to satisfying the requirements applicable to all M.A. candidates, the student must have:

    (1) taken a total of 24 hours of courses carrying graduate credit of which at least 15 are at the 600/700 level and at least 12 hours are at the 600/700 level in statistics and probability (STAT);
    (2) taken 6 hours of STAT 799 (Research) in addition to requirement (1);
    (3) written a satisfactory thesis;
    (4) passed a final oral examination.

Thesis: The M.A. thesis should represent a meaningful piece of independent work which has some novel features, for example, the detailed working out of the application of a general theory or method to some particular case or cases of interest. It must be prepared in the form required by the Graduate School. Each member of the final oral committee must receive a legible typed copy at least one week before the final oral examination. Two copies of the thesis must be delivered to the Graduate School after the final oral examination and before the deadline specified in the Schedule of Classes.

Nomination of Thesis or Dissertation Committee Form: This form, obtained from the Office of Graduate Studies, must be completed two months prior to the date of the final oral and in keeping with the deadline listed in the Schedule of Classes. It should be completed in conjunction with the student's thesis advisor and returned to the Administrator of the Graduate Program who will forward it to the Graduate School. This will generate the Report of Examining Committee form sent from the Graduate School to the Statistics Director to be taken to the final oral examination. It should be signed by all members of the thesis committee and returned to the Graduate School. There is also an equivalent internal form. The student will be examined on the thesis and related topics at the discretion of the examiners. All pertinent information concerning this oral examination should be given to the Office of Graduate Studies two weeks prior to the examination. The information will then be posted, as the examination is open to the public.

MINIMUM REQUIREMENTS FOR THE M.A. WITHOUT THESIS

In addition to satisfying the requirements applicable to all M.A. candidates, the student must have:

    (1) taken a total of 30 hours of courses carrying graduate credit of which at least 18 are at the 600/700 level and not less than 12 hours are at the 600/700 level in statistics and probability (STAT);
    (2) passed 3 Master's written examinations or the Ph.D. written examinations at the Master's level;
    (3) written a satisfactory scholarly paper;
    (4) passed a final oral examination.

Scholarly paper: The student must complete an acceptable scholarly paper of an expository nature. Normally, the topic shall be related to an advanced course or seminar taken in partial fulfillment of the course requirements for the degree. The topic shall normally be agreed upon with the professor in the course, who shall become the student's advisor. If the paper is not written in connection with a course, some other appropriate faculty member may approve the topic and become the advisor. A second reader shall be appointed by the Statistics Program Director and both readers must approve in order for the paper to be accepted. A neat copy of the final approved version shall be provided for the Office of Graduate Studies files. The scholarly paper shall be based on substantial use of at least two sources, including one journal article. The paper must include an abstract and references to all literature used.

Final Oral Examination: The final oral examination shall consist of a presentation of the material in the scholarly paper, plus questioning by the examiners based on the paper and whatever material in the approved M.A. program that has not been covered by the written examination. The examining committee shall consist of the two readers of the scholarly paper.


The Degree of Doctor of Philosophy

To receive the Ph.D. degree in mathematical statistics a student must display a high level of scholarship shown by the ability to do original research and should possess a broad knowledge of major fields of the subject. It is not necessary to obtain a master's degree before obtaining the doctorate.

Residence Requirements: The equivalent of at least three full years of graduate study is required, of which at least one must be in residence at the University of Maryland campus. At least 18 hours of course work must be taken at the University of Maryland, plus 12 hours of research at the Ph.D. level.

Minimum Requirements: In order to receive a Ph.D. degree, the student must have:

    (1) taken at least 30 hours of formal course work (at least 27 at the 600/700 level) with an average of B or better. Courses used as part of a Master's program may be used in fulfillment of this requirement. At least 18 hours must be taken in statistics and probability (STAT). Grades D, F, and I count as 0 quality points, and courses in which they are obtained cannot be used to fulfill degree requirements;
    (2) taken at least 12 hours of STAT 899 (Research);
    (3) passed the written examination in three fields at the Ph.D. level, including probability and mathematical statistics parts;
    (4)  given an acceptable Doctoral Candidate's Presentation in an area of current research;
    (5)  Participated in the probability and statistics seminar and statistics workshop. This participation will be checked and enforced by the thesis advisor;
    (6) been admitted to candidacy no later than the year previous to the one in which the degree is granted;
    (7) prepared a dissertation representing an original contribution to existing knowledge of mathematical statistics or probability;
    (8) passed the final oral examination.

Doctoral Candidate's Presentation: As a condition for Ph.D. candidacy, the student must make an oral presentation in an area of current research. The level of the presentation should demonstrate depth of knowledge, familiarity with research literature, and ability to write a doctoral dissertation on a topic related to the subject of the presentation. The subject matter will be determined by the student with the help of his prospective thesis advisor. An examining committee of three statistics faculty members is appointed by the Program Director. At the conclusion of the presentation, the committee judges the presentation as acceptable or unacceptable. The committee may question the student on other material, if they deem such questioning necessary to reach a judgement.

Approved Program: The entire course of study must constitute a unified program, approved by an advisor in the field of the student's major interest and by the Program Director.

Admission To Candidacy: Before petitioning for admission to candidacy, a student must have:

    (1) completed half of the residence requirements;
    (2) maintained a B average in his or her formal course work;
    (3) passed the written examinations at the Ph.D. level;
    (4) given an acceptable Doctoral Candidate's Presentation;
    (5) obtained the consent of a faculty member who will accept the responsibility of directing a dissertation.

After fulfilling these requirements, the student should complete the Admission to Candidacy form available in the Office of Graduate Studies. This will be forwarded to the Graduate School.Dissertation: The dissertation must represent an original contribution to existing knowledge in mathematical statistics or probability. It must follow the form given in the manual which is available at the Copy Center at Reckord Armory. Two copies of the dissertation, three copies of the abstract, and two title pages must be submitted to the Graduate School on the proper paper as stated in the manual. The copies must be submitted to the Graduate School Records Office, after the Final Oral Examination but before the deadline listed in the Graduate School's Calendar of Important Dates. It is expected that the dissertation or some modification thereof will be submitted to a statistical, mathematical or scientific journal for publication.

Final Oral Examination: The final oral examining committee must consist of five members, one of whom is a regular member of the graduate faculty of a department other than mathematics. Each member of the committee must be given a copy of the dissertation at least two weeks prior to the examination.

The Nomination of Thesis or Dissertation Committee form is obtained from the Office of Graduate Studies and must be completed and returned to that office three months prior to the final oral and in accordance with the deadline listed in the Schedule of Classes. Details governing the structure of the committee are on the back of this form. This will generate the Report of Examining Committee form sent from the Graduate School to the Statistics Director which must be taken to the final oral, signed by all members of the committee and returned to the Graduate School. There is also an equivalent internal form.

All pertinent information concerning the oral examination should be given to the Office of Graduate Studies two weeks prior to the examination. The information will then be posted as this examination is open to the public.

The final oral examining committee will examine the candidate on the research work incorporated in the dissertation, review attainments and then vote on the candidate's qualifications for the degree. In order to justify a finding of failure, at least two negative votes must be cast.


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  • Predictive Science and Deep Learning - A Bright Future or an Odd Couple?

    Speaker: Wolfgang Dahmen (Aachen, University of South Carolina) - https://sc.edu/study/colleges_schools/artsandsciences/mathematics/our_people/directory/dahmen_wolfgang.php

    When: Wed, September 20, 2023 - 3:15pm
    Where: Kirwan Hall 3206
  • The optimal paper Moebius band

    Speaker: Richard Schwartz (Brown University) - https://www.math.brown.edu/reschwar/

    When: Fri, September 29, 2023 - 3:15pm
    Where: Kirwan Hall 3206
  • Riehl (TBA)

    Speaker: Emily Riehl (Johns Hopkins University) - https://math.jhu.edu/~eriehl/

    When: Fri, October 6, 2023 - 3:15pm
    Where: Kirwan Hall 3206
  • Categorification and geometry

    Speaker: Lars Hesselholt (Nagoya University) - https://www.math.nagoya-u.ac.jp/~larsh/

    When: Fri, October 13, 2023 - 3:15pm
    Where: Kirwan Hall 3206
  • Mathematics Around the Heisenberg Group

    Speaker: Roger Howe (Yale University) - https://www.norbertwiener.umd.edu/fft/2023/Speakers/Roger_Howe.html

    When: Thu, October 26, 2023 - 3:45pm
    Where: Kirwan Hall 3206
  • Decoding Time's Mysteries for Better Predictions

    Speaker: James Howard (Johns Hopkins University) - https://www.norbertwiener.umd.edu/fft/2023/Speakers/James_Howard.html

    When: Thu, October 26, 2023 - 6:45pm
    Where: Kirwan Hall 3206
  • A tale of two invariants

    Speaker: Paul Feehan (Rutgers) - https://sites.math.rutgers.edu/~feehan/

    When: Wed, November 15, 2023 - 3:15pm
    Where: Kirwan Hall 3206
  • Using logic to study homeomorphism groups

    Speaker: Thomas Koberda (University of Virginia) - https://sites.google.com/view/koberdat

    When: Wed, November 29, 2023 - 3:15pm
    Where: Kirwan Hall 3206
  • Generative Models for Implicit Distribution Estimation: a Statistical Perspective

    Speaker: Yun Yang (University of Illinois Urbana-Champaign) - https://sites.google.com/site/yunyangstat/

    When: Thu, January 25, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Video Imputation and Prediction Methods with Applications in Space Weather

    Speaker: Yang Chen (University of Michigan) - https://yangchenfunstatistics.github.io/yangchen.github.io/

    When: Tue, January 30, 2024 - 4:00pm
    Where: Kirwan Hall 3206
  • Arboreal Galois groups: an introduction

    Speaker: Robert Benedetto (Amherst College) - https://rlbenedetto.people.amherst.edu/

    When: Wed, February 7, 2024 - 3:15pm
    Where: Kirwan Hall 3206
  • Higher theta series

    Speaker: Zhiwei Yun (MIT) - https://math.mit.edu/~zyun/

    When: Wed, February 28, 2024 - 3:15pm
    Where: Kirwan Hall 3206
  • Random lattices and their applications in number theory, geometry and statistical mechanics

    Speaker: Jens Marklof (School of Mathematics, University of Bristol) - https://www.bristol.ac.uk/people/person/Jens-Marklof-6eb63e14-a018-4833-9cf8-b95272b5a09e/

    When: Fri, March 1, 2024 - 3:15pm
    Where: Kirwan Hall 3206
  • TBA

    Speaker: Svetlana Jitomirskaya (University of California, Berkeley) - https://math.berkeley.edu/people/faculty/svetlana-jitomirskaya

    When: Thu, March 14, 2024 - 3:00pm
    Where: Kirwan Hall 3206
  • Instantaneous everywhere-blowup of parabolic stochastic PDEs

    Speaker: Davar Khoshnevisan (University of Utah) - http://www.math.utah.edu/~davar/

    When: Wed, April 3, 2024 - 3:15pm
    Where: Kirwan Hall 3206