Graduate Degree Programs & Requirements

For general Wash U Arts and Sciences Graduate School Admission information, please visit the Office of Graduate Studies page.

The Office of Graduate Studies also has general information about the application process.

In addition to the general Office of Graduate Studies requirements for application, there are department and program specific requirements/procedures as well. This information is detailed below for each Statistics and Data Science program.

The Office of Graduate Studies in Arts & Sciences has an accelerated BA/Master's program in which highly qualified undergraduate majors can earn both the BA and MA degrees with two additional semesters of work (usually a total of five years). The MA degree is in Statistics.

Participants can count up to 15 units of 400-/500-level coursework earned during the four years of undergraduate study (with grades of B or better) toward the MA course requirements. Counting these 15 units makes it possible to finish the master's requirements in one additional year, but the program is still fast-paced and requires a lot of intense work and some careful planning. SDS expects applicants to have backgrounds comparable to the students admitted to the regular MA program.

This program is only for Washington University undergraduates who, if they participate, must do so in the academic year immediately following graduation (no deferments). According to the Office of Graduate Studies in Arts & Sciences, eligibility requires having completed the BA degree from Arts & Sciences (which would rule out, for example, a second major whose degree is from the McKelvey School of Engineering).

There are 36 units of course work required and an optional thesis; 3 units may be for thesis research. The minimum residence requirement is one full academic year of graduate study. A GPA of B (3.0) or better must be maintained in the graduate courses.

Optional thesis requirements: To be eligible for the thesis option, a student must maintain a cumulative GPA of 3.5 or higher in the first 18 units of courses satisfying the program requirements.

The program allows participants to count up to 15 units of 400-/500-level course work earned during the four years of undergraduate study (with grades of B or better) toward the MA course requirements. (The point of the 15-unit limit is to avoid having majors push so much specialized work into the BA years that they limit their opportunities to do the exploration outside of the major that an undergraduate should do.) Counting these 15 units makes it possible to finish the master's requirements in one additional year, but the program is still fast-paced and requires a lot of intense work and careful planning.

Careful course selection throughout the undergraduate program is required. Usually, the department will not recommend that the Office of Graduate Studies, Arts & Sciences, admit a major to this program unless the 15 applicable units of 400-/500-level work will be completed by the time of graduation. In addition, the department expects applicants to have backgrounds comparable to students admitted to the regular master's programs.

For specific course requirements, please view the Bulletin.

Interested majors should consult with the Director of the Master's Program (SDSMastersDirector@wustl.edu) at the beginning of the Fall semester of their senior year, before the add/drop deadline, to ensure that all necessary courses will be taken during the students senior year.

To apply for the Accelerated BA/MA in Statistics, please visit our Graduate Application page. The deadline to apply for the Accelerated BA/MA in Statistics is March 1st. \

Please note: On the application, in the section titled “Additional Applicant Information” you must select "Current WashU undergraduate student" under the Washington University Affiliation question. You will then be asked to provide your student ID number so that we can confirm you are a current undergraduate student. In the section titled “Program Information”, the option “Bachelor’s/Master’s Program” will then appear under Intended Level of Study.

International Students:
For students in the United States on a visa as undergraduates, staying on to complete an MA creates a change in visa status, which will involve reapplication paperwork. Interested students should check on the details with an international student advisor at the Office for International Students and Scholars website.

The MA in Statistics is available to all qualified students from any field. Master's students in The Statistics and Data Science Department are expected to be self-funded. These programs provide students with the analytical background needed to prepare them for diverse careers, from positions in government and business to further PhD studies. 

Our program encourages practical training experiences, such as internships off campus or research opportunities on campus, which students can pursue based on availability and their own initiative. 

The regular MA in Statistics consists of 36 units of course work to be completed in three to four semesters and an optional thesis; 3 units may be for thesis research. The minimum residence requirement is one full academic year of graduate study. A GPA of B (3.0) or better must be maintained in graduate courses.

After completing a well-designed and judiciously chosen set of core courses (currently six), MA students can choose from a wide range of electives that includes several courses from other departments. MA students can also challenge themselves to take the more advanced Statistics PhD qualifier courses to prepare them for further PhD programs upon graduation. High-achieving students may also choose to complete a masterʼs thesis.

Typically, at most three electives shall be chosen from outside the SDS Department. If not taken before, a course in Python or R programming is strongly recommended to build essential programming skills widely used in data analysis and statistics. However, if the course is below the 500-level, it cannot be included among the courses used to satisfy the 36 units requirement.

For more information, please view the Bulletin page.

All 5000-level SDS classes are eligible electives.

SDS 5061-62 Theory of Statistics I / II

SDS 5070 Stochastic Processes

SDS 5072 Advanced Linear Models II  

SDS 5111 Experimental Design

SDS 5120 Survival Analysis

SDS 5140 Advanced Linear Statistical Models

SDS 5155 Time Series Analysis

SDS 5430 Statistical Learning

SDS 5440 Mathematical Foundations of Data Science

SDS 5510 Advanced Probability I  

SDS 5511 Advanced Probability II  

SDS 5531 Advanced Statistical Computing I  

SDS 5532 Advanced Statistical Computing II  

Advanced Topics Courses:

SDS 5480

SDS 5481

SDS 5571

SDS 5595

SDS 5800

SDS 5801/5802

SDS 5805

MATH 5151 Measure Theory and Functional Analysis I  

MATH 5152 Measure Theory and Functional Analysis II

MATH 5011 Introduction to Analysis

MATH 5012 Introduction to Lebesgue Integration

MATH 5031 Linear Algebra  

MATH 5051 Numerical Applied Mathematics

MATH 5056 Topics in Financial Mathematics  

FIN 5380 Stochastic Foundations for Finance (1.5 credits)  

FIN 5390 Mathematical Finance (1.5 credits)  

DAT 5561 Introduction to Python and Data Science  

DAT 5550 Machine Learning Tools for Prediction of Business Outcome

BIOL 5181 Population Genetics  

BIOL 5483 Human Genetic Analysis  

BIOL 5495 Computational Molecular Biology  

CSE 4107 Introduction to Machine Learning

CSE 5100 Deep Reinforcement Learning  

CSE 5104 Data Mining  

CSE 5105 Bayesian Methods in Machine Learning  

CSE 5107 Machine Learning  

CSE 5109 Advanced Machine Learning  

CSE 5270 Natural Language Processing  

CSE 5610 Large Language Models  

ECON 5141 Advanced Microeconometrics

ECON 8111 Quantitative Methods in Economics II  

ECON 8151 Advanced Theoretical Econometrics  

ECON 8110 Applied Econometrics  

ECON 8130 Structural Microeconometrics  

ESE 522 Random Variables and Stochastic Processes II  

ESE 5291 Special Topics in Information Science & Learning: Statistical Foundations of High-dimensional Information Processing

ESE 5450 Stochastic Control

INFO 5558 Applications of Deep Neural Networks

To be eligible for the thesis option, a student must maintain a cumulative GPA of 3.5 or higher in the first 18 units of courses satisfying the program requirements.

General requirements: This program is a tailored masterʼs degree in statistics for graduate students in political science. Note that, while the program is designed to serve political science graduate students, it is run by the Department of Statistics and Data Science. Students interested in this program will need to begin their additional course work during their third year of study (or before). Students are encouraged to apply for the program in their third year, but they may prefer to try the additional courses first.

Requirements for admission:
• To be eligible for this program, students must have already passed Pol Sci 5052 Mathematical Modeling in Political Science, Pol Sci 581 Quantitative Political Methodology I, and Pol Sci 582 Quantitative Political Methodology II and earned a grade of A- or A in these courses. Although exceptions have been made in the grade requirements at the request of political science faculty, this decision is up to the Department of Statistics and Data Science.
• Students must obtain permission from the methodology field committee in the Department of Political Science.
• Students must formally apply to the Department of Statistics and Data Science Master of Arts program.

Thesis: To be eligible for the thesis option, a student must maintain a cumulative grade point average of 3.5 or above in the first two semesters (or 18 units) of course work satisfying the program requirements. A maximum of 3 units may be used for thesis research. The thesis must be supervised by faculty with an appointment in Mathematics and Statistics (e.g., a faculty member with a joint appointment in Political Science and Mathematics and Statistics).

Please see The Bulletin for additional information, including modified course requirements for this degree.

For general information about applying to a graduate program at Washington University in St. Louis, please visit the Office of Graduate Studies website. This website will have all current information about the application process, form, and general deadlines.

To apply for the Master's in Statistics program, please visit our Graduate Application page. The early application due date for the Master's in Statistics is March 1st, with the extended deadline of April 10, 2026.  (Note that applications completed by March 1 will be reviewed by early March. Later applications will be reviewed in batches in March and April.).

For questions specific to the Statistics and Data Science Department, please contact the Director of the Master's Program at SDSMastersDirector@wustl.edu.

Students ordinarily complete the PhD program in five years, and those students may expect up to five years of support. Continuation of support each year is dependent upon normal progress toward the degree and the satisfactory performance of duties. Students typically spend their first two years (four semesters) taking graduate courses. At the end of this time, they will have completed requirements for the master's degree. Students ordinarily start the process of finding a dissertation advisor and start their research during their second year.

A student who comes to Washington University with advanced preparation may finish in less time. Alternatively, some students find that it is advisable for them to take some preparatory courses before attempting the qualifying courses. In special cases, the time schedule may be lengthened accordingly.

Washington University's graduate student stipends are in the top 25% of stipends at similar universities, and St. Louis has a low cost of living.

Completion of the PhD requires four to five years of graduate study. The student must spend at least one academic year as a full-time student; this requirement cannot be met wholly by summer sessions or part-time study. The student may, with departmental permission, transfer a maximum of 15 graduate credits from other universities. The typical course load is 9 credit units per semester. A GPA of B (3.0) or better is required in graduate coursework.

PhD students may ordinarily expect up to five years of support. Continuation of support each year is dependent upon normal progress toward the degree and the satisfactory performance of duties. Teaching experience is an increasingly important component of graduate education for students who seek academic employment. The PhD in statistics program provides the opportunity for students to work as Assistants to the Instructor and to learn how to teach technical topics to students with a wide range of backgrounds.

Additional information can be found in the Bulletin. 

A total of 45 graduate units are required, consisting of the following:

• 18 required coursework units in fundamental topics and exam fields
• 18 elective coursework units
• Two qualifying exams in statistics
• 1.5 coursework units of the Teaching Seminar Course
• 1.5 coursework units of the Professional Development Course
• 6 coursework units of Statistics and Data Science Seminars
• Teaching Requirement for PhD Students from the Office of Graduate Studies, Arts & Sciences
• Oral presentation
• Dissertation research, thesis preparation, and defense

Specific course requirements and information can be found on the Bulletin.

All students must demonstrate proficiency in English.

If English is not the student's native language, they must pass an oral English proficiency exam with a grade of 3 or better. If the student does not score a 3 the first time they take the exam, the director of English Language Programs for Arts & Sciences will recommend that the student take one or more classes to improve reading, writing, pronunciation, listening, or speaking skills. After the recommended classes have been completed, the student is required to retake the English proficiency exam. Once the student has demonstrated the ability to handle teaching a class (by scoring a 3 or better on the exam), they will qualify for Assistant in Instruction or Course Instructor duties.

More information, including information about exemptions, can be found on the Office of Graduate Studies website.

The qualifying exam and candidacy requirements constitute two separate requirements. The qualifying exam is a series of two written tests that cover a range of topics; the candidacy requirement is an oral presentation and thesis proposal.

The written tests cover the material in two of the following three sequences:

1. Pick one of the following two course pairs:
   1. SDS 5061 Theory of Statistics I and SDS 5062 Theory of Statistics II
   2. SDS 5010 Probability and SDS 5020 Mathematical Statistics
2. SDS 5071 Advanced Linear Models I and SDS 5072 Advanced Linear Models II
3. SDS 5531 Advanced Statistical Computing I and SDS 5532 Advanced Statistical Computing II

Each spring, at the end of the SDS 5020 (or SDS 5062), SDS 5072, and SDS 5532, all students enrolled in these courses take a two-hour final exam; this exam usually covers the second half of the sequence. Doctoral candidates take an additional one-hour exam that covers the two courses of each sequence. To pass the qualifying exam of the sequences, the student must pass the three-hour combined exam.

Because each sequence varies somewhat in content from year to year, it is recommended that the student take each set of exams at the conclusion of the sequence in which they are enrolled. No advantage is gained by delaying the exam for a year. It is desirable to make every effort to finish all three exams by the end of the second year of study.

Some students will enter the PhD program with previously acquired expertise in one or more of the three basic sequences. This situation sometimes happens with students who transfer from other PhD programs or who come from certain foreign countries. Such students may formally petition the Director of Graduate Studies to be exempted from the appropriate course and its qualifying exam. The petition must be accompanied by hard evidence (e.g., published research, written testimony from experts, records of equivalent courses, examinations and the grades achieved on them). The graduate committee will make the final judgment on all exemption requests.

Once the written phase of the qualifying process is complete, the student is ready to begin specialized study. By the third year of study, the student must complete the candidacy requirement. The student must form a preliminary thesis committee called a Research Advisory Committee that includes their advisor and at least two other faculty members. In discussion with the advisor and the preliminary thesis committee, the student will select a topic, and a body of literature related to this topic. The student will prepare a one-hour oral presentation related to the topic and a two-page thesis proposal that demonstrates mastery of the selected topic. The oral presentation is designed to expedite specialized study and to provide guidance toward the thesis. The preparatory work for the thesis proposal often becomes the foundation on which the thesis is constructed.

After the student completes the oral presentation, work on the thesis begins. More information about qualifying exams and candidacy requirements can be found in The Bulletin.

The student's dissertation is the single most important requirement for the PhD degree; it must be an original contribution to the knowledge of data science, statistics, probability, and/or applied probability and is the student's opportunity to conduct significant independent research.

It is the student's responsibility to find a thesis advisor who is willing to guide their research. Since the advisor should be part of the oral presentation committee, the student should have engaged an advisor by the beginning of their second year of study.

Once the department has accepted the dissertation (on the recommendation of the thesis advisor), the student is required to defend their thesis through a presentation accompanied by a question-and-answer period.

For information about preparing the thesis and its abstract as well as the deadlines involved, including the creation of the Research Advisory Committee and the Dissertation Defense Committee, please consult the Office of Graduate Studies, Arts & Sciences.

Please use these additional relevant resources: the Doctoral Dissertation Guide, the Forms page and the Policies and Procedures page.

For general information about applying to a graduate program at Washington University in St. Louis, please visit the Office of Graduate Studies website. This website will have all current information about the application process, form, and general deadlines.

To apply for the PhD in Statistics program, please visit our Graduate Application page. 

For questions specific to the Statistics and Data Science Department, please reach out to the Director of the PhD Program at SDSPhdDirector@wustl.edu.