Getting Started
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.
Master’s of Arts in Statistics and Data Science
The degree offers two concentrations: Statistics and Applied Data Science. There are 30 units of coursework. Students may also choose an optional thesis pathway, which requires 6 additional units of thesis research, bringing the total requirement to 36 units. 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. 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.
For more information, please view the Bulletin page.
The Statistics concentration is intended for students seeking deeper training in statistical theory, mathematical statistics, and advanced statistical methodology, including those preparing for PhD study or technically intensive statistical work.
There are 12 units of required courses for students in the Statistics Concentration:
- SDS 5010 & SDS 5020 Probability and Mathematical Statistics (6 units)
- SDS 5130 Linear Statistical Models (3 units) OR SDS 5521 Advanced Linear Models I (3 units)
- SDS 5210 Statistical Computation (3 units)
- SDS 5910 Practical Training in Statistics (0 units)
For more information, visit the Bulletin.
The Applied Data Science concentration is designed for students who want rigorous training in statistical modeling, computation, and data science, with greater flexibility to connect these tools to domain-specific applications in areas such as biology, economics, political science, psychology, and other data-driven fields.
There are 12 units of required courses for students in the Applied Data Science concentration:
- SDS 5005 Essentials of Probability Models and Statistical Inference (3 units)
- SDS 5130 Linear Statistical Models (3 units)
- SDS 5210 Statistical Computation (3 units)
- SDS 5215 Python for Data Science (3 units)
- SDS 5910 Practical Training in Statistics (0 units)
For more information, visit the Bulletin.
The Office of Graduate Studies in Arts & Sciences has an accelerated Bachelor’s/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. Students can choose either the Statistics or Applied Data Science concentration.
Participants can count up to 12 units of 4000-/5000-level coursework earned during the four years of undergraduate study (with grades of B or better) toward the MA course requirements. Counting these 12 units makes it possible to finish the master's requirements in one additional year, but the program is still fast-paced and requires intense work and careful planning. Applicants are expected to have backgrounds comparable to the students admitted to the regular MA program.
Interested majors should consult with the SDS Director of Master's Program by the beginning of the fall semester of their senior year, before the add/drop deadline, to ensure that all necessary courses will be completed during the senior year. Students are strongly recommended to contact the program director early. This program is only for Washington University in St. Louis undergraduates who, if they participate, must do so in the academic year immediately following graduation (no deferments). Eligibility requires having completed the BA or BS degree at Washington University in St. Louis and completing sufficient coursework from the Department of Statistics and Data Science.
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.
For more information, visit the Accelerated BA/MA in Statistics concentration and the Accelerated BA/MA in Applied Data Science concentration pages of the Bulletin.
This program is a tailored Masterʼs degree in Statistics and Data Science for PhD students in political science at Washington University in St. Louis. Note that, while the program is designed to serve political science PhD students, it is run by the Department of Statistics and Data Science. Students interested in this program will need to begin their additional coursework during their third year of study (or preferably before). Students are encouraged to apply for the program in the fall semester of their second 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 5690 Quantitative Political Methodology I, and Pol Sci 5695 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 and the Director of Graduate Studies in the Department of Political Science.
• Students must formally apply to the Department of Statistics and Data Science Master of Arts program.
Please see The Bulletin for additional information, including modified course requirements for this degree.
The Statistics and Data Science Department at Washington University in St. Louis has partnered with Sungkyunkwan University (SKKU) in Korea to allow students earning a BA degree from SKKU’s Department of Statistics to earn their MA in Statistics from WashU, usually in one additional year of study.
To earn the MA in Statistics and Data Science, students will need to complete 30 total units of coursework. Participants can count up to 9 units of undergraduate coursework earned at SKKU toward the MA course requirements, leaving 21 units to be completed (with grades of B or better) at WashU. Applicants are expected to have backgrounds comparable to the students admitted to the regular MA program.
To Apply: Senior Statistics students at SKKU should submit their application to WashU no later than one semester before they hope to enroll, adhering to the application requirements on our Graduate Application Page.
To be eligible for the thesis option in any of our Master’s programs, 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 Statistics (e.g., a faculty member with a joint appointment in Political Science and Statistics).
Every Master’s student in SDS must take 18 elective credits. All 5000-level SDS courses are eligible electives. In addition, this list includes pre-approved elective courses from other departments.
SDS 5061 / 5062: 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 5315: Python for Data Science
SDS 5320: Foundations for Causal Inference
SDS 5430: Statistical Learning
SDS 5440: Mathematical Foundations of Data Science
SDS 5510 / 5511: Advanced Probability I / II
SDS 5531 / 5532: Advanced Statistical Computing I / II
Advanced Topics Courses:
- SDS 5480
- SDS 5571
- SDS 5595
- SDS 5800
- SDS 5801/5802
- SDS 5805
MATH 5151 / 5152: Measure Theory and Functional Analysis I / II
MATH 5011 / 5012: Introduction to Analysis / Lebesgue Integration
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 5220 Practical Bioinformatics
BIOL 5483 Human Genetic Analysis
BIOL 5495 Computational Molecular Biology
CSE 4107 Introduction to Machine Learning
CSE 5100 Deep Reinforcement Learning
CSE 5103: Theory of Artificial Intelligence and Machine 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 6110 Econometrics
ECON 6140 Machine Learning and Data Science in Economics
ECON 6840 Introduction to Stata
ECON 6850 A First Python Course for Economists
ECON 8111 Quantitative Methods in Economics II
ECON 8151 Advanced Theoretical Econometrics
ECON 8110 Applied Econometrics
ECON 8130 Structural Microeconometrics
ECON 8135 Advanced Microeconometrics
ECON 8150 Advanced Topics in Econometric Theory
PSYCH 5068 Hierarchical Linear Models
PSYCH 5167 Applied Bayesian Statistics for Psychologists
POLSCI 5063 Causal Inference
POLSCI 5626 Applied Statistical Programming
POLSCI 5720 Computational Social Science
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
For Accelerated BA/MA students: 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 that 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.
For questions specific to the Statistics and Data Science Department, please contact the Director of the Master's Program at SDSMastersDirector@wustl.edu.
Prior to Fall 2026, the regular MA in Statistics consisted of 36 units of coursework to be completed in three to four semesters. A GPA of B (3.0) or better must be maintained in graduate courses.
After completing a set of 6 core courses, MA students 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 an optional Masterʼs thesis; 3 units may be for thesis research.
Typically, no more than 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 5000-level, it cannot be included among the courses used to satisfy the 36 units requirement.
Current students enrolled before Fall 2026 may choose to switch to the new requirements or may continue with the requirements from when they enrolled.
View prior Bulletins.
PhD in Statistics
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:
- Pick one of the following two course pairs:
- SDS 5061 Theory of Statistics I and SDS 5062 Theory of Statistics II
- SDS 5010 Probability and SDS 5020 Mathematical Statistics
- SDS 5071 Advanced Linear Models I and SDS 5072 Advanced Linear Models II
- 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.