michigan statistics phd

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The Ph.D. in Statistics is flexible and allows students to pursue a variety of directions, ranging from statistical methodology and interdisciplinary research to theoretical statistics and probability theory. Students typically start the Ph.D. program by taking courses and gradually transition to research that will ultimately lead to their dissertation, the most important component of the Ph.D. program.

These requirements apply to students admitted for Fall 2020 and after. Students admitted in Fall 2019 and earlier should consult the Previous Program Requirements page .

PhD Coursework:

The core PhD curriculum is divided into five areas: 

Methods — STATS 600 and 601

Practice — STATS 604

Statistical Theory — STATS 511, 610, 611

Probability — STATS 510, 620, 621

Computing — STATS 507, 606, 608 

All doctoral students must complete the following in their first three semesters in the program and before advancing to candidacy: 

Take all methods and practice courses (600, 601, 604)

Take at least two courses in the combined areas of statistical theory and probability,  including at least one course in statistical theory and at least one 600-level course 

Take at least one computing course

Achieve a 3.5 average grade (on the 4.0 scale used by Rackham) in 600, 601, 604, and one 600-level statistical theory or probability course

Not completing requirements 1-4 by the end of the third semester will trigger probation which, if not resolved by the end of the fourth semester, may lead to dismissal from the program.  For more details, see the link below. 

By the end of the PhD program, all students must take at least 30 credits of graduate statistics courses.    All courses from the core areas count towards this total, as well as all 600-level, 700-level, and selected additional  500-level courses with approval of the PhD Program Director. Seminars and independent study courses do not count. At least 21 credits must be at the 600 level or higher. The Rackham Graduate School requires PhD students to maintain an overall GPA of at least 3.0 to remain in good standing.   

In addition, all doctoral  students must take 3 credits of cognate courses as required by the Rackham graduate school, and two professional development seminar courses. Cognate courses are 400- and higher-level courses from outside Statistics and not cross-listed with Statistics. All cognate course selections must be approved by the PhD Program Director. The professional development courses are 

STATS 810, research ethics and introduction to research tools, in the first semester in the program.

STATS 811, technical writing in statistics. Students are strongly advised to complete this course in their second or third year.

Typical Course Schedules:

Our Ph.D. program admits students with diverse academic backgrounds. All PhD students take STATS 600/601  in their first year. Students are strongly encouraged to take STATS 604 in their second year (Stats 600 is a prerequisite).  

Students with less mathematical preparation typically take STATS 510/511 (the Master’s level probability and statistical theory) in their first year and 600-level probability and/or statistical theory courses in their second year.    

Advanced students, for example those with a Master’s degree, typically do not need to take 510/511, and in some cases may skip 610 and 621. Students who wish to take 600-level probability and statistical theory courses in their first year must take a placement test just before the fall semester of their first year to get approved. The PhD Program Director will help each student choose their individual path towards completing the requirements.  

Some typical sample schedules are listed below. In most cases, we do not recommend taking more than three full-load courses per semester (not counting seminars).

Sample schedule 1:

Sample schedule 2:

Advancing to Candidacy:

Students are expected to find a faculty advisor and start research leading to their dissertation proposal no later than the summer after their first year. The PhD Program Director and the faculty mentor assigned to each first year student can assist with finding a faculty advisor. Students are expected to submit a dissertation proposal and advance to candidacy some time during their second or third year in the program.   

Requirements for advancing to candidacy are:

Satisfying Requirements 1-4

Completing at least 3 credit hours of cognate courses

Writing a dissertation proposal and passing the oral preliminary exam, which consists of presenting the proposal to the student's preliminary thesis committee

A dissertation proposal should identify an interesting research problem, provide motivation for studying it, review the relevant literature, propose an approach for solving the problem​, and present at least some preliminary results​. The written proposal must be submitted to the preliminary thesis committee and the graduate coordinator a​head of time (one week minimum, two weeks recommended)​ and then presented in the oral preliminary exam. The preliminary thesis committee is chaired by the faculty advisor and must include at least two more faculty members, at least one of them from Statistics. ​​The faculty on the preliminary thesis committee typically continue t​o serve ​on ​the doctoral thesis committee​​, but changes are allowed.  Please see Rackham rules on thesis committees for more information.  

At the oral preliminary exam, the committee will ask questions about the proposal and the relevant background and either elect to accept the proposal as both substantial and feasible, ask for specific revisions, or decline the proposal. The unanimous approval of the proposal by the committee is necessary for the student to advance to candidacy.

Additional Information:

Students are encouraged to complete the bulk of their coursework beyond Requirements 1-4 in the first two years of study.  Candidates are allowed to take only one course per semester without an increase in tuition.

All PhD students are expected to register for Stats 808/809  (Department Seminar) every semester unless restricted by candidacy, and attend the seminar regularly regardless of whether they are registered.  

Exceptions to the PhD program requirements may be granted by the PhD Program Director.

Annual Report:

Each candidate is required to meet with the members of their thesis committee annually. This could be in the form of either giving a short presentation on their research progress to the thesis committee as a group, or meeting with committee members individually.

Each committee member should complete a Thesis Committee Member Report and return it to the student. The student should share the completed Thesis Committee Member Reports with both the PhD Program Coordinator and their advisor.

All meetings with the committee members should take place by April 15.

Following the meetings, the student and the advisor should complete the Annual PhD Candidate Self-Evaluation and Feedback Form . The advisor should review the committee members’ Thesis Committee Member Reports and take them into account when completing the advisor’s portion. The completed Annual PhD Candidate Self-Evaluation and Advisor Feedback Form must be submitted to the PhD Program Coordinator by May 31. The completed form will be saved with the department, and a copy will be shared with the student.

Dissertation and Defense:

Each doctoral student is expected to write a dissertation that makes a substantial and original contribution to statistics or a closely related field. This is the most important element of the doctoral program. After advancing to candidacy, students are expected to focus on their thesis research under the supervision of the thesis advisor and the doctoral committee. The composition of the doctoral committee must follow the Rackham's  guidelines for dissertation committee service . The written dissertation is submitted to the committee for evaluation and presented in an oral defense open to the public.

Rackham Requirements:

The Rackham Graduate School imposes some additional requirements concerning residency, fees, and time limits. Students are expected to know and comply with these requirements.

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Doctor of Philosophy in Survey and Data Science

Become an expert and lead with confidence in survey methods and data science. The Doctor of Philosophy in Survey and Data Science program at the University of Michigan is designed for individuals interested in conducting original research and teaching material in survey and data science jobs.

Our survey and data science PhD degree program will prepare you to identify problems, design solutions, and evaluate results at the intersection of survey methods and data science. You will work with a wide range of leading academic scholars who are faculty in the U-M’s Institute for Social Research , the world’s largest academic social science research center. Collaborate with experts in survey methods and data science to investigate issues that have broad impact across the social sciences, statistics, and data science.

U-M’s survey and data science graduate program has a higher completion rate than our peer programs, according to the Association of American Universities Data Exchange. That means by enrolling in the MPSDS PhD program you will be well positioned to lead in virtually any industry that conducts quantitative research on human social behavior. You will also have the expertise to help train the next generation of survey and data scientists.

Complete your survey and data science PhD in as little as four years, which is faster than the average completion time for many other social science PhD programs

Learn from leading experts in survey methods and data science

Get ahead through groundbreaking research initiatives with U-M’s Institute for Survey Research

Prepare to lead in survey research or academia

View the courses | Admissions requirements | Doctoral Degree Requirements |  Request more information | Apply Now

Why Pursue a Survey and Data Science Graduate Program?

Survey and data science as a field needs leaders who can manage interdisciplinary teams of scientists. At the same time, individuals who can guide and mentor future experts in our ever-changing profession are also in high demand. If you’re passionate about methods of surveying — and their intersection with data science — U-M’s survey and data science PhD program may well be the right program for you.

Our survey and data science graduate program attracts leading minds from around the globe. From our faculty to our graduate students, we share an interest in developing, researching, and evaluating new methods for conducting social science research using survey data, big data , or a combination of both.

A Doctoral Program That Gives You the Best of Both Worlds

While other doctoral programs may focus on just survey methods or only data science, U-M’s survey and data science graduate program prepares you for survey and data science jobs with broad interdisciplinary applications. You will learn to identify trends in survey and data science and develop theories and applications for which there is great demand among survey and data science jobs. In the end, you will be well prepared for research and teaching positions in both academic and non-academic institutions.

Learn from accomplished experts in survey and data science — then become one

U-M’s national and international reputation in survey methods and data science is unrivaled. Our program faculty members are leading contributors in the field and are highly engaged in their respective research communities, contributing their time in professional organizations, as editors or members of the editorial boards for top journals, invited speakers, and much more.

These accomplished professionals will guide, mentor, and support you as you grow your career in survey methodology and data science.

An affordable investment in survey and data science jobs

PhD students in our survey and data science graduate program are fully funded for four years. This means your tuition and fees will be paid while you earn your survey and data science PhD. Plus, you will also receive a paid, four-year Graduate Student Research Assistantship to work on a faculty-led project or assist in the classroom.

Several research fellowships help cover the cost of conducting your original research and in some cases, provide you a stipend. These financial resources help make your doctoral studies affordable. You will receive the training you need for a career with competitive survey and data science salaries.

Pursue groundbreaking research with a worldwide leader in survey and data science

Our survey and data science graduate program is housed in the U-M Institute for Social Research (ISR), which is the world’s oldest social science research organization. ISR employs more than 300 research scientists in over 20 academic disciplines. ISR’s survey research operations are home to a telephone interviewing lab and headquarters for a national field staff, as well as a large staff who provide logistical and analytical support.

This means you will be exposed to methods for survey data collection as they are developed and about to be deployed. This experience will help you learn about survey methods and their intersection with data science. You will also stand out as conversant with cutting-edge developments as you pursue data science and survey jobs.

Gain a global view of survey and data science

While you will receive a top-notch doctorate in data science and survey methods from Michigan, we know that gaining multiple perspectives in our field is important. With them you’ll grow into a well-rounded professional prepared for success in research and education in the workplace where the mission is focused on survey research and data science techniques. As a U-M doctoral student, you will have the opportunity to study for a semester, or more, in the United Kingdom at University of Essex, another international leader in developing methods for and conducting longitudinal research.

“Michigan’s survey and data science PhD program stands out because of their emphasis on applications of data science into the survey world. Faculty teach not only what data science is, but how it changes based upon the collection of data. Michigan has everything I wanted.”

-Curtiss Engstrom, PhD in Survey and Data Science, 2025

What Can You Do With a PhD in Data Science and Survey?

Students in our survey and data science graduate program are leaders in their respective fields and earn promising survey and data science salaries. What sets our graduates apart is their ability to work with survey data and big data.

Our graduates have found impactful and rewarding jobs in a wide variety of industries and locations. They’ve also found promising survey and data science salaries.

These survey and data science jobs are housed at universities, social and market research companies, health care research organizations, government agencies, technology companies, and more. Examples of where their jobs in survey and data science have taken them include:

• Research and academic programs at Harvard University, UCLA, the Universidad del Desarrollo, the University of Colorado, the University of Costa Rica, the University of Mannheim, the University of Maryland, the University of Michigan, the University of Munich, the University of Nebraska, and Zhejiang University
• Research and survey companies such as the Institute for Employment Research, Pew Research Center, Survey Monkey, Facebook, Google, Southpaw Insights, and Westat

Explore Coursework for the Survey and Data Science PhD Program

Our four-year doctoral degree program will prepare you to lead in data science and survey jobs that drive decision making.

First- and second-year survey and data science PhD students take courses offered by the program such as Design and Implementation of Web Surveys, Questionnaire Design and Evaluation, and Analysis of Complex Sample Survey Data. You will also take courses across the university that are relevant to your dissertation research.

Plus, a doctoral seminar during your first two years immerses you in literature and cutting-edge research to help you learn to identify where more research is needed and how to design research that fills those gaps. During the doctoral seminar, you will develop an original research proposal on a topic of your choice — under the guidance of two faculty instructors — that will likely serve as the basis of your doctoral dissertation.

You will then spend your final two years of the survey and data science PhD program conducting research, reviewing literature, and documenting your findings. Our doctoral students typically present their dissertation results during one or more conference presentations and publish several journal articles or chapters based on their research — helping them develop a professional network.

Examples of past doctoral dissertations include:

• Careless Survey Respondents: Approaches to Identify and Reduce Their Negative Impacts on Survey Estimates
• The Effects of Respondent Commitment and Feedback on Response Quality in Online Surveys
• Mobile Web Surveys: A First Look at Measurement, Nonresponse, and Coverage Errors

View all required classes for this program.

Get Started on Your Survey and Data Science PhD

Advance your research or teaching career in survey and data science. If you have questions, please fill out a request for more information or call us at 734-647-0038 .

Apply today

Submit your application online today for the PhD in Survey and Data Science from the University of Michigan.

Learn more about admission requirements

See what admission requirements are required to pursue Michigan’s PhD in survey and data science.

Still accepting applications for online and hybrid programs!

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Biostatistics

Turn data into action.

Graduate programs in the Department of Biostatistics at the University of Michigan School of Public Health are among the best in the world. Currently, we are ranked as the No. 4 biostatistics department by US News and World Report. 

Alongside our world-renowned faculty, you’ll learn how to develop statistical designs and computational tools for analysis of large scale complex data in medical and health sciences, and work to apply statistical methods to discover groundbreaking scientific findings.

2023 Biostatistics Prospective Student Day

Explore Michigan Biostatistics in-depth at our annual Prospective Student Day on Sunday, October 29. From meeting the department’s students, faculty, and staff; to diving deeper into many of the topics and questions on the minds of prospective students; to sitting in on research presentations from a Biostatistics faculty member and a current Biostatistics student – attendees will get a full picture of what the department is all about. Lunch is provided for all attendees.

2023 Biostatistics PROSPECTIVE Student DAY

Apply to Michigan Biostatistics

Applications for Fall 2024 are open! Please consider applying to one of our two masters degrees (MS in Biostatistics or MS in Health Data Science) or our PhD program in Biostatistics. Applications close on December 1.

JOIN OUR INTEREST LIST

Master of Science Degree (MS)

Twenty-month, 48-credit-hour degree for students who plan to go on to pursue a PhD or scientific research and academic careers, including jobs in biostatistics and data science.

Doctor of Philosophy Degree (PhD)

High-level research track with original research as part of a doctoral dissertation. We offer two programs of study: one for students with a relevant master's degree and one for students without a relevant master's degree.

Student Spotlight

We are driven by our collective mission to help people and our resolute passion for problem solving. We are innovators and collaborators; we are thinkers and we are doers.

Career Outcomes

With more than $50M in funded research annually, Biostatistics faculty and students are conducting cutting-edge biostatistical research. They are involved in a wide range of collaborative research activities with faculty across the University of Michigan campus. Among our research areas:

• Computational biology and big data
• Statistical genetics and bioinformatics
• Cancer biostatistics
• Longitudinal data and survival analysis
• Clinical trials
• Biomedical imaging
• Bayesian statistics 

Meet our Faculty

Ready to apply.

Learn more about our application requirements and deadlines and start your application today. If you’re not ready to apply yet, but would like to receive more information about Michigan Public Health and the program(s) you’re interested in, join our prospective student interest list.

For more information about the admissions process, email our Recruitment and Admissions team at [email protected] or schedule an appointment to talk with a member of our Graduate Admissions team.

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Graduate College

Statistics (ph.d.),   application deadlines.

Applicantions must be submitted by the priority deadline of February 15 to be considered for a graduate assistantship.

Program admits for fall semester only. Submission deadline is July 1 for domestic applicants and March 1 for international applicants.

  Resume/Curriculum Vitae (CV)

A resume or curriculum vitae (CV) is required; please submit within the online application system.

  Graduate test

This program does not require the General GRE.

Note: International applicants may have to provide evidence of English language proficiency. More information can be found within the online application.

  Recommendations

If applying for a Teaching Assistantship, please request 3 recommendation letters.

  Written statement

Please prepare a statement which covers the following information, and attach it within the online application:

Summarize your experiences in academic, professional, research, creative, or scholarly activities, and indicate how these experiences make you an ideal candidate for graduate study in your selected program. Also address how these activities align with the strengths of your chosen program and faculty, and with your professional goals, including future job positions. This statement (double-spaced and between 500 – 1500 words) should demonstrate your communication skills and writing competence

  Previous written work

This program does not require any previous written work be submitted.

  Other program materials

If applying for graduate assistantship, complete the following narrative and submit within the online application:

For those interested in a Teaching Assistantship, please list all math and stats courses taken, when they were taken, the number of credits received for each, and the grade received.

  Transcript requirement

An official transcript from the institution from which you received your bachelor degree is required, as well as a transcript from the institution(s) where any additional graduate level courses or degrees have been taken/completed. Applicants are not required to submit an official transcript of courses taken/completed at WMU.

  Additional information

If you have any questions, please review the website below for program and contact information.

Department of Statistics — College of Arts and Sciences

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Welcome to the Department of Statistics and Probability (STT) at Michigan State University. Our Department has a long and proud tradition of excellence for world-class research and training for more than 65 years. 

Founded in 1955, the Department of Statistics and Probability ( https://stt.natsci.msu.edu/ ) is part of the College of Natural Science at Michigan State University and is dedicated to advancing knowledge through research, education, and innovation. Its faculty are engaged in applied, methodological and theoretical research in statistics, probability, and data science and collaborate across diverse disciplines including computational biology, actuarial science, education, engineering, genetics, medical sciences, and the social sciences, among others, with access to a high-performance computing facility on campus. Faculty are engaged in statistics education   research and practice, and the department has a vibrant community of teaching faculty. The department awards bachelor’s degrees in statistics and in quantitative risk analytics, master’s degrees in statistics, applied statistics, and data science, and doctoral degrees in statistics. The department is home to over 100 graduate students and more than 100 undergraduate students from many countries. 

UPCOMING EVENTS

Department of EPIDEMIOLOGY AND BIOSTATISTICS

Phd students, epidemiology , tamanna afroj.

Tamanna finished her undergraduate studies in dentistry and practiced as a licensed dentist in Bangladesh. Learn More

Avery Armstrong

Avery is a PhD student in the Department of Epidemiology and Biostatistics Learn More

Norman Chamusah

Norman is a PhD student in the Department of Epidemiology and Biostatistics at Michigan State University. Learn More

Keran W. Chamberlin

Keran got her master’s degree at Fudan Univ, China and another master’s degree in health data science at the Univ of Manchester, UK. Learn More

Alicynne Glazier-Essalmi

Alicynne is a public health scientist and PhD student in the Department of Epidemiology and Biostatistics Learn More

Jazib Gohar

Jazib is a 4th year DO-PhD candidate in the Department of Epidemiology and Biostatistics as well as the College of Osteopathic Medicine. Learn More

Ra'ed Hailat

Ra'ed Hailat is a physician-epidemiologist investigating stroke outcomes and healthcare services with a focus on improving the efficiency and equity of health care Learn More

Florence Kizza

Florence is a Ph.D. Epidemiology student in the Department of Epidemiology and Biostatistics at Michigan State University and currently works as a Graduate Research Assistant with Dr. Misra’s lab. Learn More

Prudence Kunyangna

Prudence is a Ph.D. student in the Department of Epidemiology and Biostatistics at Michigan State University. Learn More

Xuan is a PhD student and completed her Master of Public Health degree at USC , Learn More

Timothy Michling

Tim Michling is a doctoral student in epidemiology and research assistant with the Margerison Research Group. Learn More

Matthew Myers

Matthew works as a Research Assistant with Dr. Kipling Bohnert on a variety of substance-use related topics. Learn More

Mounira Ozoor

Mounira Ozoor is a PhD candidate in the Department of Epidemiology and Biostatistics and works with Dr. Luo as her Advisor. Learn More

Claire Schertzing

Claire Schertzing is a PhD student in the Department of Epidemiology and Biostatistics and serves as the president of BEAMS Learn More

Bendu Sherman

Bendu is a PhD student in the Department of Epidemiology and Biostatics and a Graduate Teaching/Research Assistant. Learn More

Jessica Worley

Jessica is a PhD student in the Department of Epidemiology and Biostatistics Learn More

Jingjing (Kathy) Xia

Jingjing specializes in epidemiology Learn More

Michael Yeboah

Michael holds a bachelor's degree in Disability and Rehabilitation studies Learn More

BIOSTATISTICS

Kyle is a PhD student in the Department of Epidemiology and Biostatistics and serves as the vice president of BEAMS Learn More

Yanzeng is a PhD student in the Department of Epidemiology and Biostatistics with Dr Chenxi Li as his advisor Learn More

Yifei Li is a PhD after graduating with MS and BS degrees from MSU Learn More

Guanqi is a Biostatistics PhD student in the Department of Epidemiology and Biostatistics. Learn More

Alexa is a biostatistics PhD student who has been a part of the Department of Epidemiology and Biostatistics since 2016, Learn More

Cody Makinson

Cody is a Biostatistics Ph.D. student in the Epidemiology and Biostatistics Department and is a Graduate Teaching Assistant for the Statistics and Probability Department. Learn More

Elizabeth McMahon

Elizabeth is a PhD Biostatistics student in the Department of Epidemiology and Biostatistics Learn More

Maxwell Mac-Ocloo

Maxwell recently completed his master's program in Statistics and Data Science at the University of Texas at El Paso (UTEP) Learn More

Eleanor Song

Eleanor is a Ph.D. Candidate in the Department of Epidemiology and Biostatistics at Michigan State University (MSU) and has worked as a graduate research assistant. Learn More

Nabasmita Taludkar

Nabasmita is a Phd student in Department of Epidemiology and Biostatistics at Michigan State University. Learn More

Pengbo Wan is a Biostatistics PhD student in the Department of Epidemiology and Biostatistics at Michigan State University. Learn More

Liang Wang is a Biostatistics PhD candidate in the Department of Epidemiology and Biostatistics at Michigan State University. Learn More

Harold is a Biostatistics Ph.D. student in the Department of Epidemiology and Biostatistics at Michigan State University. PhD Biostatistics

Kun is a Biostatistics Ph.D. student in the Department of Epidemiology and Biostatistics at Michigan State University since 2022. Learn More

Hong is a Biostatistics PhD student in Epidemiology and Biostatistics at Michigan State University, Learn More