Distinguished University Professor
Presser, Stanley, Full Member
Abraham, Katharine, Full Member
Kreuter, Frauke, Full Member
Lahiri, Partha, Full Member
Li, Yan, Full Member
Associate Research Professor
Elliott, Michael, Full Member
Conrad, Frederick G., Full Member
Couper, Mick P., Full Member
Lepkowski, James M., Full Member
Assistant Research Professor
Research Professor Emeritus
Valliant, Richard L., Full Member
Survey and Data Science (online) (MPDS)
Program Title and Classification
Survey and Data Science (online)
Graduate Degree Program
College: Behavioral and Social Sciences
The Joint Program in Survey Methodology (JPSM) blends together faculty with diverse disciplinary backgrounds all devoted to teaching state-of-the-art practices in the statistical and methodological aspects of surveys and data. The program's faculty primarily come from the University of Maryland, University of Michigan and Westat, supplemented by instructors from a number of federal statistical agencies. Many of these faculty are leading researchers and statisticians in the field of survey methodology, thereby providing an unparalleled educational experience to the students. JPSM's offerings include onsite PhD and Master’s degrees as well as online Certificates and a Professional Master's degree.
- Transcript(s): Should show previous coursework or knowledge in mathematical/applied statistics demonstrated by completion of 6 credits of applied statistical methods courses covering content from probability theory through basic regression techniques (including both OLS and logistic regression)
- TOEFL/IELTS/PTE (international graduate students)
- Provide a CV which should show at least one full year of relevant work experience at the time of application in a position dealing with survey or census design, data collection, or statistical analysis.
- Supplementary Application: Complete a one-page essay describing relevant work experience, interest in survey and/or data science, and expected benefits of enrolling in this degree program. (Uploaded to Supplementary Application in the Uploads Requirements section of the application.)
- Provide the contact information for three references: Supplementary Application Two
- Statistics Prerequisites: Previous coursework or knowledge of mathematical/applied statistics demonstrated by completion of 6 credits of applied statistical methods courses covering content from probability theory through basic regression techniques (including both OLS and logistic regression). Students should provide a short explanation of how the requirement is met by noting courses on their transcripts, describing courses taken not for credit, or relevant work experience and attach relevant syllabi. If students cannot demonstrate prior knowledge, they will be required to pass an entrance examination administered by JPSM that tests knowledge of applied statistical methods.
*Visa Eligibility: This program is not eligible for I-20 or DS-2019 issuance by the University of Maryland.
Applicants must have earned a four-year baccalaureate degree from a regionally accredited U.S. institution, or an equivalent degree from a non-U.S. institution. Applicants must have earned a 3.0 GPA (on a 4.0 scale) in all prior undergraduate and graduate coursework.
For more admissions information or to apply to the program, please visit our Graduate School website: www.gradschool.umd.edu/admissions
|Type of Applicant||Fall||Spring|
US Citizens and Permanent Residents
|29 Jun||31 Oct|
F (student) or J (exchange visitor) visas
A,E,G,H,I and L visas and immigrants.
|29 Jun||31 Oct|
Other Deadlines: Please visit the program website at http://jointprogram.umd.edu/
Master of Professional Studies (M.P.S.)
The online International Master of Professional Studies in Survey and Data Science will provide post-baccalaureate training for individuals interested in broadening their knowledge and understanding of the emerging field of data science, the conduct of sample surveys, practical applications of data analysis and survey methodology, and data management, along with the skills needed to communicate results.
Survey methodology, which is already an interdisciplinary field drawing upon statistics, sociology, economics, political science, informatics, public health (e.g., physical measures taken on respondents), and the geographic sciences (e.g., geographic information systems), is now intersecting with the big data world. As public and private organizations are increasingly combining various data sources, including survey data, for the purpose of decision making, the need for professional development in data generation, quality and analysis is on the rise. The online environment is convenient for working professionals who cannot easily travel to a traditional campus. In addition, courses will be shared with our international partners, providing a rich perspective to class discussions.
Facilities and Special Resources
Training will be provided by permanent and adjunct faculty in the University of Maryland's Joint Program in Survey Methodology. Online lectures will be conducted via accessible video conference systems and Webinar tools.
Students will be instructed that to fully participate, they will need to purchase a webcam and headset with a microphone, and have a reliable computer and Internet access. Recorded lectures will be posted online at announced times and will be available online at any time thereafter during the course. Weekly discussions or help sessions will be held at scheduled, fixed times once per week.
As officially admitted students to the University of Maryland, students in this program will have access to all University resources that are accessible in the online environment. Students in online programs are assessed an online student services mandatory fee which supports access to these University resources.
For more information, contact the department at email@example.com.
University of Maryland
College Park MD, 20742
Online Masters, Professional Studies, Survey Practice, Surveys, Survey Research, Data Science, Statistical Methods, International Programs, Distance Learning, Household Surveys, Business Establishments, Institition Surveys, Population Surveys, Samnpling and Estimation in Complex Surveys, Questionnaires, Questionnaire Design, Data Collections, Survey Data Quality, Measurement Error, Survey Design, Data Sources, Applied Sampling, Survey Methodology, Analysis of Complex Data, Sampling Theory, Public Opinion, Statistical Modeling, Survey Management.