Graduate Degree Program Summary
Graduate programs offered
Earn a Graduate Degree
- MS in Survey Research and Methodology (47 cr, Option II only)
- PhD in Survey Research and Methodology (90 cr)
Earn a Graduate Certificate
Certificates have their own deadlines and checklists; select one for details.
- Grad Cert in Survey Research and Methodology (18 cr)
Online and Distance OpportunitiesSome online coursework may be available for your program; contact dept. for details.
Application checklist and deadlines
1. Required by Graduate Studies
Submit these items as part of the standard steps to admission.
2. Required by Survey Research and Methodology
After you apply, allow one business day for us to set up your access so you can complete these requirements via MyRED.
- Entrance exam(s): GRE or GMAT
- Minimum English proficiency: Paper TOEFL 585, Internet TOEFL 95, IELTS 6.5
- Three recommendation letters
- Statement of purpose
When sending GRE or TOEFL scores, Nebraska's institution code is 6877 and a department code is not needed.
Application Deadlines for Survey Research and Methodology
- January 31 for Fall.
Application/admission is for entry in a specific term and year. Our academic year is divided into 3 terms: Fall (August-December), Spring (January-May), and Summer (multiple sessions May-August). Some programs accept new students only in certain terms and/or years; if your desired entry term isn't mentioned here, you may want to consult the department for clarification.
The Survey Research and Methodology (SRAM) program offers M.S. and Ph.D. degrees and a certificate program. All three are very much cross-disciplinary. Areas of study include: cognitive survey research, intermediate and advanced data analysis, survey sampling, study design and management, data collection methods, instrument design, and testing and assessment, as well as cross-cultural survey research and methods. In addition, master's and doctoral students may choose from a wide range of minor area of emphasis.
The M.S. program is designed to provide students with comprehensive expertise in survey methodology, equipping them to conduct survey research and analysis in a wide range of fields in the public and private sectors, including health, education, media, official statistics, and polling. The M.S. program is a two-year nonthesis program which includes an internship with an external organization, agency, or company. The Ph.D. program offers research opportunities in areas such as data analysis, social and cognitive survey research, questionnaire design, survey error and the "total survey error paradigm", nonresponse, data collection challenges, and cross-cultural and cross-national survey research. The program is designed as a four-year program and requires a dissertation of original work that advances knowledge in the field of survey methodology. Ph.D. graduates are likely to have opportunities within academic settings, in government, business, and nonprofit sectors.
The SRAM program offers funding for research assistantships to promising M.S. and Ph.D. applicants and special opportunities exist to receive a scholarship funded by the Gallup Organization in Omaha.
Courses and More
Faculty and research
Where available, faculty names link to bios or homepages and conversation icons () link to directory listings with address, phone, and email.
Database Marketing; Market Research; New Product Development; Customer Relationship Marketing; Human Trafficking; Services Marketing and CRM; Database Marketing; Measurement and Problems of Measuring Difficult Constructs and Phenomena
Novel Latent Variable Applications; Bio-Behavioral Data Analysis
Item Response Theory; Hierarchical Linear Models; Applied and Theoretical Psychometrics; Computer Adaptive Testing
Survey Informatics; Environment and User Modeling; Autonomous Data Science
Measurement Error; Nonresponse Error and Interaction of Error Sources
Survey Methodology; Non-Response Error, Measurement Error, Interviewer Effects
Nonresponse; Questionnaire Design; Gender; Family
Multiagent Systems; Intelligent Education Systems; Machine Learning; Intelligent Agents; Data Mining; Image Processing and Analysis; Multiagent Systems