Survey Data Collection and Analytics Specialization
Collect and analyze data, and communicate results.. Learn to collect quality data and and conduct insightful data analysis in six courses.
About This Specialization
This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains. In six courses, you will learn the basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data. In the final Capstone Project, you’ll apply the skills learned throughout the specialization by analyzing and comparing multiple data sources. Faculty for this specialisation comes from the Michigan Program in Survey Methodology and the Joint Program in Survey Methodology, a collaboration between the University of Maryland, the University of Michigan, and the data collection firm Westat, founded by the National Science Foundation and the Interagency Consortium of Statistical Policy in the U.S. to educate the next generation of survey researchers, survey statisticians, and survey methodologists. In addition to this specialization we offer short courses, a summer school, certificates, master degrees as well as PhD programs.
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Designed to help you practice and apply the skills you learn.
Highlight your new skills on your resume or LinkedIn.
- Beginner Specialization.
- No prior experience required.
Framework for Data Collection and AnalysisUpcoming session: Mar 26
- 4 weeks of study, 1-2 hours/week
About the CourseThis course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research quest
Data Collection: Online, Telephone and Face-to-faceUpcoming session: Mar 19
- 4 weeks of study, 2-4 hours/weeks
About the CourseThis course presents research conducted to increase our understanding of how data collection decisions affect survey errors. This is not a “how–to-do-it” course on data collection, but instead reviews the literature on survey design decisions
Questionnaire Design for Social SurveysUpcoming session: Mar 19
- 4-8 hours/week
About the CourseThis course will cover the basic elements of designing and evaluating questionnaires. We will review the process of responding to questions, challenges and options for asking questions about behavioral frequencies, practical techniques for evaluating qu
Sampling People, Networks and RecordsUpcoming session: Mar 19
About the CourseGood data collection is built on good samples. But the samples can be chosen in many ways. Samples can be haphazard or convenient selections of persons, or records, or networks, or other units, but one questions the quality of such samples, especia
Dealing With Missing DataUpcoming session: Mar 19
- 4 weeks of study, 1-2 hours/week
About the CourseThis course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response prope
Combining and Analyzing Complex DataUpcoming session: Mar 19
About the CourseIn this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be
Survey Data Collection and Analytics Project (Capstone)Upcoming session: Mar 19
About the Capstone ProjectThe Capstone Project offers qualified learners to the opportunity to apply their knowledge by analyzing and comparing multiple data sources on the same topic. Students will develop a research question, access and analyze relevant data, and cr
Frederick Conrad, Ph.D.
Research Professor, Survey Methodology
James M Lepkowski
Frauke Kreuter, Ph.D.
Professor, Joint Program in Survey Methodology
Richard Valliant, Ph.D.
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