Framework for Data Collection and Analysis
Master comprehensive data collection methods and quality assessment frameworks for effective research and analysis.
Master comprehensive data collection methods and quality assessment frameworks for effective research and analysis.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Survey Data Collection and Analytics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Design effective research questions and data collection plans
Evaluate and select appropriate data sources
Assess data quality using established frameworks
Understand various data collection methodologies
Apply quality metrics to data analysis
Develop comprehensive research strategies
Skills you'll gain
This course includes:
2.8 Hours PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course provides a framework for data collection and analysis, focusing on research design and quality assessment. Students learn to identify appropriate data sources, develop measurable research questions, and evaluate data quality using established frameworks. The curriculum covers various data collection methods, quality metrics, and real-world applications through case studies of major surveys. Special attention is given to the Total Survey Error framework and its application in assessing data quality across different collection methods.
Research Designs and Data Sources
Module 1 · 3 Hours to complete
Measurements and Analysis Plan
Module 2 · 1 Hours to complete
Quality Framework
Module 3 · 2 Hours to complete
Application of TSE Framework to Existing Surveys
Module 4 · 2 Hours to complete
Fee Structure
Instructors
Distinguished Survey Methodologist and Data Science Expert
Dr. Frauke Kreuter is a distinguished scholar in survey methodology and data science, holding key positions at the University of Maryland, University of Michigan, University of Mannheim, and the German Institute for Employment Research. Her extensive academic background includes roles at Ludwig Maximilians University and UCLA. Dr. Kreuter has made significant contributions to the field through influential books on data analysis and survey sampling, pioneering research on paradata in surveys, and interdisciplinary studies published in major journals. Her teaching experience spans over two decades, including long-standing courses at JPSM and the University of Michigan's Summer Institute. Dr. Kreuter's expertise is widely recognized, as evidenced by her election as a fellow of the American Statistical Association and her receipt of the Warren Mitofsky Innovators Award. Her work, which bridges survey methodology, statistics, and data science, has profoundly influenced survey research and its adaptation to evolving data environments, cementing her status as a leading figure in the field.
Lecturer
Mariel Leonard is a Lecturer at the University of Maryland, College Park, specializing in survey methodology and data analytics. With over a decade of experience in designing and implementing survey research projects, she began her career at Westat in Rockville, MD, where she worked in both the Telephone Research Center and the Instrument Design, Evaluation, and Analysis Services department. Her expertise extends to consulting for various organizations, including the German Ministry for Migration and Refugees and UNICEF, focusing on improving data equity and representation of ethnic minorities in research.Dr. Leonard holds a doctorate in empirical sociology from the University of Mannheim, where her research emphasized the importance of effective data collection methods. She teaches courses such as "Framework for Data Collection and Analysis," where she equips students with essential skills to conduct rigorous research in diverse contexts. Her commitment to advancing knowledge in survey methodology is evident through her active participation in academic conferences and her work on sensitive topics involving special populations. Through her teaching and consulting efforts, Mariel Leonard continues to make significant contributions to the field of data analytics and survey research
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Frequently asked questions
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