Data Sampling & Measurement
Understanding the representativeness of different subpopulations is complex when developing nationally representative surveys, but it is even more challenging when building samples from publicly shared user posts. MDI researchers work to understand how to reweight samples to make them more representative of populations of interest. They also develop standards for constructing different types of variables and determining the reliability of different types of measurements. This is particularly important when developing measurements using big data sources, e.g. social media, newspapers, mobile phones, satellite images, etc. Representative samples and reliable measurements are necessary for developing evidence-based public policy.
Faculty
Colonel William J. Walsh Professor of American Government, Department of Government and McCourt School of Public Policy
Professor
Professor
Crnkovich Family Business of Health Chair
Professor and Operations and Information Management Area Chair
Associate Professor
Associate Professor | AG Field Chair
Associate Professor
Professor
Department of Psychology, Professor
McCourt School of Public Policy, Assistant Professor
Director, Massive Data Institute
Sonneborn Chair | Chair and Professor, Department of Computer Science | Professor, McCourt School of Public Policy