Data Dimensions Presents: Spatial Statistics and Policing

Description

Join host Collin Paschall, program director and senior lecturer for the MS in Data Analytics and Policy program, for a discussion with Claire Kelling, an assistant professor of statistics at Carleton College in Northfield, Minnesota, on publicly available policing data and how communities can better understand how they are being policed.

This event is hosted by Advanced Academic Programs' MS in Data Analytics and Policy.

Publicly available policing data presents numerous opportunities for communities to better understand how they are being policed. However, limited data quality and complexities in policing data present opportunities and challenges for research in spatial statistics. This talk will focus on one particular challenge within the area of spatial analysis of policing data. Point process models rely on the availability of the precise location—for example, latitude/longitude coordinate—associated with each observed event. Uncertainty in point-level data sets is introduced for many reasons, such as privacy-preserving methods, geocoding algorithms, and data-gathering mechanisms. We introduce a new constrained jittering method and discuss implications for statistical utility and disclosure risk.