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This event is part of the Harvard Affiliate Only Spatial Data Science Workshop Series. January, 21, 2022 | 12:00 PM ET Course Description: Whenever we look at a map, we naturally organize, group, differentiate, and cluster what we see to help us make better sense of it. This workshop will explore powerful spatial statistics techniques designed to do just that in space and time. We’ll start with statistical cluster analysis methods, such as Hot Spot Analysis and Cluster and Outlier Analysis. We will then present advanced space-time pattern mining techniques, including aggregating and visualizing temporal data into a Space Time Cube and running an Emerging Hot Spot Analysis. Through discussions and demonstrations, we will learn how these techniques work, the types of questions each tool can answer, best practices for running the tools, and strategies for interpreting and sharing results. The workshop will focus on a use case that examines racial disparities in police stops. Panelists: Lauren Bennett Alberto Nieto Lynne Buie Ankita Bakshi Cheng-Chia Huang Eric Krause Jie Liu Kevin Butler Xiaodan Zhou