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ISART 2024 sought consensus on how to address the pressing challenge of developing, agreeing on, and applying radio frequency propagation models that take into account the impact of foliage and buildings—clutter—for planning of both spectrum policy and spectrum-dependent systems of all kinds. Tutorial: Building and Evaluating a Statistical Propagation Model The purpose of this tutorial was to guide attendees to build their own statistical propagation model based on clutter metrics derived from lidar data. Attendees were able to build, experiment, and evaluate their propagation models against real clutter measurement datasets. Each attendee was provided with a cloud-based Python programming environment accessible through the web browsers on their laptops (no software installation necessary). Example code and step-by-step instructions guided attendees to (a) measure clutter statistics from LiDAR data, (b) formulate a clutter loss model, and (c) assess their model’s generalizability against measurements in new clutter environments. No programming experience was necessary, but tutorial attendees had to have a computer with a browser and a GitHub account. o William Kozma, Jr., NTIA Institute for Telecommunication Sciences and Head of U.S. Delegation to ITU-R Study Group 3 o Max Hollingsworth, University of Colorado Boulder and NTIA Institute for Telecommunication Sciences