Event box

VIRTUAL Esri Spatial Statistics Workshop II: Making Predictions with Spatial Statistics

VIRTUAL Esri Spatial Statistics Workshop II: Making Predictions with Spatial Statistics In-Person

INSTRUCTORS: Alberto Nieto and Ankita Bakshi, Esri Spatial Statistics Team

Headshot of co-instructor Alberto NietoHeadshot of co-instructor Ankita Bakshi











Modeling makes it possible to better understand events, estimate values, and predict occurrences. This workshop starts by covering how Geographically Weighted Regression is used to model, using geography to calibrate the factors that help you predict. Next, you’ll learn how Forest-based Classification and Regression make the random forest method accessible to improve predictions. Finally, you'll see the new Presence-Only Prediction tool, which uses a maximum entropy approach to predict the location of phenomena without requiring explicit absence data. Through discussions and demonstrations, we will learn how these methods work, considerations and best practices for running each tool, and strategies for interpreting and refining results.

Software Used: ArcGIS Pro

Prerequisites: Basic experience in ArcGIS Pro’s functionality, including the ability to create and open projects, load layers, and use geoprocessing tools.

REGISTRATION: To confirm your registration, please complete the pre-workshop survey. The registration link is available below.

Learning Objectives

  • To understand the motivations behind modeling and regression analysis in GIS.
  • To characterize the different regression and predictive analysis tools available in the Spatial Statistics toolbox in ArcGIS. 
  • To learn to make appropriate decisions about regression analysis methods and parameters depending on the problem.
  • To learn how to take advantage of data processing tools in ArcGIS for predictive analysis.
  • To learn how the following statistical analysis tools work and how to apply them in your own work:
    • Generalized Linear Regression
    • Geographically Weighted Regression
    • Multiscale Geographically Weighted Regression
    • Forest-based Classification and Regression 
    • Presence-only Prediction (MaxEnt)

Before you join via Zoom

  • Answer the pre-workshop survey we will send prior to the workshop
  • Please test your Zoom connection at zoom.us/test
  • If you currently do not have access to ArcGIS Pro, please prepare in advance: 

Please email gishelp@yale.edu with any questions about this workshop.

LOCATION: Zoom (Link will be e-mailed to registrants)

Related LibGuide: Geographic Information Systems at Yale by Miriam Olivares

Friday, September 30, 2022
12:00pm - 1:30pm
Time Zone:
Eastern Time - US & Canada (change)
Zoom Session - CSSSI (online only_1)
  GIS & Geospatial     Marx Science and Social Science Library  
Registration has closed.

Event Organizer

Profile photo of Miriam Olivares
Miriam Olivares