Beyond Where: Modeling Spatial Relationships and Making Predictions
This workshop will cover regression analysis concepts for the analysis of geographic data. Using these statistical methods in many areas (e.g., business, public health, natural resources) allows you to examine, model, and explore data relationships to help answer questions such as “why do we see so much disease in particular areas?” Regression analysis also allows you to predict spatial outcomes for other places or time periods. Application and use of ordinary least squares regression (OLS) and geographically weighted regression (GWR) will be demonstrated. You will learn how to build a properly specified OLS model and interpret the results and diagnostics. The latest advancements in regression and prediction in ArcGIS will be covered.

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Statistical Cluster Analysis and Space-Time Analysis Workshop

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Esri 2014 UC Tech Session: Modeling Spatial Relationships Using Regression Analysis

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Integrating R and ArcGIS for Advanced Analysis

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Using Spatial Statistics to do More: Simple Approaches

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How to Conduct Ordinary Least Squares and Multiscale GWR Modeling in ArcGIS Pro: Theory and Practice

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Spatial Data Mining I: Essentials of Cluster Analysis

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The Forest for the Trees: Making Predictions using Forest-Based Classification and Regression

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Enhancing Qualitative Social Science with GIS

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AlphaFold - The Most Useful Thing AI Has Ever Done

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Dive Into ArcGIS Pro 3.0 - Introduction to Multiscale Geographically Weighted Regression Analysis

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Beyond Where: Modeling Spatial Relationships and Making Predictions

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Spatial Data Mining II: A Deep Dive into Space-Time Analysis

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Spatial Statistics in R: An Introductory Tutorial with Examples

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Workshop on Multiscale Geographically Weighted Regression (MGWR)

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Predictive Modeling Through Spatial Analysis & Data Science

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Geographically Weighted Regression

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Doing More with Spatial Analysis: An Introduction to Spatial Statistics

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How Maxwell's Equations Were Discovered

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Applying Spatial Statistics: The Analysis Process in Action

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