Determine which explanatory variables may act as consistent predictors for the 2024 US Presidential Election percentage Democrat vote.

This is a partial print out of the Exploratory Regression report generated using ArcGIS.
Exploratory regression is a spatial statistics tool that evaluates all possible combinations of the input candidate explanatory variables.

It looks for Ordinary Least Squares (OLS) models that can best explain the dependent variable within the context of user-specified criteria.

Exploratory Regression was Run with the following parameters:

Input features: CountyData_EnrichLayer Dependent Variable: PCT_DEM Candidate Explanatory Variables: 2016 Ave HH Income 2016 Diversity Index 2016 Population Density Percent Seniors (Age 65+) Percent Republican Percent Blue Collar Workers Percent Never Married Percent College Degree CDC SVI Index Percent Vaccinations



Check out the Jekyll docs for more info on how to get the most out of Jekyll. File all bugs/feature requests at Jekyll’s GitHub repo. If you have questions, you can ask them on Jekyll Talk.