Title: Analyze crime using statistics and the R-ArcGIS Bridge | Learn ArcGIS
Headings: Analyze crime using statistics and the R-ArcGIS Bridge
Analyze crime using statistics and the R-ArcGIS Bridge
This lesson will be retired in May 2021. New R-ArcGIS bridge lessons will be published in the future.
Requirements
Install the R-ArcGIS bridge and start statistical analysis
Download R and RStudio
Create an ArcGIS project
Install the R-ArcGIS bridge
Aggregate point data by counts within a defined location
Analyze crime hot spots
Enhance your data with additional attributes
Add additional attributes to your dataset
Prepare your dataset for additional analyses
Perform statistical analysis using R and ArcGIS Pro
Bridge your data into R
Calculate smoothed crime rates
Continue analysis in ArcGIS Pro
Identify areas with unusually high crime rates
Identify attributes that influence crime
Create a correlation matrix in R to evaluate attribute relationships

Content: Conversely, the dark blue bins are persistent cold spots. These are areas where crime is statistically, and persistently, less prevalent. The light blue outlined bins are intensifying cold spots but means the opposite of its counterpart. Clusters of low crime counts in these cells are becoming more intense over time. In other words, the cold spots are getting colder. The department needs to be especially concerned about the areas where crime is persistent or intensifying. They may move resources to these areas from the places where crime cold spots occur. Save the project. You installed the R-ArcGIS bridge, prepared your data for statistical analysis, and started using some of the available tools. Next, you'll add additional attributes to your dataset, allowing you to draw conclusions from your analysis about what factors likely influence the