#### Overview of this book

Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data.
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Introduction to Spatial Statistics in ArcGIS and R
Measuring Geographic Distributions with ArcGIS Tools
Analyzing Patterns with ArcGIS Tools
Modeling Spatial Relationships with ArcGIS Tools
Working with the Utilities Toolset
Introduction to the R Programming Language
Creating Custom ArcGIS Tools with ArcGIS Bridge and R
Application of Spatial Statistics to Crime Analysis
Application of Spatial Statistics to Real Estate Analysis

## The Standard Distance and Directional Distribution tools

The `Standard Distance` tool measures the degree to which features are concentrated or dispersed around the geometric mean center. It shows the concentration or dispersal of data. The output circle created by this tool is defined by standard deviation and can include one, two, or three standard deviations. In general, the larger the circle, the more dispersed the data.

The `Directional Distribution (Standard Deviational Ellipse)` tool creates standard deviation ellipses to summarize the spatial characteristics of geographic features, including central tendency, dispersion, and directional trends. The ellipses are centered on the mean center. This tool calculates directionality, centrality, and dispersion.

In this exercise, you'll learn how to use both tools.

### Preparation

In `ArcMap`, open the `C:GeospatialTraingSpatialStatsDenverCrime.mxd` file. You should see a point feature class called `Denver Burglary`, as shown in the following screenshot. These...