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Spatial Analytics with ArcGIS

You're reading from   Spatial Analytics with ArcGIS Build powerful insights with spatial analytics

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787122581
Length 290 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Eric Pimpler Eric Pimpler
Author Profile Icon Eric Pimpler
Eric Pimpler
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Table of Contents (16) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
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1. Introduction to Spatial Statistics in ArcGIS and R FREE CHAPTER 2. Measuring Geographic Distributions with ArcGIS Tools 3. Analyzing Patterns with ArcGIS Tools 4. Mapping Clusters with ArcGIS Tools 5. Modeling Spatial Relationships with ArcGIS Tools 6. Working with the Utilities Toolset 7. Introduction to the R Programming Language 8. Creating Custom ArcGIS Tools with ArcGIS Bridge and R 9. Application of Spatial Statistics to Crime Analysis 10. Application of Spatial Statistics to Real Estate Analysis

The Analyzing Patterns toolset


The Analyzing Patterns toolset, found in the Spatial Statistics Tools toolbox and shown in the following screenshot, contains a set of tools that perform pattern analysis against a dataset. Each of these tools returns statistical information about the entire dataset. The output of these tools is not a map, but rather statistical information that helps determine if a dataset is clustered, dispersed, or has a random pattern.

To help interpret the results of these tools, this section will provide information about the null hypothesis, p-values, z-scores, and standard deviations.

Understanding the null hypothesis

All the pattern analysis tools that we examine in this chapter work on the premise that our features or the values associated with those features are randomly distributed. This is known as Complete Spatial Randomness (CSR). This is the null hypothesis used with all the ArcGIS spatial statistics tools.

The pattern analysis tools return z-scores and p-values...

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