This document discusses exploratory spatial data analysis (ESDA) and the software GeoDa. It defines ESDA as the visualization and exploration of data that takes geographic location into account to identify patterns like clusters and outliers. The document explains that GeoDa is a free, open-source software for ESDA developed by Dr. Luc Anselin. It can be used to create choropleth maps, histograms, scatter plots, and identify clusters through tools like box maps and multivariate LISA. Examples using health and demographic data from Rwanda are provided to demonstrate GeoDa's univariate and multivariate analysis features.

1. Getting to Know Your Data:
Exploratory Spatial Data Analysis
with GeoDa
MEASURE GIS Working Group Meeting
26 June 2012
James Stewart
MEASURE Evaluation

2. Overview
 What is Exploratory Spatial Data Analysis
(ESDA)?
 What is GeoDa?
 GeoDa in action

3. Exploratory Spatial Data Analysis
 Visualization and
exploration that
take geographic
location into
account
 Identification of
interesting patterns
(e.g., clusters and
outliers)

4. Exploratory Spatial Data Analysis
 Data-driven,
bottoms-up
approach to
generating
hypotheses
 Provides foundation
for spatial modeling
to explain patterns
(includes OLS)

5. GeoDa
 Short for Geographic Data Analysis
 Developed by Dr. Luc Anselin, now at Arizona
State University
 As of Oct 2011, downloaded over 62,000 times
(since release in Feb 2003)

6. GeoDa
 Latest version is OpenGeoDa
 Free and open source
 Cross-platform
 Windows (XP, Vista, and 7)
 MacOS
 Linux
 Run-time executable requires no installation; can
run from anywhere

7. GeoDa in Action
GeoDa toolbar
 Beginning map
window
 Data must be in
shapefile format

8. GeoDa in Action: Univariate
 Choropleth map: quantile, percentile, box map,
standard deviation
 Histogram
 Cluster analysis

9. Box Map and Box Plot
Rwanda by District, 2010
Percent HIV Positive among Box
Women Age 15-49 Map
Outliers Box
1.5 x IQR Plot
Q3
mean
median
Q1
Source: Rwanda DHS 2010
1.5 x IQR

10. Can Add Histogram

11. All Data Views are Linked

12. All Data Views are Linked: Points

13. Can Identify Clusters / “Hot Spots”

14. GeoDa in Action: Multivariate
 Side-by-side comparison
 Scatter plot
 Standardized scatter plot (correlation plot)
 Multivariate LISA (cluster analysis)

15. Side-by-Side Comparison
Rwanda by District, 2010
Rwanda by District, 2010 Women Age 15-49 using
HIV Prevalence among Any Modern Method of
Women Age 15-49 Contraception
Source: DHS 2010 Source: DHS 2010

16. Scatter Plot
Rwanda by District, 2010
HIV Prevalence vs. Median Yrs Education
Among Women Age 15-49
Source: DHS 2010

17. Standardized Scatter Plot
Source: DHS 2010

18. Multivariate Cluster Map (LISA)

19. Summary
 ESDA can help visualize data and formulate
hypotheses
 GeoDa is an easy-to-use but powerful tool for
ESDA
 GeoDa is free and open source

20. For more information
 Visit http://geodacenter.asu.edu/
 Tutorials
 Videos
 Documentation
 Detailed glossary
 Publications
 Working papers

21. MEASURE Evaluation is a MEASURE project funded by the
U.S. Agency for International Development and implemented by
the Carolina Population Center at the University of North Carolina
at Chapel Hill in partnership with Futures Group International,
ICF Macro, John Snow, Inc., Management Sciences for Health,
and Tulane University. Views expressed in this presentation do not
necessarily reflect the views of USAID or the U.S. Government.
MEASURE Evaluation is the USAID Global Health Bureau's
primary vehicle for supporting improvements in monitoring and
evaluation in population, health and nutrition worldwide.