Case08C-Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago

Chapter 8 Spatial Statistics and Applications

Spatial statistics analyzes the pattern, process and relationship in spatial (geographic) data. This chapter implements some fundamental tasks in spatial statistics: measuring geographic distributions, spatial cluster analysis, and spatial regression models. Section 8.1 uses a case study on place names in Yunnan, China, to illustrate the implementations of various centrographic measures and point-based spatial clustering. Section 8.2 employs a case study to demonstrate the methods for detecting global and local colocation patterns of two types of points (here crimes and facili ties). Section 8.3 applies spatial cluster analysis and spatial regression in a case study of homicide patterns in Chicago.

Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago

The following data sets are provided in the subfolder ChiCity under the study area folder Chicago :
1.A polygon feature citytrt.zip contains 846 census tracts in the City of Chicago (excluding the O’Hare airport tract) with fields CNTYBNA (tract id), POPU (population in 1990), JA (job accessibility) and CT89 _ 91 (total homicide counts for 1989–91).

2. A text file cityattr.csv contains cntybna (tract id) and 10 socioeconomic attributes represented by columns Field 2-11 based on the 1990 census (families below the poverty line, families receiving public assistance , female-headed households , unemployment , new residents who moved in the last five years, renter-occupied homes, residents with no high school diplomas , crowded households with an average of more than 1 person per room, Black residents, and Latino residents).

Computational Methods and GIS Applications in Social Science - KNIME Lab Manual
Lingbo Liu, Fahui Wang

External resources

• Github for Workbook Issue Report
• Github for Geospatial Analytics