Analysis of crime data using principal component analysis: A case study of Katsina State

This paper analyses Katsina State crime data which consists of the averages of eight major crimes reported to the police for the period 2006 - 2008. The crimes consist of robbery, auto theft, house and store breakings, theft/stealing, grievous hurt and wounding, murder, rape, and assault. Correlation analysis and principal component analysis (PCA) were employed to explain the correlation between the crimes and to determine the distribution of the crimes over the local government areas of the state. The result has shown a significant correlation between robbery, theft and vehicle theft. While MSW local government area has the lowest crime rate, KTN local government area has the overall crime rate in the state. Robbery is more prevalent in DMS local government area, rape in JBA local government area, and grievous hurt and wounding in DDM local government area. The PCA has suggested retaining four components that explain about 78.94 percent of the total variability of the data set.