DETERMINATION OF CRIME PATTERN IN KADUNA STATE USING PRINCIPAL COMPONENT ANALYSIS AND MULTIDIMENSIONAL SCALING
Keywords:Crime Pattern, Principal Component, Multidimensional Scaling, Euclidean Distances, Dhat Matrix, STRESS Function
Crime is a complex event occurring in a real spatio-temporal environment. Understanding crime patterns requires both theory and research. The study used secondary data collected from the 23 Divisional Police Headquarters (DPHs) on all the 23 Local Government Areas (LGA) of Kaduna State. The analysis was carried-out using multivariate approaches of Principal Component Analysis and multidimensional scaling. The results shows that three components were retained which collectively accounted for about 85% of the total variability in the data and individually, the first, second and third PC accounted for 42.4%, 25.5% and 16.9% of the total variability in the data respectively. On the other hand, The Euclidean Distance map shows that grievous hurts, assaults, rape, murder and kidnapping are closely compact. This means that these crimes are closely related as people commit them in Kaduna State.It is therefore recommended that further research should be conducted to cover three geo-political zones in the northern Nigeria in particular or the country at large; this would further assist towards addressing the recent problems of insecurity affecting our there
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