Abstract:
Objective: Researchers always pay attention to grouping, classifying or reducing the dimension of objects or units to account relationships between them. Such relationships are described as similarity or dissimilatry between the objects or distance between the units. In grouping the objects and units statistical techniques such as Discriminant analysis and Clustring analysis are used. However, in less dimensional space, Multidemensional Scaling (MDS) and Bi-plot graphing analysis known as Graphing methods as well as Principal Component analysis and Factor analysis are used. In this study, overall crime rates were analyzed based on crimes committed against persons and properties in Turkey. Based on 81 provinces, crime committed against persons consisting of 10 sub-items and crimes committed against properties consisting of 5 sub-items were used to detect crime rates and to prevent crimes using the Multidimensional Scaling. Material and Methods: Based on data of judicial statistic for 2008, Multidimensional Scaling Method was used. Results: Regarding provential characteristics, Ankara, Istanbul, Van, Hatay, and Izmir were different compared to other provences and regarding crime types, crimes of public order, smuggling and trafic were different from the general trend. Conclusion: Preventive measures considering the results of provincial and crime related analyses, may contribute to reduce crime rates.