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A spatial outlier is a spatially referenced object whose non spatial attribute value is significantly different from the corresponding values in its spatial neighbourhood. In other words, a spatial outlier is a local instability, or an extreme observation which deviates significantly in its spatial neighbourhood, but may not be in the entire data set. In this paper, we have applied the well-known mean algorithm for detecting spatial outliers in the multiple attributes state wise crime data and predicted which states need more attention from the government so as to reduce crimes there. We have also done regression analysis between the populations of age group 15-19 years and separately for population of age 15 years with the crimes data of all states.

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