Statistics and police activities are too often regarded as two distant domains: on the one side, police urgently need to solve individual cases; on the other, statistics by definition deal with the collection, analysis and interpretation of data related to aggregates. So, to what extent might statistics be useful to police officers in their daily activities? This is the key question addressed by this article. In offering an answer, it reviews traditional and innovative approaches where statistics – both simple (including basic numbers such as averages or distances between places) and more advanced – may support police in: 1) understanding the spatial and temporal distribution of crime (section 2, on crime mapping), thus improving their knowledge as to the best places and times to intervene in order to reduce the amount of crime occurring in a given area; 2) identifying offenders (section 3, on geographical offender profiling); 3) predicting crimes (section 4, on prospective hot-spotting). The article ends with some concluding remarks.
Vettori, B., “The contribution of statistics to police activities”, in Aa.Vv, A., White paper on best practices in asset recovery, Ministerio del Interior, Madrid 2012: 215-227 [http://hdl.handle.net/10807/63112]
“The contribution of statistics to police activities”
Vettori, Barbara
2012
Abstract
Statistics and police activities are too often regarded as two distant domains: on the one side, police urgently need to solve individual cases; on the other, statistics by definition deal with the collection, analysis and interpretation of data related to aggregates. So, to what extent might statistics be useful to police officers in their daily activities? This is the key question addressed by this article. In offering an answer, it reviews traditional and innovative approaches where statistics – both simple (including basic numbers such as averages or distances between places) and more advanced – may support police in: 1) understanding the spatial and temporal distribution of crime (section 2, on crime mapping), thus improving their knowledge as to the best places and times to intervene in order to reduce the amount of crime occurring in a given area; 2) identifying offenders (section 3, on geographical offender profiling); 3) predicting crimes (section 4, on prospective hot-spotting). The article ends with some concluding remarks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.