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	Crime Hot Spot Analysis	Near-Repeat Analysis
Dziedzina	Criminology	Criminology
Rodzina	Process / pipeline	Process / pipeline
Rok powstania	1995	2003
Twórca	Lawrence Sherman & David Weisburd (policing); Arthur Getis & J. Keith Ord (statistic)	Michael Townsley, Shane Johnson & Kate Bowers
Typ	Spatial cluster detection for crime concentration	Space-time clustering test for crime contagion
Źródło pierwotne	Sherman, L. W., & Weisburd, D. (1995). General deterrent effects of police patrol in crime "hot spots": A randomized, controlled trial. Justice Quarterly, 12(4), 625–648.	Townsley, M., Homel, R., & Chaseling, J. (2003). Infectious burglaries: A test of the near repeat hypothesis. British Journal of Criminology, 43(3), 615–633.
Inne nazwy	Hot Spot Mapping, Crime Hotspot Detection, Getis-Ord Gi* Crime Analysis, Spatial Cluster Analysis of Crime	Near Repeat Calculator Method, Space-Time Near-Repeat Analysis, Near-Repeat Victimization, Contagion Crime Pattern Analysis
Pokrewne	4	4
Podsumowanie	Crime hot spot analysis identifies the places where crime concentrates far more than chance — the small number of street segments, blocks, or addresses that account for a large share of incidents. Building on Sherman and Weisburd's landmark demonstration that crime clusters tightly in space and that patrolling those clusters deters offending, the method uses spatial statistics such as the Getis-Ord Gi* local statistic to separate genuine, statistically significant clusters from random noise and to classify each place as a hot spot, a cold spot, or neither.	Near-repeat analysis tests whether crimes cluster in space and time beyond chance: after a crime occurs, are nearby locations at elevated risk for a short period? Developed in the early 2000s by Townsley, Johnson, Bowers and colleagues for burglary, it formalizes the 'contagion' or 'communicable disease' pattern of crime using a Knox space-time test against a Monte Carlo reference distribution.