Detection of Atypical Data (Outliers) for the Reduction of the Homicide Rate in Colombia
Synopsis
The use of statistical methodologies for data estimation and analysis in organizations has proven to be highly beneficial for constructing and describing social scenarios, supporting assertive decision-making in aspects related to citizen, public, and human security where crimes occur.
The main objective of this chapter is to adopt the box and whisker diagram to identify outlier statistical data, concerning the occurrence of homicides in the quadrants of the National Community Surveillance Model by Quadrants (MNVCC) of the National Police of Colombia during the year 2021.
A verification of the National Police databases will be conducted, and the boxand-whisker diagram will be applied to group the quadrants into quartiles based on the historically recorded number of homicides. This will allow for the recognition of quadrants that exhibit atypical behavior regarding homicides, specifically those that concentrate more than 50% of urban homicides, referred
to as outlier quadrants. Following this identification, preventive, anticipatory, and operational strategies will be deployed to reduce crime incidence.
In conclusion, identifying outlier data and implementing institutional actions aimed at countering crime has led to a historical reduction in homicide cases in urban areas of the country over the past 19 years.
Pages
87 - 111
Published
September 26, 2024
Series
Copyright (c) 2024 National Directorate of Academies Editorial
