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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 11, ISSUE 3, MARCH 2022

Prediction on requirement of police recruitment on the basis of community population and rate of violent crimes where Colored (Afro) Americans live

Anand Kumar Jha, Prithwish Raymahapatra, Nandini Ghosh, Sayantika Bose, Sulekha Das

DOI: 10.17148/IJARCCE.2022.11389

Abstract: There is a general tendency that effective police force has a significant protective effect on violent crimes. The effect of police on crime operates through both a deterrence and an incapacitation way.The deterrence theory is based on the fact that an increase in capacity of police force enhances a typical offender’s chance of being caught and thereby decreases crime particularly those which are violent in nature.The police departments actively focus their resources on the incapacitation of individuals posing the greatest risk to society, which make the incapacitation channel also an important factor. In this perspective adequate human resources (deployed police personnel) play a vital role. This article goes on to explore the relationship between population of a community of coloured (Afro-American) people, number police staff employed and violent crime occurrences in particular. The findings from this paper suggest that numbers of police recruited/ employed for maintaining law and order of a community/ area with coloured (Afro-American) inhabitation depend on population of that community/area and number of prevalent violent crimes. Our findings suggest that higher numbers of police not only reduce crime rates but also increase the share of crime, and in particular violent crime. This data will be analyzed using multiple linear regression in machine learning method using python programming language.

Keywords: Forecast; data Science, data analysis, Regression analyses; Stepwise multiple regression

How to Cite:

[1] Anand Kumar Jha, Prithwish Raymahapatra, Nandini Ghosh, Sayantika Bose, Sulekha Das, “Prediction on requirement of police recruitment on the basis of community population and rate of violent crimes where Colored (Afro) Americans live,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2022.11389