Statistical Analysis for the Traffic Police Activity: Nashville, Tennessee, USA

M. Tufail, S. Gul
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Abstract

Data Science is one of the fastest growing interdisciplinary field and has many applications in various disciplines. The actual motivation of data science came from John Tukey. In his seminal paper, in 1962, he presented the idea of data analysis which is now the field of data science. Several algorithms for data science related to statistical analysis have been developed and applied over variety of datasets since 1962. In this field, the significant development began with the aid of high performance computers that help to analyse a massive datasets. In this paper, we study the statistical analysis of the traffic stops in Nashville, Tennessee, USA for the year 2011--2021. Data is taken from the Stanford open policing project. Analysis is based on total number of 3071706 traffic stops. In this paper, we consider and investigate various aspects. This study comprises gender comparison (male vs female) and race comparison (black vs white) for different traffic offences. Complete findings and possible gaps are discussed in the conclusion.
交通警察活动的统计分析:美国田纳西州纳什维尔
数据科学是发展最快的跨学科领域之一,在各个学科中都有很多应用。数据科学的真正动机来自John Tukey。在他1962年发表的开创性论文中,他提出了数据分析的概念,这就是现在数据科学的领域。自1962年以来,一些与统计分析相关的数据科学算法已经开发并应用于各种数据集。在这个领域,重要的发展开始于高性能计算机的帮助下,它有助于分析大量的数据集。本文对美国田纳西州纳什维尔市2011- 2021年的交通站点进行了统计分析。数据来自斯坦福大学公开警务项目。分析基于3071706个交通站点的总数。在本文中,我们考虑和研究了各个方面。这项研究包括不同交通违例的性别比较(男性与女性)和种族比较(黑人与白人)。在结论中讨论了完整的发现和可能的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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