Data Analysis: Insights on Crime in Chicago

This article provides insights on crime in Chicago obtained through data analysis. It covers aspects such as types of crimes, location of crimes, day of the week when crimes are committed, and the arrest frequency against reported cases. The article also includes a cover letter to the Chicago Police Department with recommendations on how to improve the security of Chicago, and a reflection on the challenges faced during the data analysis project. References are provided at the end of the article.

Running head: DATA ANALYSIS 1
Data analysis
Name
Institution

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Contents
Task 3 – Advanced Insights.................................................................................................3
Task 6 – Cover letter............................................................................................................3
Task 7 - The Reflection:......................................................................................................4
References............................................................................................................................5

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Task 3 – Advanced Insights
 Chicago has a low safe city index due to the high domestic crimes reported per year
(Zimring, 2011).
 The Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and
Reporting) system has a very low crime clearance rate because arrests are never made in
most of the reported crime cases.
 Narcotics crimes has the highest crime clearance rate while theft crimes has the lowest
crime clearance rate.
 Residential areas and the streets are the crime hot spots in Chicago. This means that there
is high prevalence of crimes in this areas (Chainey, 2008).
 People absence from their residence on the day of worship is a predisposing factor for
crime.
Task 6 – Cover letter
Police chief
Chicago police
26th September 2018
Dear sir/madam
I am a data analyst currently working for Federation University Australia. In the data analysis
project, I used the Watson analytic software to analyze the information about the crimes in
Chicago. I have considered different aspects of the crimes as you provided. Some of the aspects I
analyzed are types of crimes, location of the crimes, day when the crime was committed, and the
arrest frequency against the reported cases among others. After the data analysis, there are very

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important insights I obtained and concluded that will be very crucial for you in the endeavor of
improving the operations and in laying of strategies in order to improve the overall security of
Chicago. Some of these insights are discussed below.
The crime clearance rate of Chicago, especially the theft crimes is low. This means that the ratio
of the crimes reported to the crimes cleared ( Mahony, 2012), is low. This therefore calls for
much effort to improve this condition. The residential areas and the streets are the areas that are
has high crime cases. This calls for increased patrols in this areas especially on Sundays, the day
when the crime cases committed are very high. This will help reduce the crime cases in Chicago
and hence increase its safe city index (Helms, 2016).
Theft is the principle damage crime in Chicago but surprisingly, only a very small number theft
crime perpetrators are arrested. This shows that something must be done in order to ensure that
these perpetrators never go scot free so as to reduce the occurrence of these crime cases.
It is my hope that the information I provide will be of much help to you and that you will
consider my recommendations in order to improve the security of Chicago.
Task 7 - The Reflection:
In obtaining data analysis skills, the project has imparted so much to us. This knowledge
obtained is very crucial in our academics in future. The project also gave us an opportunity to use
the Watson Analytic Software and hence helped us learn its basics and also the usage.
However, the whole project was not without challenges. The use of these software being
a new software to many of us in the group was challenging and this took much of our time.
Drawing of the conclusions of the analyzed data was also not a walk in the park as we had to pull

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all the group members efforts in coming up with complete, concrete and comprehensive
conclusions of the data.
References
Zimring, F. E. (2011). The city that became safe: New York's lessons for urban crime and
its control. Oxford University Press.
Helms, G. (2016). Towards safe city centres?: remaking the spaces of an old-industrial
city. Routledge.
Mahony, T. H., & Turner, J. (2012). Police-reported clearance rates in Canada, 2010.
Ottawa: Statistics Canada.
Curran, F. C. (2014). The Impacts of the Chicago Welcoming Schools' Safe Passage
Program on Student Safety and Crime. Society for Research on Educational Effectiveness.
Chainey, S., Tompson, L., & Uhlig, S. (2008). The utility of hotspot mapping for
predicting spatial patterns of crime. Security journal, 21(1-2), 4-28.

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