Predicting
Homicides in St.
Louis City for 2013
Chad Iseman - Geoff Hickman - Jon
Perkins - Yanhui Long - Mustafa Khalili
Objective
The ability to accurately predict when and
where homicides will occur in the City of St.
Louis grants us the ability to effectively
allocate resources to prevent those crimes.
We will use statistical techniques and historical
data sets to predict where homicides will
occur in the city in 2013.
Approach
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Collect Data
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Obtained 4 years of St. Louis city crime-related data by district
Obtained demographic and socioeconomic data from 2010 census by
district
Obtained weather and gas price historical data
Data Analysis
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Analyzed data for correlations
Conducted regression analysis to predict the number of district
homicides for 2013
Conclusion
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Recommend increased police resource in districts with predicted high
homicide counts in 2013
Saint Louis City
Estimated population of
350,000.
Divided into 79 government
designated neighborhoods
and further divided into 9
districts.
Ranked 3rd most dangerous
city in 2012 with 1,857
violent crimes per 100,000
people, and 58.7 forcible
rapes per 100,000 people.
Definitions
Homicide is the killing of a human being due to
the act or omission of another. Included
among criminal homicides are murder and
manslaughter.
Non-criminal homicides include killing in selfdefense, a misadventure like a automobile
wreck, or legal government execution.
[dictionary.law.com]
Why Districts?
The City of St. Louis is
divided into 9 Police
Districts. This makes
access to crime data
precise and reliable.
Using data referencing the
9 districts also allows us
to present more
meaningful
recommendations.
Factors We Thought That Affect
Crime
Gang activity
Municipal budget
Weather
Consumer price index
Gasoline prices
Sports teams performance
Riots
Drug use
Health
Population density
Demographics:
Marital status
Age
Race
Income
Employment status
Education level
Poverty level
Housing (multi or single)
Household income
Based on 2010 Census
Hypothesis: Crime takes
place, in large part, due
scarcity or resources.
Household income attempts
to quantify each Districts
challenges to provide
adequate food, shelter and
transportation.
District 1
$ 28,499.66
District 2
$ 38,016.40
District 3
$ 25,880.64
District 4
$ 13,957.68
District 5
$ 19,353.00
District 6
$ 24,155.81
District 7
$ 20,686.00
District 8
$ 20,724.00
District 9
$ 26,261.15
Poverty Rate
Based on 2010 Census
Similar to average
household income, the
poverty rate also
attempts to quantify
each Districts
challenges to provide
adequate food, shelter
and transportation.
District 1
24.63%
District 2
9.07%
District 3
42.17%
District 4
69.66%
District 5
56.38%
District 6
36.68%
District 7
44.73%
District 8
40.46%
District 9
29.02%
Unemployment
Based on 2010 Census
District 1
7.65%
District 2
4.00%
District 3
12.39%
District 4
26.49%
District 5
22.09%
District 6
16.36%
District 7
14.25%
District 8
15.28%
District 9
13.67%
Total crimes per person (all crimes)
Visually, you can see
that the areas with the
highest unemployment
and poverty, and the
lowest household
income overlap with
crime.
Based on 2010 Census
Murders - victims per 100 people
Based on 2010 Census
District 1
0.017
District 2
0.000
District 3
0.140
District 4
0.000
District 5
0.742
District 6
0.358
District 7
0.278
District 8
0.000
District 9
0.000
Homicides vs Temperature
Homicides vs Avg. Gas Price
Prediction Improvements
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Monthly Gang activity by district
Monthly Police budget data by district
Homicide categorization (gang related, vehicular, etc.)
Gun owners by district updated monthly
Average rent/mortgage payment by district
Drug users by district per month
CPI by district by month
Prediction Model
We used the following factors to construct our homicide
prediction model:
Rape incidents
Armed robbery reports
Total aggravated assaults
Temperature
Time of year
Total aggravated assaults and armed robbery had the
highest correlation with homicides.
2013 Homicide Count Prediction = 114
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Our Recommendations
• Dispatch additional resources to
Districts 5,6, and 7 during the second
half of the year.
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These additional resources can be
allocated from Districts 1 and 2 during
the time period.
Conclusion
Our prediction model can be used by police
resource managers to ensure that potential
homicide hot spots have adequate police
officers in the area.