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HOMICIDE PREDICTIONS St. Louis 2013 Group A: Derek Clardy Maria Kattia Del Rio Tomita Seungyoon Kim Tamara Pokol

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Homicide predictions. St. Louis 2013 Group A: Derek Clardy Maria Kattia Del Rio Tomita Seungyoon Kim Tamara Pokol. Approach. St. Louis 14 th Most Dangerous. Downtown West was ranked 14 th most dangerous A report based on F.B.I data back in 2010. St. Louis Homicide Historical Data. - PowerPoint PPT Presentation

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Page 1: Homicide predictions

HOMICIDE PREDICTIONSSt. Louis 2013Group A:Derek ClardyMaria Kattia Del Rio TomitaSeungyoon KimTamara Pokol

Page 2: Homicide predictions

Approach

Collect Historical

Data• Number and place of murders

Build a Regression Model

• Factors to be considered• Factors available• Build a regression model

Forecast Murder

• Number and place of murders

Page 3: Homicide predictions

St. Louis 14th Most Dangerous

• Downtown West was ranked 14th most dangerous• A report based on F.B.I data back in 2010

Page 4: Homicide predictions

St. Louis Homicide Historical Data

1985 1990 1995 2000 2005 2010 2015 -

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Murder and Nonnegligent Manslaughter

Num

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ders

Page 5: Homicide predictions

St. Louis Homicide by Police District

Police Patrol

District Number 2008 2009 2010 2011 2012

South 1 10 9 10 12 12

South 2 1 2 4 2 2

South 3 11 13 10 16 13

Central 4 12 12 7 11 6

Central 5 19 26 30 17 18

North 6 44 27 40 26 32

North 7 35 29 21 15 15

North 8 17 17 15 13 8

Central 9 18 8 7 2 7

Page 6: Homicide predictions

Factors considered

CRIME

• Robbery• Forcible Rape• Aggravated Assault• Drug Enforcement

Arrest Data• Number of

Policeman

ECONOMIC

• Low Income Households (<$10,000)

• With Food Stamp Benefit

• Unemployed Civilians

• Unemployment rate

Page 7: Homicide predictions

Factors consideredDEMOGRAPHIC/

EDUCATION

• Divorced• Race• Men (18-65 years)• Men (15-44 years)• High School

Dropout Rate• Educational level

Other Factors

• Gun ownership• Gangs

concentration• Drug usage• Alcohol sales• Crime prevention

programs

Page 8: Homicide predictions

Factors Available & Correlation with Murder

CRIME

• Robbery: 0.85• Forcible Rape:

0.65• Aggravated

Assault: 0.78• Drug

Enforcement Arrest Data: (-0.64)

• Number of Policeman: -0.54

ECONOMIC

• Low Household Income Class: 0.79

• With Food Stamp Benefit: 0.79

• Unemployed Civilians: 0.78

• Unemployment rate: (-0.18)

DEMOGRAPHIC/ EDUCATION

• Divorced: 0.37• Race: White:

0.58 African American: 0.59

• Men 18-65 years: 0.36

• Men 15-44 years: 0.77

• High School Dropout Rate: 0.12

Page 9: Homicide predictions

Factors Selection• Correlation doesn`t mean causation!• Highly correlated factors• Build a reasonable model

• Factors used to build regression model:• Robbery in St. Louis• Aggravated Assault• Low Income Class• Unemployed Civilians• Black or African American• Men 15-44 years

63 potential models!

Page 10: Homicide predictions

Best Fit Regression Model

• Regression line:Number of murders=(-405.90559)-(0.08864*Robbery)+(0.00035*Low Income Class)+(0.00460*Black or African American)

• Model:P=0.0327=<0.05 R square=0.98 Standard Error of Estimate=4.1

2006 2007 2008 2009 2010 2011 201270

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Murder and Nonnegligent Manslaughter

Actual ValuesFitted Values

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Page 11: Homicide predictions

2013 ForecastBased on Homicide Statistics 1985-2012

Exponential Smoothing

Holt`s Method Moving Average

Forecasting Constant

Alfa: 0.92 Alfa: 1, Beta:0 Span: 3

Forecasting Error*

17.10% 16.91% 18.79%

Forecast 2013 113.08 111 113.5

*Mean Absolute Percentage Error

Page 12: Homicide predictions

2013 Forecast – Holt`s Method

• Accuracy: 16.91% mean absolute percentage error

• 111 murders are forecasted for 2013

1985

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2013

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Forecast and Original Observations

Murder and Nonnegligent ManslaughterForecastMurder and Nonnegligent Manslaughter

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Page 13: Homicide predictions

2013 ForecastNumber of Murders by Police District

• 58% of all murders was committed in district 5, 6, and 7• 65 out of 111 murders predicted to be in three districts

Police Patrol

District Number

% of Total Murders

2008-2012 Years

Number of Murders Forecasted 2013

South1 8% 02 2% 23 9% 10

Central 4 7% 85 16% 18

North6 25% 287 17% 198 10% 11

Central 9 6% 7100% 111

Page 14: Homicide predictions

Conclusion• Our regression model is better than the best forecasting

technique• Useful model for predictions

• The model can be extended:• Include more data: buy statistics (e.g. divorce by year), FBI

historical data• Our model can be used to support decision-making in

different industries: • Health Care• Security • Investment Opportunities• Community Services

Page 15: Homicide predictions

Microsoft Excel Worksheet

Questions?

Page 16: Homicide predictions

References• St Louis Police Department: http://www.slmpd.org/• Missouri Census Data Center: http://

mcdc1.missouri.edu/cgi-bin/acsprofiles/acsprofiles.py?period=2006&geoids=16000US2965000&subjects=Demographic&subjects=Economic&subjects=Social&subjects=Housing

• Crime Reports: https://www.crimereports.com/map/index/?search=1200+Clark%20Avenue+St.%20Louis+MO&agencyzoomlevel=

https://www.crimereports.com/map/index/?search=1200+Clark%20Avenue+St.%20Louis+MO&agencyzoomlevel

=• KMOV News: http

://www.kmov.com/news/local/St-Louis-ranks-14th-as-most-dangerous-neighborhood-89951832.html