1. Homicide Predictions : Saint Louis City IS6833 February 28, 2010 Group B: Chris Gaynor Robert Jones Kevin Prinke Poernomo Wikandjojo

2. The Problem Create a model to predict the 2010 Saint Louis homicides by geographical location.

3. The Background St. Louis was founded in 1764 and incorporated in 1822 Current Estimated Population of 354,361 Divided into 79 different neighborhoods Murder Rate is 2.8 times the national average

4. The Approach Macro: Predict the total numbers of homicides for 2010 based on past macro level demographics Micro: Predict the density of homicides per neighborhood based on trend in crimes

5. Macro Level Model Team investigated correlation of local demographic and economical data to yearly murder rates Total PopulationUS Decennial Census2000 American Community Survey2001-2008 % of Males – 15-24US Decennial Census2000 American Community Survey2001-2008 % of Single Family HouseholdsUS Decennial Census2000 American Community Survey2001-2008 % of PovertyUS Decennial Census2000 American Community Survey2001-2008 Unemployment RateBureau of Labor and Stats2000-2008 High School Drop-Out RateMissouri Kids Counts / Saint Louis Public School Report Card 2000-2009 Crime StatisticsFBI Uniform Crime Reports2000-2004 Saint Louis Police Department2005-2009

6. Factor Correlation with Murders FactorCorTrend Total Population0.502 % of Males 15-240.859 % of Single Family Households 0.051 % of Poverty-0.118 Unemployment Rate-0.110 High School Dropout Rate0.642 Compared 2000-2008 Removed 2003 data because low homicide rate % of Males 18-24 and High School Dropout rate observed the highest correlation

7. Model Comparison Total Population, % of Males 15-24 and High School Drop Out Rate Standard Error – 11.27 R Square -.787 F Significance Probability -.079 A Reduced to remove High School Drop Out Rate Standard Error – 11.20 R Square -.738 F Significance Probability -.035 B

8. Best Fit Model Model A was used to predict the macro level murder rate Equation: # of Murders = 67.45 + 104.20(HS Dropout Rate)+ 1881.58(% of Males 15-24) - 0.00022 (Total Population) Model A Estimate: 153. Increase by 10 from 2009

9. Micro Level Model Team created a weighted average model for crimes by neighborhood from 2005-2009 – Murder – Drop out rate – Age demographics Property crime excluded – low correlation Weighted Average – Homicide (.975) – Personal Crime (.025) – Yearly homicide rate (weighted by year)

10. Micro Level Model Weighted % contribution of homicides Weighted % of personal crimes Total Weight Convert weighted number into a percentage (% contribution of homicides in St. Louis) Use macro model prediction of total homicides and % contribution of micro model to determine the number of homicides by neighborhood

11. Predictions by Neighborhood Red – > 7Orange – 5-7Yellow – 3-4Blue – 1-2Green – < 1 153

12. Yearly Changes : 2009 - 2010 Red – > 2Orange – 1-2Yellow – 0-1Blue – No changeGreen – Decrease >= 1 9

13. Improving Our Prediction Yearly Data by Neighborhood Average income Population demographics Predictive Crime Statistics Gang activity by neighborhood Drug related crimes Categorization of homicides for influential trend factors Governmental Influence Factors Yearly police budgets Civic progress initiatives Other Modeling Capabilities Spatial impacts between different homicides Citizen Survey Feedback Time and Money

14. Conclusion Allocate additional resources in District 3 to prevent homicide increase – Dutchtown – Gravois Park Allocate resources in District 5 & 7 – OFallon – Fairground – Wells / Goodfellow