St. Louis Homicide by Police District Police Patrol District Number20082009201020112012 South1 109 12 South2 12422 3 1113101613 Central4 12 7116 Central5 1926301718 North6 4427402632 North7 35292115 North8 17 15138 Central9 188727
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
Factors considered DEMOGRAPHIC/ 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
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
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!
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
2013 Forecast Based on Homicide Statistics 1985-2012 Exponential Smoothing Holt`s MethodMoving Average Forecasting Constant Alfa: 0.92Alfa: 1, Beta:0Span: 3 Forecasting Error* 17.10%16.91%18.79% Forecast 2013113.08111113.5 *Mean Absolute Percentage Error
2013 Forecast – Holt`s Method Accuracy: 16.91% mean absolute percentage error 111 murders are forecasted for 2013
2013 Forecast Number 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 South 18%0 22%2 39%10 Central 47%8 516%18 North 625%28 717%19 810%11 Central96%7 100%111
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
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