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Crime in St. Louis City in 2011 David Adams John Fields Leticia Garcia Shawn Kainady Chris Schaefer Travis Tatum.

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Presentation on theme: "Crime in St. Louis City in 2011 David Adams John Fields Leticia Garcia Shawn Kainady Chris Schaefer Travis Tatum."— Presentation transcript:

1 Crime in St. Louis City in 2011 David Adams John Fields Leticia Garcia Shawn Kainady Chris Schaefer Travis Tatum

2 Our Mission Mission: Use statistics and data sets to predict the number and location of unlawful homicides in St. Louis City in 2011. Concern: The CQ Press released the results of a study that named St. Louis, MO, as the most dangerous city in the United States. (chosen over lovely vacation spots like Detroit, MI; Camden, NJ; and Oakland, CA)

3 2010 population: 319,294 No. of neighborhoods: 79 Homicide history Year 200520062007200820092010 No. of Homicides 130126134162142143 St. Louis City Facts

4 Homicides can be predicted rather accurately by analyzing environmental variables. Example: Large number of bars in a particular neighborhood might lead to increase in drunk driving. No foreseen catastrophic event (e.g., federal government shutting down March 4) Murder is bad  Assumptions

5 Homicide rates are affected by variables such as income and education as well as both violent and non-violent crimes that do not result in homicide. By knowing where there are deficiencies in education, we can predict where there will also be more homicides. Hypothesis

6 Crime stats collected from StL Metro Police Dept (http://www.slmpd.org/crime_stats.html)http://www.slmpd.org/crime_stats.html Data collected and analyzed by neighborhood Data also collected from 2000 Census ( http://stlcin.missouri.org/citydata/newdesign/index.cfm) http://stlcin.missouri.org/citydata/newdesign/index.cfm Data Mining

7 We plotted the data in scatter graphs to determine any linear relationship. If no relationship between homicide and a variable, we omitted that data. If a relationship existed, we analyzed further to determine the correlation’s significance. Our Approach

8 Population Population density (per sq mi) Education above high school Median household income Income (per capita) No. of rented properties No. of owned properties Unemployment rate Property value Violent crimes Non-violent crimes Poverty rate (individuals) Poverty rate (families) No. of liquor stores Initial Variables We each listed our preferred variables and then tallied the top vote-getters (shown here).

9 Regressions We used Minitab to compare homicides to our initial variables to determine the greatest correlations. We discovered some very interesting correlations.

10 R^2P-ValueY-interceptSlope Violent Crimes0.691.88E-21-0.16330.0207 Non-Violent Crimes0.783.76E-27-0.018560.4019 Income0.170.0002133.714-0.00012 Property Value0.180.0001133.3366-2.20E-05 Property Rented0.0020.652.09-0.00536 Property Owned0.0034560.6091.5140.006101 Unemployment0.03760.0881.320.031 Poverty Rate Individual0.0770.0136620.62740.041 Poverty Rate Family0.0710980.0182850.846720.0398 Liquor Stores0.234377.10E-060.89870.9736 Population0.080.0118971.02170.000171 Population Density0.050.0470.77560.000147 High school Education0.285.66E-074.952-0.07345 Median Household Income0.160.0002754.33-9.60E-05 Results of Regressions

11 Final Variables Population Population density (per sq mi) Education above high school Median household income Income (per capita) Property value No. of violent crimes No. of non-violent crimes Poverty rate (individuals) Poverty rate (families) No. of liquor stores We used the resulting 11 variables in our final predictions.

12 Variable with the greatest degree of correlation (most probable) with homicide is Non-Violent Crimes. R 2 value =.78 (highest) P-value = 3.76E-27 (lowest) Our Results

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14 Variable with the second-greatest degree of correlation with homicide is Violent Crimes. R 2 = 0.69 P-value = 1.88E-21 Our Results (cont.)

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16 Our third significant variable is the Number of Liquor Stores. R 2 = 0.23437 P-value = 7.10E-06 Our Results (cont.)

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18 Equation Homicides =.676 +.0276 * Violent Crime -.00228 * Non Violent Crime +.000004 * Property Value +.0085 * Poverty Rate (ind.) –.0216 * Poverty Rate (fam) +.403 * Liquor Stores -.000048 * Population -.0161 * Above High School Education

19 Using 2000 Census data it is predicted that JeffVanderLou will have the most Homicides in 2011. Our Results (cont.) NEIGHBORHOOD200520062007200820092010 Forecasted 2011 Jeff Vanderlou5410131078.3 Wells-Goodfellow9414101168.16 Dutchtown4226357.04 The Greater Ville10945555.88 O'Fallon5979365.23 Acad emy2346324.37 Gravois Park2053144.31 Baden7546774.27 Walnut Park East13543334.24 Hamilton Heights4286434.15 West End3815543.81

20 Number of homicides: 8.3 Location of homicides: JeffVanderLou Total Forecasted City of St. Louis Homicides: 142.10 Our Predictions

21 Conclusion Violent, Non-Violent, and the Number of Liquor stores have an effect on the number of homicides in neighborhoods. Using 2010 Census data will result in a more accurate forecast.

22 Supporting Evidence

23 Thank You!


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