1. St. Louis Homicide Analysis
Jacob Treat, Thuy xa, Charles Gendron

2. Objectives
Use statistical analysis to predict the total number of homicides in St. Louis
Locate areas with high homicide trends
Determine factors that may disrupt data analysis

3. Data Overview Collected 7 years of data from SLMPD website
City divided into 79 neighborhoods
Organized data into Excel to run statistical analyses

4. 2008 – 2013 Model Analysis Downward trend in total homicides
Model: Y=-9.057x
R² = .761
F-Test = .023
P-Value Intercept = .023
P-Value X Variable = .023
Predictions:
100 Murders in 2014
91 Murders in 2015

5. Anomalies 2014 actual homicide number 156 Bloody Spring
Wells Goodfellow
St. Louis Place
West End
Kingsway East
Accounted for +18 change in homicides from 2013 to 2014
Ferguson Effect
Extra patrols called to Ferguson leaving other neighborhoods with less officers
August - December

6. Model Analysis
Linear Regression Model does not fit when data for 2014 is added
Model: Y = x
R² = .107
F-Test = .473
P-Value Intercept = .464
P-Value X Variable = .473
56 more than the model predicted for 2014
2015 YTD (March) change is 0
Prediction:
2015 Prediction of 123 murders

7. Top 10 Most Dangerous (Statistical Average of 7 Years)
Wells Goodfellow = 8
Jeff Vanderlou = 7.86
Baden = 7.14
Dutchtown = 5.43
Mark Twain = 5.43
O’Fallon = 5.14
Greater Ville = 4.86
College Hill = 4.29
Penrose = 4.14
West End = 3.86