1 / 19

Predicting 2014 Homicides in St . Louis City

Predicting 2014 Homicides in St . Louis City. Milos Bucalo Haishan Zhao Samir Muratovic. Agenda. Goal Overall Approach Data Collection Data Organization Prediction. Goal. To accurately predict the number and location of homicides that will occur in the city of St. Louis in 2014.

rachel
Download Presentation

Predicting 2014 Homicides in St . Louis City

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Predicting 2014Homicides in St. Louis City Milos Bucalo Haishan Zhao Samir Muratovic

  2. Agenda • Goal • Overall Approach • Data Collection • Data Organization • Prediction

  3. Goal • To accurately predict the number and location of homicides that will occur in the city of St. Louis in 2014. • To enable the city of St. Louis to effectively allocate resources to prevent those crimes.

  4. St. Louis City • Population: 319,294 • Divided into 79 neighborhoods • 9 Districts • 3 Patrols • Ranked 3rd most dangerous city in 2012 • 1,777 violent crimes per 100,000 people

  5. Approach • Data Collection • Initially wanted to collect homicide data by counties • Decided to collect homicide data by districts • Patrols (North, Central, South) • Collected 6 years of homicide data from 2008-2013 • Collected demographic and socioeconomic data from 2010 U.S. Census by districts • Data Organization • Used Excel to organize and make meaning of data • Summed up homicides by Patrols

  6. Approach • Calculations • Used Excel to calculate several key metrics • Summed up homicides by Patrols • Average number of homicides per year by Patrols • Homicide rate per 1000 inhabitants • Homicide trend • Prediction • Linear regression using homicide data from 2008-2013

  7. Collecting Data Saint Louis Metropolitan Police Department Combine CSV files

  8. Collecting Data - Homicides Data from January 2008 – January 2014 417 244 N 167 C S Table 1 Figure 1

  9. Collecting Data - Population U.S. Census Bureau 97,693 60,895 N 157,540 C S Figure 2 Table 2

  10. Organizing Data Average Number of Homicide per Year by Patrols 59.57 34.86 N 23.86 C S Table 3 Figure 3 Formula 1

  11. Organizing Data Homicide Rate per 1000 inhabitants 4.26 4.00 N 1.06 C S Table 4 Figure 4 Formula 2

  12. Organizing Data Homicide Trend -13 -1.39 -14.1 2.47 -3.22 Table 5 Formula 3

  13. Organizing Data • Top 4 dangerous streets by Patrols Table 6

  14. Organizing Data • Top 4 dangerous streets by Patrols Table 7

  15. Organizing Data • Top 4 dangerous streets by Patrols Table 8

  16. Prediction

  17. Prediction Table 9 Table 10

  18. Prediction • 2014 homicides victims average age 31 • Shooting related victims average age 29.7 • Main reasons: • Unknown • Gang • Suicide • Relative conflict

  19. References • www.slmpd.org • www.census.gov • www.njsp.org/info/ucr2000/pdf/calc_ucr2000.pdf • www.stltoday.com/st-louis-area-murder-map/html_3bf7a0a8-0440-5ada-aacf-11e4314a9956.html

More Related