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Crime Analysis for Problem Solvers - PowerPoint PPT Presentation

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Crime Analysis for Problem Solvers

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  1. Crime Analysis for Problem Solvers Problem Oriented Policing Conference Charlotte, NC October 2004

  2. #1 How should crime data be used?

  3. Crime is relative 2003 Data

  4. Target 4 Walmart Auto Theft Vehicle Burglary Total Vehicles Stolen: 30 % Recovered: 50% Avg. Time at Lot: 109 min. Avg. Vehicle Year: 1988 Top Makes/Models Toyotas & Nissans Walmart had 18 incidents predominantly between 12:00 – 20:00. The top makes include Fords and Hondas. Most Common Lot Addresses within Target Area #4 Walmart – 75 N. Broadway Best Buy – 59 N. Broadway Auto Theft Time of Day Auto Theft Day of Week

  5. Motor vehicle theft trend

  6. Types of motor vehicle theft

  7. Recovered vehicles

  8. Recovery by vehicle type

  9. #2 Make better use of Calls-for-Service data

  10. Top 10 Calls for ServiceChula Vista 2003 • False Burglary Alarm 8,882 12% • Disturbance by Person 3,977 5% • Domestic Violence 3,692 5% • Traffic Collision 3,680 5% • Noise Disturbance 2,759 4% • 911 Hang Up 2,397 3% • Vehicle Theft 2,327 3% • Petty Theft 2,091 3% • Vandalism 1,983 3% • Suspicious Person 1,806 2% Total 33,594 44%

  11. Domestic Disturbance Calls

  12. #3 What amount of data should be used?

  13. Too Much Data

  14. Miami

  15. Too Little Data Use at least 15-20 per category.

  16. Drug-related calls

  17. Adding data

  18. #4 What type of data are most appropriate?

  19. Estimating Magnitude of the Problem • Complaints to police 31 • Arrests 201 • Suspects 148 • Chronic offenders 60

  20. Estimating Offenses • Chronic offenders 60 • Tricks per day 3 – 5 • Days per week 5 • Weeks per year 50 • Estimated transactions 67,500 • Clearance rate 3/10 %

  21. #5 How else can In-house data be used?

  22. Utilize Narratives • To determine usefulness of data • To understand context of a problem • Content analysis and coding for additional statistical analysis

  23. Example: Construction Site BurglaryDifficulty Index (Four Characteristics)

  24. Difficulty Index: Initial Analysis 72% Port St. Lucie, FL Construction Site Burglary Analysis: N=155

  25. Difficulty Index: Preliminary Analysis Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158

  26. #6 When In-House Data Isn’t Enough

  27. Auto Theft Offender Interviews

  28. Access Control: A Critical Parking Lot Feature Number of Auto Thefts • Las Americas Safer than CV Mall in Other Ways: • -69% burglary • -60% fights/disturb. • -38% grand theft • -84% petty theft • zero robberies (16 at Chula Vista Mall)

  29. Traffic Congestion Problem: Who Drives to School and Why? AM Drivers and Walkers Paseo Bus Stops = All grades = K/1st Park

  30. Observations of Drop-Off/Pick-up Times Explain Afternoon Crunch School end time: 3:00 School start time: 8:30

  31. #7 What Analysis is Most Useful to Police Managers?

  32. Volume Outliers: 10 Worst Parking Lots Account for 15% of all Auto Thefts in City

  33. Rate Outliers: Vehicle Theft Rate Per Spot vs. Top 10 Lots Median: 3.1

  34. #8 How can I use mapping to understand a problem?

  35. Mapping • Use mapping sparingly • Should not be the central method used to direct police efforts • Mapping most useful for bringing data together, scanning, and presenting analysis results.

  36. Should we deploy officers based on this map?

  37. Example: Scanning

  38. Example: Bring Data Together

  39. Example: Presentation of Results San Diego County Recovery Rates 2001 Recovery Rates - Cars 2001 Recovery Rates - Trucks

  40. Example: Presentation of Results HIGHWAY closed section CAB STAND P P NEW CAB STAND Tønsberg downtown area P P Moved barristers P P MOVED BUS STAND TØNSBERG BRIDGE P=parking lot =no admission From: Gypsy Cabs in Tønsberg – a Case for Problem-Oriented Policing Johannes Knutsson, National Police Academy and Knut-Erik Søvik, Vestfold Police District

  41. #9 How do I know there’s a difference?

  42. Test Relationships • Ad hoc reasoning • Use of statistics • Statistical vs. practical significance

  43. Date Span Port St. Lucie, FL Construction Site Burglary Analysis

  44. Time Span *Statistically significant at the .01 level **58% of the CSBTs has a date span of 0 or 1 Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158

  45. #10 Did it work?

  46. Effort to Reduce Traffic Collisions Through Citations Results: -Very weak correlation between cites and collisions -Not statistically significant Chula Vista Police Department

  47. Domestic Violence Intervention Intervention Began

  48. Domestic Violence Intervention