crime analysis for problem solvers part i
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Crime Analysis Crime Analysis for Problem Solversfor Problem Solvers
Problem Oriented Policing ConferenceProblem Oriented Policing Conference
Charlotte, NCCharlotte, NC
October 2004October 2004
#1 How should crime #1 How should crime data be used?data be used?
Crime is relativeCrime is relative
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Homicide Rape Robbery Agg. Assault Burglary Non MVLarceny
MVTheft/Larceny
2003 Data
Auto Theft Vehicle Burglary
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Target 4Walmart
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Auto Theft Time of Day
Auto Theft Day of Week
Total Vehicles Stolen: 30% Recovered: 50%Avg. Time at Lot: 109 min.Avg. Vehicle Year: 1988
Walmart had 18 incidents predominantly between 12:00 – 20:00. The top makes include Fords and Hondas.
Most Common Lot Addresses within Target Area #4Walmart – 75 N. BroadwayBest Buy – 59 N. Broadway
Top Makes/ModelsToyotas & Nissans
Motor vehicle theft trendMotor vehicle theft trend
1998 2003
1,240,754
1,354,189
1,152,075 1,165,5591,228,391 1,246,646 1,260,471
1997 2000 20011999 2002
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200000
400000
600000
800000
1000000
1200000
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1600000
1 2 3 4 5 6 7
Source: Federal Bureau of Investigation (www.fbi.gov)
Types of motor vehicle theftTypes of motor vehicle theft
Professional27%
Fraud8%
Temporary use65%
Recovered vehiclesRecovered vehicles
347369
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1Not recovered Recovered
Recovery by vehicle typeRecovery by vehicle type
61
32 27
127
78
2217 11 6
162
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Not recovered Recovered
#2 Make better use of #2 Make better use of Calls-for-Service dataCalls-for-Service data
Top 10 Calls for ServiceTop 10 Calls for ServiceChula Vista 2003Chula Vista 2003
1. False Burglary Alarm 8,882 12%2. Disturbance by Person 3,977 5%3. Domestic Violence 3,692 5%4. Traffic Collision 3,680 5%5. Noise Disturbance 2,759 4%6. 911 Hang Up 2,397 3%7. Vehicle Theft 2,327 3%8. Petty Theft 2,091 3%9. Vandalism 1,983 3%10. Suspicious Person 1,806 2% Total 33,594 44%
Domestic Disturbance CallsDomestic Disturbance Calls
5519
4321
5519
19409
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Once-only DV DV 2+
Addresses DV Calls
#3 What amount of data #3 What amount of data should be used?should be used?
Too Much DataToo Much Data
MiamiMiami
Too Little DataToo Little Data
Use at least 15-20 per category. Use at least 15-20 per category.
Drug-related callsDrug-related calls
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JAN FEB MAR APR MAY JUN JUL AUG
911 CALLS SELF-INITIATED CALLS
Adding dataAdding data
0102030405060708090
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Apr-0
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911 CALLS SELF-INITIATED CALLS TOTAL CALLS
#4 What #4 What typetype of data are of data are most appropriate?most appropriate?
Estimating Magnitude of the Estimating Magnitude of the ProblemProblem
Complaints to policeComplaints to police 3131
ArrestsArrests 201201
SuspectsSuspects 148148
Chronic offendersChronic offenders 6060
Estimating OffensesEstimating Offenses
Chronic offendersChronic offenders 6060 Tricks per day Tricks per day 3 – 5 3 – 5 Days per weekDays per week 55 Weeks per yearWeeks per year 5050
Estimated transactionsEstimated transactions 67,50067,500
Clearance rate Clearance rate 3/10 % 3/10 %
#5 How else can In-#5 How else can In-house data be used?house data be used?
Utilize NarrativesUtilize Narratives
To determine usefulness of data To determine usefulness of data
To understand context of a problemTo understand context of a problem
Content analysis and coding for additional Content analysis and coding for additional statistical analysisstatistical analysis
Example: Construction Site BurglaryExample: Construction Site BurglaryDifficulty Index (Four Characteristics)Difficulty Index (Four Characteristics)
SkillSkill TransportTransport AccessAccess TimeTime
00 No skillNo skill Walk awayWalk away Outside/Outside/visible/visible/
unattachedunattached
0 to 5 minutes0 to 5 minutes
11 Heavy, Heavy, awkward, awkward, forcibly forcibly
removedremoved
Car, Car,
small trucksmall truck
Outside Outside attached, attached,
inside visible inside visible attached attached and/or and/or
unattachedunattached
5 to 10 minutes5 to 10 minutes
22 Skills/toolsSkills/tools Truck and/or Truck and/or trailertrailer
Secured insideSecured inside More than 10 More than 10 minutesminutes
Difficulty Index: Initial AnalysisDifficulty Index: Initial Analysis
Difficulty Index
Value Percent
0 2%
1 4%
2 11%
3 11%
4 16%
5 28%
6 13%
7 8%
8 7%
72%
Port St. Lucie, FL Construction Site Burglary Analysis: N=155Port St. Lucie, FL Construction Site Burglary Analysis: N=155
Difficulty Index: Preliminary AnalysisDifficulty Index: Preliminary Analysis
SkillSkill TransportTransport
PercentPercent PercentPercent
No skillNo skill 12%12% Walk awayWalk away 12%12%
Heavy/awkward/ forcibly Heavy/awkward/ forcibly removedremoved 37%37% Small truck/carSmall truck/car 70%70%
Skills/toolsSkills/tools 51%51% Large truckLarge truck 17%17%
AccessAccess TimeTime
PercentPercent PercentPercent
Outside/visible/unattached Outside/visible/unattached 21%21% 0 to 5 minutes 0 to 5 minutes 35%35%
Outside attached, inside Outside attached, inside visible attached and/or visible attached and/or unattachedunattached 41%41% 5 to 10 minutes 5 to 10 minutes 37%37%
Secured insideSecured inside 38%38% More than 10 minutes More than 10 minutes 28%28%
Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158
#6 When In-House Data #6 When In-House Data Isn’t Enough Isn’t Enough
Auto Theft Offender Auto Theft Offender InterviewsInterviews
A number admitted
taking stolen
cars into Mexico for sale
A number mentioned the ease of breaking into older Toyotas
(as well as Hondas)
A number said they
can use any old Toyota
key to unlock
some of the Toyotas
(didn’t even need to
shave the key)
Many admitted to
stealing from parking lots because it offered so
many choices in unguarded
settings
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2002
Chula Vista MallHorton Plaza (electronic arms)Las Americas (electronic arms)
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)
Number of Auto Thefts
Access Control: A Critical Access Control: A Critical Parking Lot FeatureParking Lot Feature
Paseo
Park
= K/1st
= All grades
Bus Stops
AM Drivers and Walkers
Traffic Congestion Problem: Traffic Congestion Problem: Who Drives to School and Why?Who Drives to School and Why?
Observations of Drop-Off/Pick-up Observations of Drop-Off/Pick-up Times Explain Afternoon CrunchTimes Explain Afternoon Crunch
0%
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Before 7:45 7:45-8:00 8:01-8:15 8:16-8:30
0%
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40%
Before2:40
2:40-2:50 2:51-3:00 3:01-3:10 3:11-3:20
School start time:
8:30
School end time:
3:00
#7 What Analysis is #7 What Analysis is Most Useful to Police Most Useful to Police
Managers?Managers?
Volume Outliers: 10 Worst Parking Lots Volume Outliers: 10 Worst Parking Lots Account for 15% of all Auto Thefts in CityAccount for 15% of all Auto Thefts in City
Location
2000-2002 Total Auto
Thefts
1. Chula Vista Center 202
2. Trolley Stations 162
3. Swapmeet 73
4. Wal-Mart 73
5. Costco (Broadway) 57
6. Target (Broadway) 49
7. Southwestern College 40
8. Costco (East H Street) 39
9. Palomar Shopping Center 36
10. Home Depot 35
Total for the City 2000-2002 5,046
Total for the 10 Lots 2000-2002 766
Rate Outliers: Vehicle Theft Rate Per Rate Outliers: Vehicle Theft Rate Per Spot vs. Top 10 LotsSpot vs. Top 10 Lots
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24-H
our F
itnes
s
CV M
all
Trolley St
ations
Swap
mee
t
Wal-M
art
Costco
#1
Targ
et
SW College
Costco
#2
Palomar
Cen
ter
Home Dep
ot
Median: 3.1
#8 How can I use mapping #8 How can I use mapping to understand a problem?to understand a problem?
MappingMapping
Use mapping sparinglyUse mapping sparingly
Should not be the central method used to Should not be the central method used to direct police effortsdirect police efforts
Mapping most useful for bringing data Mapping most useful for bringing data together, scanning, and presenting together, scanning, and presenting analysis results. analysis results.
Should we deploy officers based on this Should we deploy officers based on this map?map?
Example: ScanningExample: Scanning
Example: Bring Data TogetherExample: Bring Data Together
2001 Recovery Rates - Trucks2001 Recovery Rates - Trucks2001 Recovery Rates - Cars2001 Recovery Rates - Cars
Example: Presentation of ResultsExample: Presentation of ResultsSan Diego County Recovery RatesSan Diego County Recovery Rates
MOVED BUS MOVED BUS STANDSTAND
CAB STANDCAB STAND
PP
PP
PP
PP
P=parking lotP=parking lot
=no admission=no admission
PP
HIGHWAYHIGHWAY
closed sectionclosed section
TTØNSBERG ØNSBERG BRIDGEBRIDGE
P
NEW CAB NEW CAB STANDSTAND
Moved Moved barristersbarristers
Example: Example: Presentation of Presentation of
ResultsResults
Tønsberg Tønsberg downtowdowntown arean area
From: Gypsy Cabs in Tønsberg – a Case for From: Gypsy Cabs in Tønsberg – a Case for Problem-Oriented PolicingProblem-Oriented PolicingJohannes Knutsson, National Police Academy and Johannes Knutsson, National Police Academy and Knut-Erik Søvik, Vestfold Police DistrictKnut-Erik Søvik, Vestfold Police District
#9 How do I know #9 How do I know there’s a difference?there’s a difference?
Test RelationshipsTest Relationships
Ad hoc reasoningAd hoc reasoning
Use of statisticsUse of statistics
Statistical vs. practical significanceStatistical vs. practical significance
Date Span in Days: CSBT
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Time span in days
Nu
mb
er o
f ca
ses
Mean SD N
Residential Burglaries 4.36 23.66 614
Construction Site Burgs 2.52 4.16 225
Date SpanDate Span
Date Span in Days: Residential Burglaries
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Time span in days
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er o
f ca
ses
Port St. Lucie, FL Construction Site Burglary AnalysisPort St. Lucie, FL Construction Site Burglary Analysis
Time Span in Hours: CSBT
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Time span in hours
Nu
mb
er o
f C
ases
Mean* SD N
Residential Burglaries 7.31 8.47 479
Construction Site Burgs 14.64 7.79 130**
Time SpanTime Span
*Statistically significant at the .01 level **58% of the CSBTs has a date span of 0 or 1*Statistically significant at the .01 level **58% of the CSBTs has a date span of 0 or 1
Time Span in Hours: Residential Burglaries
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Time span in hours
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mb
er o
f ca
ses
Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158
#10 Did it work?#10 Did it work?
Effort to Reduce Traffic Collisions Effort to Reduce Traffic Collisions Through CitationsThrough Citations
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Q1 19
98
Q3 19
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Q1 19
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Q3 19
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Q1 20
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Q3 20
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Q1 20
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Q3 20
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Q1 20
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Q3 20
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Cites per 1 million DVMT
Collisions per 1 millionDVMT
Results:
-Very weak correlation between cites and collisions
-Not statistically significant
Chula Vista Police Department
Domestic Violence InterventionDomestic Violence Intervention
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DV Rate per 100 Persons
Intervention Began
Domestic Violence InterventionDomestic Violence InterventionTotal # of Total # of DV IncidentsDV Incidents
Total # of Total # of Repeat Repeat IncidentsIncidents
Repeat Repeat RateRate
1995 (pre-)1995 (pre-) 1,7131,713 594594 35%35%
1999 (post)1999 (post) 1,5271,527 525525 34%34%
# of people # of people revictimizedrevictimized
1 time1 time 2 times2 times 3 times3 times 4 times4 times 5+ 5+ timestimes
1995 (pre-)1995 (pre-) 65%65% 19%19% 10%10% 3%3% 3%3%
1999 (post)1999 (post) 65%65% 17%17% 8%8% 2%2% 6%6%
Anti-Theft Device: Anti-Theft Device: Passive Immobilizers in Passive Immobilizers in
Honda AccordsHonda Accords
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1987
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Number of Accords Stolen in Chula Vista (1/1/02-8/1/03)
Year Immobilizers Introduced Into Accords
Discussion and Discussion and QuestionsQuestionsContact Information:Contact Information:
Deborah WeiselDeborah Weisel [email protected] [email protected]
Karin SchmerlerKarin Schmerler [email protected] [email protected]
Rachel BobaRachel [email protected]@fau.edu