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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9

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9

8

3

5

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SUN MON TUE WED THU FRI SAT

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

0

200000

400000

600000

800000

1000000

1200000

1400000

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

78

25

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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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25000

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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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

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Before 7:45 7:45-8:00 8:01-8:15 8:16-8:30

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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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our F

itnes

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CV M

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mee

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Wal-M

art

Costco

#1

Targ

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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

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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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Port St. Lucie, FL Construction Site Burglary AnalysisPort St. Lucie, FL Construction Site Burglary Analysis

Time Span in Hours: CSBT

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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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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

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Q3 19

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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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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 dlweisel@social.chass.ncsu.edu dlweisel@social.chass.ncsu.edu

Karin SchmerlerKarin Schmerler kschmerler@chulavistapd.org kschmerler@chulavistapd.org

Rachel BobaRachel Bobarboba@fau.edurboba@fau.edu