Crime Analysis
for Problem Solvers
Problem Oriented Policing Conference
Charlotte, NC
October 2004
#1 How should crime
data be used?
Crime is relative
4500
4000
3500
3000
2500
2000
1500
1000
500
0
Homicide
Rape
Robbery
Agg. Assault
Burglary
2003 Data
Non MV
Larceny
MV
Theft/Larceny
Target 4
Walmart
Auto Theft
Total Vehicles Stolen: 30
% Recovered: 50%
Avg. Time at Lot: 109 min.
Avg. Vehicle Year: 1988
Vehicle Burglary
Top Makes/Models
Toyotas & Nissans
Walmart had 18 incidents predominantly between 12:00 –
20:00. The top makes include Fords and Hondas.
Auto Theft Time of Day
Most Common Lot Addresses within Target Area #4
Walmart – 75 N. Broadway
Best Buy – 59 N. Broadway
14.00%
12.00%
10.00%
8.00%
6.00%
4.00%
Auto Theft Day of Week
9
9
8
9
8
7
5
6
5
3
4
2
3
2
0
1
0
SUN
MON
TUE
WED
THU
FRI
SAT
23:00
24:00:00
22:00
21:00
20:00
19:00
18:00
17:00
16:00
15:00
14:00
13:00
12:00
11:00
9:00
8:00
7:00
6:00
5:00
4:00
3:00
2:00
1:00
0:00
0.00%
10:00
2.00%
Motor vehicle theft trend
1600000
1,354,189
1400000
1,240,754
1200000
1,152,075
1,165,559
3
1999
4
2000
1,228,391
1,246,646
1,260,471
5
2001
6
2002
7
2003
1000000
800000
600000
400000
200000
0
1
1997
2
1998
Source: Federal Bureau of Investigation (www.fbi.gov)
Types of motor vehicle theft
Fraud
8%
Professional
27%
Temporary
use
65%
Recovered vehicles
500
450
400
350
369
347
300
250
200
150
100
50
0
1
Not recovered
Recovered
Recovery by vehicle type
180
162
160
140
127
120
100
80
78 78
61
60
32
40
17
20
27
11
22 25
6
Not recovered
Recovered
er
O
th
V
U
k/
S
Tr
uc
ed
an
S
le
r/m
ow
er
le
or
cy
M
ot
Tr
ai
A
TV
/m
ot
or
bi
ke
0
#2 Make better use of
Calls-for-Service data
Top 10 Calls for Service
Chula Vista 2003
1. False Burglary Alarm
2. Disturbance by Person
3. Domestic Violence
4. Traffic Collision
5. Noise Disturbance
6. 911 Hang Up
7. Vehicle Theft
8. Petty Theft
9. Vandalism
10. Suspicious Person
Total
8,882
3,977
3,692
3,680
2,759
2,397
2,327
2,091
1,983
1,806
33,594
12%
5%
5%
5%
4%
3%
3%
3%
3%
2%
44%
Domestic Disturbance Calls
25000
19409
20000
15000
10000
5519
5519
4321
5000
0
Once-only DV
DV 2+
Addresses
DV Calls
#3 What amount of data
should be used?
Too Much Data
Miami
Too Little Data
Use at least 15-20 per category.
Drug-related calls
70
60
50
40
30
20
10
0
JAN
FEB
MAR
APR
911 CALLS
MAY
JUN
SELF-INITIATED CALLS
JUL
AUG
911 CALLS
SELF-INITIATED CALLS
TOTAL CALLS
Sep-04
Aug-04
Jul-04
Jun-04
May-04
Apr-04
Mar-04
Feb-04
Jan-04
Dec-03
Nov-03
Oct-03
Sep-03
Aug-03
Jul-03
Jun-03
May-03
Apr-03
Mar-03
Feb-03
Jan-03
Adding data
90
80
70
60
50
40
30
20
10
0
#4 What type of data are
most appropriate?
Estimating Magnitude of the
Problem
Complaints to police
Arrests
Suspects
Chronic offenders
31
201
148
60
Estimating Offenses
Chronic offenders



Tricks per day
Days per week
Weeks per year
Estimated transactions
Clearance rate
60
3–5
5
50
67,500
3/10 %
#5 How else can Inhouse data be used?
Utilize Narratives
To determine usefulness of data
To understand context of a problem
Content analysis and coding for additional
statistical analysis
Example: Construction Site Burglary
Difficulty Index (Four Characteristics)
Skill
Transport Access
Time
0
No skill
Walk away
Outside/visible
/unattached
0 to 5 minutes
1
Heavy,
awkward,
forcibly
removed
Car,
small truck
Outside
attached,
inside visible
attached
and/or
unattached
5 to 10 minutes
2
Skills/tools
Truck and/or
trailer
Secured inside
More than 10
minutes
Difficulty Index: Initial Analysis
Difficulty Index
Value
0
1
2
3
4
5
6
7
8
Percent
2%
4%
11%
11%
16%
28%
13%
8%
7%
Port St. Lucie, FL Construction Site Burglary Analysis: N=155
72%
Difficulty Index: Preliminary Analysis
Skill
Transport
Percent
Percent
No skill
12%
Walk away
12%
Heavy/awkward/ forcibly
removed
37%
Small truck/car
70%
Skills/tools
51%
Large truck
17%
Access
Time
Percent
Percent
Outside/visible/unattached
21%
0 to 5 minutes
35%
Outside attached, inside
visible attached and/or
unattached
41%
5 to 10 minutes
37%
Secured inside
38%
More than 10 minutes
28%
Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158
#6 When In-House Data
Isn’t Enough
Auto Theft Offender
Interviews
A number
Many
said they
admitted to
A
A number
number mentioned can use any stealing from
parking lots
admitted the ease of old Toyota
key to
because it
taking
breaking
unlock
offered so
stolen
into older
some of the many choices
cars into
Toyotas
Toyotas
in unguarded
Mexico (as well as
settings
for sale
Hondas) (didn’t even
need to
shave the
key)
Access Control: A Critical
Parking Lot Feature
Number of Auto Thefts
80
Las Americas
Safer than CV Mall
in Other Ways:
60
40
• -69% burglary
20
0
• -60% fights/disturb.
2002
Chula Vista Mall
Horton Plaza (electronic arms)
Las Americas (electronic arms)
• -38% grand theft
• -84% petty theft
• zero robberies (16 at
Chula Vista Mall)
Traffic Congestion Problem:
Who Drives to School and Why?
AM Drivers
and Walkers
Bus Stops
= All grades
Paseo
= K/1st
Pa
rk
Observations of Drop-Off/Pick-up
Times Explain Afternoon Crunch
School
end time:
60%
3:00
40%
40%
20%
0%
Before 7:45
7:45-8:00
8:01-8:15
School
start time:
8:30
8:16-8:30
20%
0%
Before
2:40
2:40-2:50 2:51-3:00 3:01-3:10 3:11-3:20
#7 What Analysis is
Most Useful to Police
Managers?
Volume Outliers: 10 Worst Parking Lots
Account 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
ou
r
m
ar
D
ep
ot
Ce
nt
er
2
ge
et
#
lle
st
co
Co
H
om
e
Pa
lo
Co
SW
Ta
rg
Fi
tn
es
s
CV
Tr
M
ol
al
le
l
y
St
at
io
ns
Sw
ap
m
ee
t
W
al
-M
ar
t
Co
st
co
#
1
24
-H
Rate Outliers: Vehicle Theft Rate Per
Spot vs. Top 10 Lots
9
Median: 3.1
0
#8 How can I use mapping
to understand a problem?
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.
Should we deploy officers based on this
map?
Example: Scanning
Example: Bring Data Together
Example: Presentation of Results
San Diego County Recovery Rates
2001 Recovery Rates - Cars
2001 Recovery Rates - Trucks
Example:
Presentation of
Results
HIGHWAY
closed section
CAB STAND
P
P
NEW CAB
STAND
P
Tønsberg
downtown
area
P
Moved
barristers
TØNSBERG
BRIDGE
P
P
MOVED BUS
STAND
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
#9 How do I know
there’s a difference?
Test Relationships
Ad hoc reasoning
Use of statistics
Statistical vs. practical significance
Date Span
Mean
SD
N
Residential Burglaries
4.36
23.66
614
Construction Site Burgs
2.52
4.16
225
400
300
Tim e span in days
Number of cases
Date Span in Days: CSBT
150
100
50
0
0
1
2
3
4
5
6
7
10
11
Tim e span in days
Port St. Lucie, FL Construction Site Burglary Analysis
12
13
15
18
25
30
248
89
72
50
44
41
31
29
27
24
20
18
16
14
12
10
8
6
4
2
200
100
0
0
Number of cases
Date Span in Days: Residential Burglaries
Time Span
Mean*
SD
N
Residential Burglaries
7.31
8.47
479
Construction Site Burgs
14.64
7.79
130**
*Statistically significant at the .01 level
**58% of the CSBTs has a date span of 0 or 1
150
100
50
34
29
27
24
22
20
18
16
14
12
10
8
6
4
2
0
0
Number of cases
Time Span in Hours: Residential Burglaries
Tim e span in hours
Number of Cases
Time Span in Hours: CSBT
20
15
10
5
0
0 1
2 3
5 6
7 8
9 13 14 15 16 17 18 19 20 21 22 23 24 25 26 28 30 32
Tim e span in hours
Port St. Lucie, FL Construction Site Burglary Analysis: N=155-158
#10 Did it work?
Effort to Reduce Traffic Collisions
Through Citations
1200
1000
800
600
400
200
0
98 9 98 9 99 9 99 0 00 0 00 0 01 0 01 0 02 0 02 0 03 0 03
9
1
1
1
1
2
2
2
2
2
2
2
2
1
3
1
3
1
3
1
3
1
3
1
3
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Cites per 1 million DVMT
Collisions per 1 million
DVMT
Results:
-Very weak
correlation between
cites and collisions
-Not statistically
significant
Chula Vista Police Department
Domestic Violence Intervention
1.2
1.1
1
0.9
0.8
0.7
0.6
0.5
0.4
19
95
19
96
19
97
19
98
19
99
20
00
Intervention
Began
DV Rate per 100 Persons
Domestic Violence Intervention
Repeat
Rate
1995 (pre-)
Total # of
Total # of
DV Incidents Repeat
Incidents
1,713
594
1999 (post)
1,527
34%
525
35%
# of people 1 time 2 times 3 times 4 times 5+
revictimized
times
1995 (pre-)
65%
19%
10%
3%
3%
1999 (post) 65%
17%
8%
2%
6%
Anti-Theft Device:
Passive Immobilizers in
Honda Accords
25
Year
Immobilizers
Introduced
Into Accords
02
20
01
20
00
20
99
19
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
19
90
19
89
19
88
19
19
87
0
Number of Accords Stolen in Chula Vista (1/1/02-8/1/03)
Discussion and
Questions
Contact Information:
Deborah Weisel
dlweisel@social.chass.ncsu.edu
Karin Schmerler
kschmerler@chulavistapd.org
Rachel Boba
rboba@fau.edu