1. The Relationship Between Part I Crimes and Public High School Proximity.
A study by Mike B. Ahn

2. Project Focus
OBJECTIVE: to see if there is a statistically higher incidence of Part I Crimes near public high schools in Arlington, Texas.
PART I CRIMES ARE…
Murder, Rape, Assault (Aggravated), Robbery, Burglary, Theft, Motor Vehicle Theft, and Arson.
SUBOBJECTIVE: if a statistical significance is observed, then strength of the discovered relationship will be compared with other traditional crime influencing spatial factors (e.g. population, race, age, etc.).

3. Prior Studies…
Previous research proved that there is a relationship between nearness to public high schools and higher instances of Part I crimes.
In San Diego, California it was found that residential areas that were adjacent to public high schools had more crime than areas that were more than one city block away from these schools (Roncek and LoBosco 1983).
In Cleveland, Ohio to be next to a public high school meant that there was an additional five Part I crimes per city block annually compared to the rest of the city (Roncek and Faggiani 1985).

4. DATA NCTCOG: 2000 Census blocks of Arlington, Texas
NCTCOG: Census SF1 block data
The City of Arlington Police Department: Point shapefile of all crime reports from June 1, 2006 to May 31, 2007.
GPS: Public high school points.
(Shaofei Chen later offered Texas School Points shapefile to verify)

5. METHODS PREPARATION Locate School Blocks with GPS.
Had to edit Arlington data, filter out non-Part I crimes, and consolidate crimes that were a sub-category of Part I crimes.
Make comparable layers: School blocks, Adjacent Blocks, and City Blocks.
12 Layers of blocks surrounding the school blocks in Arlington for multiple regression.
Had to delete Ft. Worth.
Hawths Tools to count points per polygon

7. METHODS
T-TEST average number of each Part I crime on school blocks with the average number of Part I crimes on the adjacent blocks.
^If no difference, combine the blocks.
T-test the average number of each Part I crime on combined blocks with the average number of Part I crimes on the rest of the city blocks.
Run t-test for secondary adjacent blocks and all other outside blocks.
Utilized a Microsoft Excel based program called StatistiXL to run t-tests.

8. …METHODS continued.
MULTIPLE REGRESSION: for each Part I crime category to define the relationship between crime and school block distance while taking into account other variables that have been known to be related to crime.
The independent or control variables per block being…
total population
% home renters
% vacant houses
% age 15-24
% Black
% Hispanic
% single women head of household
SUBOBJECTIVE: multiple regression also defines the strength of the school proximity indicator against other crime indicators (control variables).

9. Problems Encountered Finding data.
Crime data did not line up with census data.
Block data was scarce.
Bad Communication: it might not be a user/technical issue but it was a project issue.
A few types of Part I crimes had disruptive spatial bias (construction burglaries, bank robberies, etc.), so they were removed from the study.
Could not create an address locator.
Disagreement between literary resources and advising.
SF1 Census block data was limited so I could not find all the variables to account for in multiple regression. Thus it’s not likely to be as valid as the original studies.

10. Mean on Adjacent Blocks
COMPARING THE AVERAGE NUMBER OF CRIMES ON BLOCKS CONTAINING SCHOOLS WITH THE AVERAGE ON ADJACENT BLOCKS
Mean on School Blocks
Mean on Adjacent Blocks
t-statistic
Murder
not significant
Rape
0.333
0.172
0.478
Assault
3.167
2.184
0.635
Robbery
0.368
0.105
Burglary
8.500
5.149
0.896
Theft
3.667
3.172
0.27
Auto Theft
2.000
0.782
0.887
Arson
All Crimes 18
11.828
0.833 df
t-critical
6 Blocks
87 Blocks 91
95% CI
t-statistic > t-critical for significant difference*
No statistical significant difference, so blocks containing high schools was combined with adjacent blocks to compare with the remainder of the city blocks.
click for analysis

12. COMPARING THE AVERAGE NUMBER OF CRIMES
WITHIN 1 BLOCK OF SCHOOL PROXIMITY WITH
THE AVERAGE ON ALL OTHER BLOCKS
Mean Near School Proximity
Mean On All Other Blocks
t-statistic
Murder
<0.01
not significant*
Rape
0.183
0.104
1.787
significant
Assault
2.247
1.284
2.702
Robbery
0.366
0.176
2.33
Burglary
5.366
2.641
2.947
Theft
3.204
1.691
3.143
Auto Theft
0.860
0.523
2.001
Arson
All Crimes
12.226
6.425
3.375 df
t-critical
92 Blocks
3473 Blocks
3565
95% CI
click for analysis
all crimes analysis

13. COMPARING THE AVERAGE NUMBER OF CRIMES
INSIDE THE SECONDARY ADJACENT BLOCKS
WITH THE AVERAGE ON ALL OTHER BLOCKS
Secondary Adjacent
City Blocks
t-statistic
Murder
0.013
0.004
1.124
not significant
Rape
0.094
0.105
0.443
Assault
1.237
1.289
0.249
Robbery
0.181
0.176
0.145
Burglary
2.682
2.637
0.120
Theft
1.712
1.689
Auto Theft
0.609
0.515
0.890
Arson
0.003
0.001
0.613
All Crimes
6.532
6.415
0.134 df
t-critical
299 Blocks
3175 Blocks
3472
95% CI
*discluding school blocks and their directly adjacent blocks.
click for analysis

15. Verification with Multiple Regression
Variable
Slope\Coefficient\Beta
Murder
< 0.001
Rape
-0.003
Robbery
Assault
0.001
Burglary
0.06
Theft
0.018
Auto Theft
0.002
Arson
Violent Crimes
-0.002
Property Crimes
0.081
All Crimes
0.078
*All signs reversed on the beta results for the block
proximity independent variable.
click for multiple regression analysis tables

16. Comparing the Variables Related to Crime
Standardized Betas
Variable 
All Crimes
 rank
Violent
rank 
Property
Block Proximity
0.63 1
-0.004 6
0.506
Total Population of Block
0.005 5
< 0.001 4
0.003
% Home Renters
0.036 3
0.002 2
0.02
% Vacant Households
0.152
0.009
0.088
% Population Age 15-24
-0.362 8
-0.023
-0.207
% Population Black
0.024
0.013
% Population Hispanic
-0.001
-0.002
% Women Head of Household with No Husband
-0.173 7
-0.011
-0.1
*All signs reversed on the beta results for the block proximity independent variable.
click for multiple regression analysis tables

17. SUMMARY OF RESULTS
The t-tests show that there is a definite relationship between close proximity to public high schools and higher incidences of crime.
All relevant categories of Part I crime have higher incidence near schools. (except arson, murder)
The influence high schools have on crime does stretch out to all the city blocks for property crimes and the total of Part I crimes, but it is a very weak relationship.
The t-tests finds that the notable range of influence by public high schools extends just through the blocks immediately adjacent to school blocks.

18. Literature
Roncek, D.W. and D. Faggiani High Schools and Crime: A Replication. The Sociological Quarterly 26(4):
Roncek, D.W. and A. LoBosco The Effect of High Schools on Crime in Their Neighborhood. Social Science Quarterly 64:
Hirschi, T. and M. Gottfredson Age and the Explanation of Crime. The American Journal of Sociology 89 (3):

19. Software ArcGIS: www.esri.com
Hawths Tools:
Multiple Regression Analysis and Forecasting:
StatistiXL:

20. Thank you for your support…
Cynthia Bauman
Crime Analyst
Arlington Police Department
Dr. Ronald Briggs
Professor of Geography and Political Economy
The University of Texas at Dallas
Shaofei Chen
Geographic Information Systems Teacher Assistant
Dr. Michael Tiefelsdorf
Associate Professor of Geography and Geographic Information Systems

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