IS 6833ANALYTICS ASSIGNMENTYing Chen, Sri Murali, John Powell, Scott Weber

Homicide - National Trend Definition: Willful (non-negligent) killing of one human

being by another1

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

0.0

2.0

4.0

6.0

8.0

10.0

12.0Murder and Non-negligent Manslaughter2

Rate per 100,000 inhab...

Our Approach

Study data by neighborhoods

Analyze historical homicide data and develop regression model

Evaluate independent variables correlated to homicide rates. Select variables to study

Select model for prediction

Draw conclusions about where murder will occur. Predict homicide rate for location

Regression Model Based on Historical Data Weighted Moving Average

.1 – 3 previous years.2 – 2 previous years.3 – previous year.4 – current year

This statistical analysis was used for the total number and an individual neighborhood basis

Microsoft Office Excel Worksheet

Regression Model - Prediction

Bade

n

Midtow

n

Hamilto

n Heig

hts

Columbu

s Squ

are

Walnut

Park

East

02468

1012

20112012 - Prediction

Regression Model Conclusion

We predict that 43/91 neighborhoods (47.25%) will be murder free.

Prediction1. Baden (11)2. Jeff Vanderlou (9)3. Midtown/Hamilton Heights/The Great

Ville/ Wells-Goodfellow (5)

JPEG image

Demographic Based Model Study Independent Variables Correlated to

Homicides Sources:

Report published Bureau of Justice Statistics in report Homicide Trends in the United States, 1980-2008, released in November 20113

Research Paper Structural Determinants of Homicide: The Big Three, published in Journal of Quantitative Criminology in March 20114

Article National Case-Control Study of Homicide Offending and Methamphetamine Use, published Journal of Interpersonal Violence, published in June 20095

Research paper Crime is the Problem: Homicide, Acquisitive Crime, and Economic Conditions, published in Journal of Quantitative Criminology in September 20096

Data Analysis Review Almost 90% of the offenders are males 65% of the offenders are in the 18-34 age

group Larger cities experienced higher number of

homicides More than 2/3rds of homicides were by guns Homicide rates correlated to other factors

Economic Conditions Educational Level Divorce Rate Drug Use

Educational Level

0.000 0.010 0.020 0.030 0.040 0.050 0.060 0.0700

0.10.20.30.40.50.60.70.80.9

% <HS Diploma

Poverty Level

0.000 0.010 0.020 0.030 0.040 0.050 0.060 0.0700

0.1

0.2

0.3

0.4

0.5

0.6

0.7Poverty and Homicide

St. Louis City Demographics

Analyzed data from 2010 census for census tracts in St. Louis city

Studied variables Number of males in age group 18-34 Educational level Marital Status Poverty level Median Home Price

St. Louis City Homicide Data

2005 2006 2007 2008 2009 2010 20110

20406080

100120140160180

Annual Homicide Rate

St. Louis City - Educational Level

12021112106510761266106312571018105410720.00%

10.00%20.00%30.00%40.00%50.00%60.00%

Males without high school diploma

Expressed as a percentage of male population

Divorce Rate

10641123125511641103101510621266127611130.00%

10.00%20.00%30.00%40.00%50.00%60.00%70.00%

Male Divorce Rate

Number of men divorced compared to number of men married

Economic Conditions

1257 1212 1193 1274 1184 1062 1066 1054 1053 12020.00%

10.00%20.00%30.00%40.00%50.00%60.00%70.00%

Poverty Level

Percentage of Population in Poverty

Census Tracts with High Likelihood

Males aged 18-34 as a percentage of population

Number of men without a high school diploma

Divorce Rate Among Men

Percentage of Population in poverty level

1193 1202 1064 1257

1171 1112 1123 1212

1186 1065 1255 1193

1270 1076 1164 1274

1276 1266 1103 1184

1184 1063 1015 1062

1256 1257 1062 1066

1191.02 1018 1266 1054

1045 1054 1276 1053

1268 1072 1113 1202

Prediction Based on Historical Data

Based on historical demographic information, homicide is more likely to occur in the neighborhood of Wells-Goodfellow, which is comprised of census tracts 1062 and 1063

Map of neighborhood9:JPEG Image

Conclusion Given the research on the variables we have

chosen to study are not up to date, we conclude that the best predictor of murder rates in neighborhoods in St. Louis city is the regression model.

We believe the variables are valid indicators of murder rates, but accurate conclusions cannot be drawn because the data is not current.

Baden, with 11 predicted murders in 2012, is the most dangerous neighborhood in the city.

Assumptions and Caveats

Demographic data obtained from 2010 census Census data doesn’t accurately portray current

demographics Data from St. Louis Metropolitan Police

Department assumed to include only homicides More recent numbers were assigned higher

weights Demographic data for correlation based on

single census tract

References 1: FBI definition:

http://www2.fbi.gov/ucr/cius2009/offenses/violent_crime/murder_homicide.html 2: Homicide Rates:

http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2010/crime-in-the-u.s.-2010/tables/10tbl01.xls

3: BJS report and data: http://bjs.ojp.usdoj.gov/index.cfm?ty=pbdetail&iid=2221 4: Structural Determinants of Homicide: The Big Three:

http://www.springerlink.com.ezproxy.umsl.edu/content/d484g87643485322/fulltext.html

5: National Case-Control Study of Homicide Offending and Methamphetamine use: http://jiv.sagepub.com.ezproxy.umsl.edu/content/24/6/911.full.pdf+html

6: Crime is the Problem: Homicide, Acquisitive Crime, and Economic Conditions: http://search.ebscohost.com.ezproxy.umsl.edu/login.aspx?direct=true&db=cja&AN=43757548&site=ehost-live

7: Census data: http://factfinder2.census.gov 8: St. Louis Metropolitan Police Department Crime Statistics:

http://www.slmpd.org/crime_stats.html 9: Map showing St. Louis City Neighborhoods and Census Tracts:

https://sites.google.com/a/slu.edu/montrejr/census