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Chicago Crime Data Project
(CCDP)
John Mounce
& Billy Joe
Mills
Typical Chicago Criminal
Chicago Crime Blog
All past and future findings made by the Mounce-Mills team will be posted at www.chicagocrime.wordpress.com
Data downloads, maps, & graphs galore!
Hypothesis 1: Violent Crimes and Economic Wealth - 2005
Hypothesis Violent crimes are more common in economically
poor neighborhoods than in economically wealthy neighborhoods.
Null Hypothesis Violent crimes are no more common in
economically poor neighborhoods than in economically wealthy neighborhoods.
Hypothesis 1: Poor neighborhoods have more violent crime than rich neighborhoods
About 31% of the variance in violent crime is explained by household income levels
For every $1 increase in household income, the 2005 Violent Crime Index is reduced by 0.023 units.
Hypothesis 1: Poor neighborhoods have more violent crime than rich neighborhoods
For every increase in household income by $10,000, violent crime lowers by 7.7%.
Household Median Income 2005 Line Fit Plot
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Hypothesis 1: Poor neighborhoods have more violent crime than rich neighborhoods Violent crimes are more common in economically
poor neighborhoods than in economically wealthy neighborhoods.
Violent Crime Index vs. Household Median Income Year 2005
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Hypothesis 1: Poor neighborhoods have more violent crime than rich neighborhoods
Violent Crime Index vs. Household Median Income Year 2005
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Hypothesis 1: Violent Crimes and Economic Wealth - 2005
Hypothesis 2: Rich neighborhoods have more property crime than poor neighborhoods
Reporter: Why do you rob banks?
Willie Sutton: Because that’s where the money is.
Hypothesis 2: Rich neighborhoods have more property crime than poor neighborhoods
Property Crime Index vs. Household Median Income Year 2005
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Neighborhoods Ascending by Property Crime Index 2005
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Hypothesis 2: Rich neighborhoods have more property crime than poor neighborhoods
Hypothesis 2: Rich neighborhoods have more property crime than poor neighborhoods
Hypothesis 3: Neighborhoods with higher levels of violent crime have higher levels of property crime
About 49% of the variance in property crime is explained by violent crime
For every 1 unit increase in the Violent Crime Index 2005, the Property Crime Index 2005 increases by 1.951 units
Hypothesis 3: Neighborhoods with higher levels of violent crime have higher levels of property crime
Property CrimeViolent Crime
Hypothesis 3: Neighborhoods with higher levels of violent crime have higher levels of property crime
About 58% of the variance in property crime is explained by violent crime and household income
Hypothesis 4: Neighborhoods with higher levels of racial diversity have lower violent crime
The Mounce Diversity Index explains about 40% of the variance in the Violent Crime Index 2005
Hypothesis 4: Neighborhoods with higher levels of racial diversity have lower violent crime
For every 10% increase in the Mounce Diversity Index, violent crime decreases by 4%
Hypothesis 4: Neighborhoods with higher levels of racial diversity have lower violent crime
The Herfindahl Diversity Index explains about 36% of the variance in the Violent Crime Index 2005
Hypothesis 4: Neighborhoods with higher levels of racial diversity have lower violent crime
For every 10% increase in the Herfindahl Diversity Index, violent crime decreases by 5.1%
Hypothesis 5: Neighborhoods with higher levels of racial diversity have lower property crime
The Mounce Diversity Index explains about 9% of the variance in the Property Crime Index 2005
Hypothesis 5: Neighborhoods with higher levels of racial diversity have lower property crime
For every 10% increase in the Mounce Diversity Index, property crime decreases by 2.4%
Hypothesis 5: Neighborhoods with higher levels of racial diversity have lower property crime
The Herfindahl Diversity Index explains about 9% of the variance in the Property Crime Index 2005
Hypothesis 5: Neighborhoods with higher levels of racial diversity have lower property crime
For every 10% increase in the Herfindahl Diversity Index, property crime decreases by 3.1%
Problems with Diversity Index
Violent Crime
Hypothesis 6: Violent Crime and Racial Populations
For every 10% increase in the White Population, violent crime decreases by 4.37%
Hypothesis 6: Violent Crime and Racial Populations
For every 10% increase in the Hispanic Population, violent crime decreases by 2.77%
Hypothesis 6: Violent Crime and Racial Populations
For every 10% increase in the Asian Population, violent crime decreases by 6.32%
Hypothesis 6: Violent Crime and Racial Populations
For every 10% increase in the Black Population, violent crime increases by 3.67%
Hypothesis 6: Violent Crime and Racial Populations
Hypothesis 6: Violent Crime and Racial Populations
Hypothesis 7: Low income neighborhoods have more crime at night
Hypothesis 8: Neighborhoods with higher levels of education have lower violent crime
Hypothesis 8: Neighborhoods with higher levels of education have lower violent crime
For every 10% increase in the Education Index, violent crime decreases by 3.64%
Hypothesis 9: Neighborhoods with higher levels of education have lower property crime
Hypothesis 10: Neighborhoods with higher male populations have more violent crime
Hypothesis 10: Neighborhoods with higher male populations have more violent crime
Hypothesis 11: Neighborhoods with higher male populations have more property crime
Hypothesis 12: Neighborhoods with a higher 12-24 age proportion have higher violent crime
Hypothesis 13: Neighborhoods with a higher 12-24 age proportion have higher property crime
Hypothesis 14: Neighborhoods with a higher 0-11 age proportion have lower violent crime
Hypothesis 15: Neighborhoods with a higher 0-11 age proportion have lower property crime
Hypothesis 16: Neighborhoods with higher youth populations have more violent crime
Hypothesis 16: Neighborhoods with higher youth populations have more violent crime
Hypothesis 17: Neighborhoods with higher youth populations have more property crime
Hypothesis 18: Neighborhoods with a greater proportion of families with children have lower violent crime
Hypothesis 18: Neighborhoods with a greater proportion of families with children have lower violent crime
Hypothesis 19: Neighborhoods with a greater proportion of families with children have lower property crime
Hypothesis 20: Neighborhoods with higher proportions of single parent females have higher violent crime
Hypothesis 20: Neighborhoods with higher proportions of single parent females have higher violent crime
Hypothesis 21: Neighborhoods with higher proportions of single parent females have higher property crime
Hypothesis 22: Neighborhoods with higher proportions of single parent males have higher violent crime
Hypothesis 23: Neighborhoods with higher proportions of single parent males have higher property crime
Hypothesis 24: Neighborhoods with higher BH Female Ratios have higher violent crime
Hypothesis 24: Neighborhoods with higher BH Female Ratios have higher violent crime
Hypothesis 25: Neighborhoods with higher BH Female Ratios have higher property crime
Hypothesis 24: Neighborhoods with higher BH Male Ratios have higher violent crime
Hypothesis 24: Neighborhoods with higher BH Male Ratios have higher violent crime
Hypothesis 25: Neighborhoods with higher BH Male Ratios have higher property crime
Hypothesis 26: Neighborhoods with higher Single Parent Female Index have higher violent crime
Hypothesis 26: Neighborhoods with higher Single Parent Female Index have higher violent crime
Hypothesis 27: Neighborhoods with higher Single Parent Female Index have higher property crime
Hypothesis 28: Parent Soup
Big Soup – Violent Crime
Big Soup – Property Crime
Pax Obama - Wednesday
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Pax Obama - Thursday
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Support Group: Coping with underreporting bias
Property CrimeViolent Crime
Support Group: Coping with underreporting bias
Problems with Data and Methodology
Underreporting of crimes in a biased sample of neighborhoods
Overly zealous enforcement of laws in a biased sample of neighborhoods
Grafting 2008 crime data onto 2005 demographic data
Problems with Data and Methodology
Is a one variable regression meaningful?
Condensing crime data into 77 data points Concentrate on just a few hypotheses
