Table 6
Regression models (all variables) for violent and property crime rates, city of Toronto census tracts, 2006

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Regression models (all variables) for violent and property crime rates, city of Toronto census tracts, 2006
  Violent crime Property crime
  number
Number of incidents 26,040 75,304
  percent
Explanatory power 1 66.3 51.0
  regression coefficients (b)
Socio-economic characteristics  
University graduates -0.162***
No high school diploma 0.165**
Single-parent families 0.193*** 0.121*
Low-income households 0.125*
Ethno-cultural characteristics  
Recent immigrants -0.205*** -0.200***
Ethno-cultural diversity 0.069*
Demographic characteristics  
Children
Elderly people -0.109*** -0.108***
Young men
Urban characteristics  
Single-detached houses -0.089*
Renters 0.153*** 0.121*
Did not move -0.177**
Age of buildings 0.187***
Major repairs 0.158***
Subway or train station 0.160** 0.203**
Economic activity  
Commercial activity 0.203*** 0.471***
Manufacturing jobs -0.113** -0.118**
Office jobs -0.203*** -0.224***
Bars 0.0763* 0.080*
Spatial lag 1 0.373*** 0.304***
not applicable (variables excluded from the model because they are not significant [p<0.05])
*
Significantly associated with dependent variable p<0.05
**
Significantly associated with dependent variable p<0.01
***
Significantly associated with dependent variable p<0.001
1.
Data represent the squared correlation coefficients between observed and predicted values, a measure that is related to the coefficient of determination (R2). See "Spatial autocorrelation and regression" in the Methodology section for more information on autoregressive spatial models.
Note(s):
Based on 524 census tracts. Regression models include intercept. Population at risk includes residents and workers.
Source(s):
Statistics Canada, Incident-based Uniform Crime Reporting Survey, geocoded database, 2006 and 2006 Census.