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Table 1 Descriptive statistics, dependent (rate per 1000) and independent variables

From: Theorizing globally, but analyzing locally: the importance of geographically weighted regression in crime analysis

 

Mean

Standard deviation

Minimum

Maximum

Variance inflation factor

Commercial burglary

3.89

4.84

0

26.9

 

Residential burglary

12.79

9.03

1.11

58.54

 

Other theft

7.09

11.52

0

68.68

 

Theft from vehicle

17.7

18.98

3.65

135.28

 

Theft of vehicle

2.36

1.83

0

10.64

 

Unemployment rate

3.8

0.79

2.02

6.73

1.36

Population change, %

7.37

15.94

-9.71

118.91

2.53

Rented, %

24.2

14.64

4.05

59.79

17.33

Major repairs, %

3.23

1.71

0.87

9.53

3.61

Old houses, %

11.6

6.17

0.59

25.82

3.62

Move, 1 year, %

16.67

4.69

7.55

27.71

4.42

Post secondary, %

54.46

12.79

27.24

76.55

20.25

Low income, %

18.48

6.16

9.5

44.37

7.96

Government assistance, %

8.98

4.73

2.2

33.7

11.72

Average dwelling value, 000 s

1213.42

661.13

341.89

3089.16

10.14

Average rent, 00 s

11.34

2.62

4.85

18.01

8.87

Median family income, 000 s

60.11

16.15

14.78

124.08

12.78

Aboriginal, %

2.35

2.45

0

18.11

3.74

Immigrants, %

40.99

12.3

19.39

64.32

33.54

Recent immigrants, %

5.75

2.17

1.31

11.44

3.35

Visible minorities, %

49.21

22.68

10.1

91.01

39.62

Ethnic heterogeneity

57.55

14.11

19.04

80.4

5.64

  1. n = 105