Outdoor Lighting and Crime - Amper

5.2.3.4 UCR crime rate data and light energy loss per person
Figure 9 is also a plot of the UCR crime rate, but this time the abscissa represents upward
light energy loss per person (from Table 6), corrected as described to no-snow conditions.
The regression line is positive and its slope is reliably different from zero (r 2 = 0.459, t =
2.953, 19 df, p < 0.01). Without the snow correction, the regression line slope is smaller but
still positive and statistically significant (r 2 = 0.338, t = 2.708, 19 df, p < 0.05). The changes
introduced by the corrections to no-snow conditions are relatively insensitive to the
assumptions made in deriving the corrections. As before, the actual results for the whole year
would be intermediate between the original and no-snow values.
Of the 21 USA cities, those with higher values of UCR crime rate have reliably more upward
light energy loss per person. This supports the existence of coupled growth of lighting and
crime and the lighting, commerce and crime hypothesis devised to explain it, but, by itself,
does not allow assignment of causality. Regardless, the regression equation shown on Figure
9 appears to have a useful amount of predictive power in determining the effect of a US city
lighting change on the UCR index crime rate. Within the data set examined, the equation
accounts for 46% of the variance in the crime data.
The data in Tables 5 and 6 were used to make a graph (not shown here) of UCR index crime
rate against population. Logarithmic transformation was used to deal with the gap between
the population of New York City and other cities. Despite the common belief that bigger
cities have more crime, the slope in this case was slightly negative. No reliable connection
exists between UCR crime and log10 population for the 21 cities: r 2 = 0.039 and t = 0.876, 19
df, ns. This helps in interpretation of the findings for light and crime.
5.2.3.5 Morgan Quitno crime data plots
As mentioned in Section 3.2.6, the Morgan Quitno scores are based on UCR crime rate data
weighted by the posed threat for various crimes, determined by survey. Cities and
metropolitan areas in the USA with populations of more than 75 000 are included. A score is
expressed as a positive real number when the weighted UCR value is greater than the mean
weighted crime rate for all of the cities. A score of 0 means the place is representative of the
mean, while a negative value means less dangerous than the mean. The Morgan Quitno crime
scores for 1997 were available but were missing those cities mentioned above as missing from
the 1997 UCR data. The Morgan Quitno (2000) crime scores for 1998 and their ranking are
used instead in this paper, and are both listed in Table 5 for the 21 cities.
The Morgan Quitno crime scores were plotted (not shown here) against light energy loss per
square kilometre. The regression line had a reliably positive slope (7.225) using the
uncorrected light loss data (r 2 = 0.292, t = 2.356, 19 df, p < 0.05) and a statistically nonsignificant
lesser positive slope (6.585) when the light measures were corrected as described
to no-snow conditions (r 2 = 0.127, t = 1.551, 19 df). The statistical significance of the
combined result would depend on the duration of snow cover over the year for each of the
five cities observed with snow cover.
The Morgan Quitno crime scores were then plotted against light energy loss per person. The
regression line had a reliably positive slope of 1.886 using the light loss data corrected to nosnow
conditions (r 2 = 0.537, t = 3.194, 19 df, p < 0.01) (Figure 10) and a lesser but still
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