SOURCES: Calculated from 2006–2010 American Community Survey, Table B25044; adapted from workshop presentation by Steven Romalewski.
Figure 5-2 shows the map based on the lower bound of an interval estimate for the no-car percentage, subtracting the margin of error from the estimated number of no-car households and dividing by the total number of occupied housing units. He said that this might be considered a “worst case” map for no vehicle access. Most people on Long Island have cars, so low percentages dominate the picture, but Romalewski said that the pattern of block groups with high percentages is fairly similar to the pattern based on 2000 census long-form data. But when the view is switched to the upper bound on the estimates (Figure 5-3), the volatility in the data becomes clear; the map is saturated in the red and orange tones connoting the highest levels of no vehicle access because large standard errors drive up the upper bound. It is a “world of difference” between the two maps and—for purposes of envisioning specific transportation routes and policies—it suggests that the ACS data exhibit extreme uncertainty at the fine, block-group level.
Romalewski’s next series of maps looked at the same geographic area—Suffolk County, this time looking at census tracts rather than block groups—but a slightly different data source. As discussed in greater detail in Chapter 7,