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Telling stories with the help of data.

Exhibit 1 Assumptions

Exhibit 1

This data has been smoothed to limit noise created by the tendency of riders to travel at “common” times, i.e., leaving from home or office on the hour or half-hour and arriving at entry stations 6-12 minutes later.

1.tssmooth ma smooth_rc = rider_count, window(2 1 2)

tssmooth constructs a new series in which each observation is an average of nearby observations in the original series. In this case, a uniformly weighted moving average is taken using the original observation and the two points to either side of that observation.

Before smoothing, small spikes appeared at the second 6-minute interval of every half-hour; i.e. 2:06 pm, 2:36 pm, …, 6:06 pm, 6:36 pm, etc.

The single exception for all Exhibit 1 stations occurred at 7 pm; the spike occurs on the hour rather than the following 6-12 minute period. Because this bump is distinguishable from the noise, I left that region unsmoothed.