95The 25, 50, and 100 day datasets were created by calculating the standard deviation of

the daily RRFs for the monitoring sites with at least 10 days > 85 ppb. The distribution of the

RRF was calculated from the standard deviation. The original dataset had an actual maximum

number of 30 days.

96The standard deviation is in “RRF units”. For example, an RRF of 0.90 is equal to

a10% ozone reduction. A standard deviation of 3.4% is a measure of the variability such that

±3.4% is equal to a range in mean RRF of 0.866-0.934.

The ability to accurately capture a mean RRF with a small number of days is dependent

on the variability of the daily RRFs (as measure by the standard deviation). Sites with a small

standard deviation of the daily RRFs will be able to replicate the large dataset mean RRF with

relatively few days.

Using the available information, we were able to calculate, for each monitoring site, the

number of days needed to provide a mean RRF calculation that is within ±1% and ±2% of the

“large dataset” mean, with a 95% confidence interval. The number of days needed to produce a

robust mean RRF is dependent on the variability of the daily RRFs (as measured by the standard

deviation). Therefore, more days are needed to produce a stable RRF if the standard deviation of

the daily RRFs is high.

Table 14.1 summarizes the results for the 25th, 50th (median) and 75th percentile of the

standard deviation for the 206 monitoring sites. The table presents results for a range of standard

deviations, a range of large datasets (25, 50, and 100 days), and both ±1% and ±2% accuracy.

The table shows that for the median standard deviation of the monitoring sites (2.4%), a

minimum number of 10-16 days is needed to replicate the mean RRF to within ±1% (95% of the

time) and a minimum number of 5-6 days is needed to replicate the mean RRF to within ±2%

(95% of the time). The table also shows that a smaller standard deviation requires fewer days

and a larger standard deviation requires more days.

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