http://www.bls.gov/news.release/empsit.tn.htm
For example, the confidence interval for the monthly change in total nonfarm
employment from the establishment survey is on the order of plus or minus 136,000.
Suppose the estimate of nonfarm employment increases by 50,000 from one month to
the next. The 90-percent confidence interval on the monthly change would range from
-86,000 to +186,000 (50,000 +/- 136,000). These figures do not mean that the sample
results are off by these magnitudes, but rather that there is about a 90-percent
chance that the true over-the-month change lies within this interval. Since this
range includes values of less than zero, we could not say with confidence that
nonfarm employment had, in fact, increased that month. If, however, the reported
nonfarm employment rise was 250,000, then all of the values within the 90-percent
confidence interval would be greater than zero. In this case, it is likely (at
least a 90-percent chance) that nonfarm employment had, in fact, risen that month.
At an unemployment rate of around 6.0 percent, the 90-percent confidence interval
for the monthly change in unemployment as measured by the household survey is
about +/- 300,000, and for the monthly change in the unemployment rate it is about
+/- 0.2 percentage point.
. . .
The household and establishment surveys are also affected by nonsampling error,
which can occur for many reasons, including the failure to sample a segment of the
population, inability to obtain information for all respondents in the sample,
inability or unwillingness of respondents to provide correct information on a
timely basis, mistakes made by respondents, and errors made in the collection or
processing of the data.
. . .
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ETA
https://www.bls.gov/news.release/empsit.nr0.htm
May was revised down by 125k
June was revised down by 133k
As Wiz Imp points out, both are within the 90% confidence interval for sampling error (136k). And then non-sampling error
like late responses to surveys are additional
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