What I'm ready to say and what's more meaningful for me to comment is that I don't believe that anything essential is left hidden or that
any significant errors in data based on instrumental records were left uncovered by the questionable actions.
Not exact matches
In addition, Fortune excludes companies that have announced intentions to restate previously reported financial
data, if these
errors appear to have a
significant impact.
In fact, an error in the data later came to light and, once this had been corrected (published in an erratum in a later issue of the Journal), it became clear that there was actually no significant change in teenage pregnancy rate
In fact, an
error in the data later came to light and, once this had been corrected (published in an erratum in a later issue of the Journal), it became clear that there was actually no significant change in teenage pregnancy rate
in the
data later came to light and, once this had been corrected (published
in an erratum in a later issue of the Journal), it became clear that there was actually no significant change in teenage pregnancy rate
in an erratum
in a later issue of the Journal), it became clear that there was actually no significant change in teenage pregnancy rate
in a later issue of the Journal), it became clear that there was actually no
significant change
in teenage pregnancy rate
in teenage pregnancy rates.
A
significant error in some published research on birth place is amalgamating
data from unplanned home births (without skilled birth attendants) with
data from planned births at home or
in birth centres within integrated systems.
«Long propagation delays, Doppler effects due to vehicle and water movement, and the highly dynamic multipath nature of the undersea environment result
in significant errors and outliers
in received
data measurements.
However, the fact that we find very «precise zeros» — that is, we don't find statistically
significant relationships even though we have the statistical power
in our
data to detect even very modest relationships — implies that neither measurement
error nor a lack of sufficient variation are what's driving our inability to detect a relationship between teaching and research quality.
Even though the Argo buoy
data demonstrates a increase
in SST's and require
error correction for the pressure sensors I have not seen
significant data suggesting that there is any heating at depth.
Is there evidence of
significant error / uncertainty
in the GRACE
data?
«What is needed is that there are no major but unknown systematic changes
in, how the
data is collected... Independent
errors cancel out well and their size can be estimated from the
data, while systematic
errors may remain a
significant problem, whose size is difficult to estimate».
A
significant reduction
in the uncorrelated random
error in the
data has been proven for both regular temporal
data and rapid - sample
data.
Yet if this
data has * no
significant effect * on the Antarctic Warming conclusion then this
error is not all that relevant as RC has suggested (unconvincingly so far
in my view)
Previously reported discrepancies between the amount of warming near the surface and higher
in the atmosphere have been used to challenge the reliability of climate models and the reality of human - induced global warming... This
significant discrepancy no longer exists because
errors in the satellite and radiosonde
data have been identified and corrected.
A study about method of
error correction that does not alter results
in a statistically
significant manner should / can not be used effectively to refute the confidence
in the
data as known and understood.
If no
error in capturing the
data, what possible real life situation would cause what appears as a
significant statistical outlier.
John Christy, the scientist and interviewee on whose work this latter claim is based, seems to have forgotten that he had written
in a US Climate Change Science Program report: «This
significant discrepancy [between lower and upper atmosphere warming] no longer exists because
errors in the satellite and radiosonde [weather balloon instrument]
data have been identified and corrected.
However, detailed statistical analyses of the available satellite
data (RSS, UMd, UAH) since 1979 and of radiosonde
data (HadAT, RATPAC, RICH, and IUK) since about 1959 has revealed that there are
significant errors and uncorrected biases
in all datasets.
If you know the standard -
errors of the various
data - point (i.e. global mean temperature) estimates, we can check if it's statistically
significant via a difference
in means test, while accounting for correlation
in estimator distributions (it should be, unless NASA can't measure at all, which I sincerely doubt).
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