Sentences with phrase «own statistical uncertainty»

The usual health warnings were issued in the form of statistical uncertainty estimates, but these invitations to prudence were given less attention than they deserved by most consumers of the numbers.

The model predictions are therefore reliable, taking some statistical uncertainty into account.

They should also develop more sophisticated models that better incorporate statistical uncertainties.

At nearly a dozen other sites, the authors report, the chronological results are neither reliable nor valid as a result of significant statistical flaws in the analysis, the omission of ages from the models, and the disregard of statistical uncertainty that accompanies all radiometric dates.

When we apply our approach to the complete data collection, we will largely eliminate the station selection bias, and significantly reduce statistical uncertainties.

«We were really beating down the statistical uncertainty.»

But because many countries have little surveillance data available, the statistical uncertainty is still huge, ranging from 71,000 to 447,000 deaths for the year 2010.

All of the relationships have statistical uncertainty.

1 degree is much larger than the statistical uncertainty.

The model results (which are based on driving various climate models with estimated solar, volcanic, and anthropogenic radiative forcing changes over this timeframe) are, by in large, remarkably consistent with the reconstructions, taking into account the statistical uncertainties.

Finally, I note that statistical uncertainty has been estimated according to the IPCC AR5 method, which was in turn based on the autocorrelation adjustment method in Santer et al (2008) on which you (Gavin) were a co-author.

Although some earlier work along similar lines had been done by other paleoclimate researchers (Ed Cook, Phil Jones, Keith Briffa, Ray Bradley, Malcolm Hughes, and Henry Diaz being just a few examples), before Mike, no one had seriously attempted to use all the available paleoclimate data together, to try to reconstruct the global patterns of climate back in time before the start of direct instrumental observations of climate, or to estimate the underlying statistical uncertainties in reconstructing past temperature changes.

These authors have shown that the «alternative» reconstruction promoted by McIntyre and McKitrick (which disagrees not only with the Mann et al reconstruction, but nearly a dozen independent reconstructions that agreee with the Mann et al reconstruction within statistical uncertainties) is the result of censoring of key data from the original Mann et al (1998) dataset.

Cox et al. provide a statistical uncertainty range for a single study, ignoring structural uncertainty and systematic biases resulting from their choice of model and method.

The IPCC range, on the other hand, encompasses the overall uncertainty across a very large number of studies, using different methods all with their own potential biases and problems (e.g., resulting from biases in proxy data used as constraints on past temperature changes, etc.) There is a number of single studies on climate sensitivity that have statistical uncertainties as small as Cox et al., yet different best estimates — some higher than the classic 3 °C, some lower.

Hardly within the limits of statistical uncertainty.

And I really wish people wouldn't talk about «statistical uncertainty» of models.

Given the statistical uncertainty in determining pre-1800s temperatures (see graph below) that requires greater than 50 % of the warming be attributed to anthropogenic factors.

To me that is completely irrelevant, because it was already known that there are limits of modeling performance that are stricter that those set by the statistical uncertainties.

The different conclusions arise at least in part because the studies have systematically underestimated statistical uncertainties.

If we have inadequate sampling, and short time intervals, the statistical uncertainties from random fluctuations and random measurement errors can be large, but would tend to cancel out as the number of observations and length of time increases.

Such issues of robustness need to be taken into account in estimates of statistical uncertainties.

There is not any REAL issue relevant that is including any regard for «citations» of «statistical uncertainty» with mention of «confidence levels» with relevance to the «hockey stick» or «recurring hockey stick debate», nor is there relevance in attempting to present those upon the «greenhouse wagon» as «the scientists».

We applied the same method used in the observational analysis on general circulation model data to decrease the statistical uncertainty at the expense of an increased systematic uncertainty.

As well, the statement «Whether we have the 1000 year trend right is far less certain» is in fact an admission of the lack of sufficient knowledge about the correctness of the application of the reconstruction procedure and really should not be interpreted as a scientific assessment of statistical uncertainty.

The Pacific Walrus is now believed to have recovered fully to its historic population of about 200,000, but surveys have been limited and therefore carry great statistical uncertainty.

The «monster» metaphor is rather misleading, because, as your article makes clear, there seems to be a whole menagerie of uncertainty monsters out there — statistical uncertainty, methodological, uncertainty in the setting of parameters in models etc..

As a requirement, the statistical uncertainty associated with the effect of the adjustments on the regional temperature record needs to be quantified and documented.

What is the justification for adjusting past values, and is there any way to convey the increasing level of statistical uncertainty in the USHCN values, like confidence intervals or error bars on charts?

A continued mode of corrections using approaches where statistical uncertainties are not quantified is not a scientifically sound methodology and should be avoided, considering the importance of such surface station data to a broad variety of climate applications as well as climate variability and change studies.

The biggest problem, I believe, with the IPCC reports is the lack of discussion of statistical uncertainties.

The uncertainty monster paper distinguished between statistical uncertainty and scenario uncertainty:

IMO we should be treating this situation as scenario uncertainty and not statistical uncertainty.

Particle physicists, like Brian Cox, are particularly obsessed with statistical uncertainty, witness 5 sigma results required for statistical significance to confirm the discovery of the Higg's boson.

For this reason, the proxies must be «calibrated» empirically, by comparing their measured variability over a number of years with available instrumental records to identify some optimal climate association, and to quantify the statistical uncertainty associated with scaling proxies to represent this specific climate parameter.

The implication in employing these methods is that in this particular region, the uncertainty from methodology (not included in statistical uncertainty by variance) is somewhat greater than elsewhere in the reconstruction.

The mean carries its own statistical uncertainty, but the physical uncertainty of the original data has to be calculated separately and included in any discussion of significance.

It can also have a statistical uncertainty calculated according to the statistical model, 0.03 C.

One can dismiss Beenstock and Reingewertz because they are wading into an area of statistical uncertainty, but any of us who are making inferences about temperature trends should realize we are all wading in the same waters.

Otherwise there is the risk of unreliable results and statistical uncertainty.

Not exact matches

Until, and once the uncertainty is reduced, THEN we can get back to a cyclic economy with statistical smoothing that offers better predictions of our future.

there's really no room for the concept of an independent entity possessed of «will» in a worldview shaped by cause and effect; the only place for «will» to retreat to is the zone of true randomness, of complete uncertainty, which means that truly free will as such must be completely inscrutible [sic]... Statistical laws govern the decay of a block of uranium, but whether or not this atom of uranium chooses to fission in this instant is a completely unpredictable event — fundamentally unpredictable, something which simply can not be known — which is equally good evidence for the proposition that it's God's (or the atom's) will whether it splits or remains whole, as for the proposition that it's random chance.

The team honed their statistical models to further take into account such uncertainties and possibly created a statistical first.

The new approach contrasts with previous ways scientists analyzed and came to conclusions about sea level rise because it is «the only proper one that aims to fully account for uncertainty using statistical methods,» noted Parnell, principal investigator of the study conducted collaboratively with researchers at Tufts University, Rutgers University and Nanyang Technological University.

However, in order to know that such a deviation (if observed) is not just a statistical fluctuation, the difference must be conclusive — it must be at least five times larger than the experimental and theoretical uncertainties.

In her doctoral thesis, Henni Pulkkinen, Researcher at the Natural Resources Institute Finland (Luke), explored how the various sources of uncertainty can be taken into account in fisheries stock assessment by using Bayesian statistical models, which enable extensive combining of information.

This is intended to take account of some of the uncertainties inherent in data on whale populations, and requires only two kinds of data: current estimates and their statistical error; and historical details of catches.

The journal Basic and Applied Social Psychology recently banned the use of p - values and other statistical methods to quantify uncertainty from significance in research results

Acín's group used statistical tests to show that the output from the new device indeed stems from quantum uncertainty rather than from residual deterministic — and hence predictable — effects.

The U.S. Bureau of the Census is locked in a high - stakes political battle with Congress over a plan to reduce uncertainties in the year 2000 survey through statistical techniques rather than direct head counts.