If I go out and measure something, anything, and plot the points of a piece of graph paper, and the points may lie on a straight line, some sort of curve, or there may be so
much noise in the data that no trend is apparent, then this is what fits the data.
As SkS has discussed at length with Dr. Pielke Sr., over short timeframes on the order of a decade, there is too
much noise in the data to draw any definitive conclusions about changes in the long - term trend.
Not exact matches
There was too
much noise in the system, and distinguishing planets from other variations
in the
data was a harder task than expected.
Other
data are often just
noise: For example, it's interesting that children enrolled
in Head Start may be less likely to take to crime as adults, but it's pretty
much irrelevant to judging the efficacy of an expensive government program that's failed to show
much in terms of student performance.
The error bars (based on standard errors) roughly estimate of how
much each beta value could reasonably vary due to
noise in the
data.
So, if I understand your post, which I probably don't (because I think there is quite a bit of jibberish
in there), there is too damn
much variation, variables,
noise, etc., etc.
in tree ring
data to extract a temperature record — without discovering and applying some type of «magic statistics» (which is what I think the HS team have been trying to do).
The «short - centered» leading eigenvalue (EV) magnitude for Mann's tree - ring
data is
much larger than the corresponding EV magnitudes produced
in M&M's «red
noise» runs.
In the pharmaceuticals manufacturers» efforts to gain as much promotional «noise» as possible from research conducted in compliance with FDA and EMEA requirements for marketing approval, this comes under the heading of publications planning, the extraction from available study data of as many additional articles and presentations as can be manage
In the pharmaceuticals manufacturers» efforts to gain as
much promotional «
noise» as possible from research conducted
in compliance with FDA and EMEA requirements for marketing approval, this comes under the heading of publications planning, the extraction from available study data of as many additional articles and presentations as can be manage
in compliance with FDA and EMEA requirements for marketing approval, this comes under the heading of publications planning, the extraction from available study
data of as many additional articles and presentations as can be managed.
In some cases, it seems to me that the argument in favor of a correlation is so strong that, if we don't see a correlation historically, we have to simply wonder if there is enough data yet to see the correlation, if we are asking the right questions, if there is so much background noise that it masks why is potentially a very significant correlation — or some combination thereo
In some cases, it seems to me that the argument
in favor of a correlation is so strong that, if we don't see a correlation historically, we have to simply wonder if there is enough data yet to see the correlation, if we are asking the right questions, if there is so much background noise that it masks why is potentially a very significant correlation — or some combination thereo
in favor of a correlation is so strong that, if we don't see a correlation historically, we have to simply wonder if there is enough
data yet to see the correlation, if we are asking the right questions, if there is so
much background
noise that it masks why is potentially a very significant correlation — or some combination thereof.