Sentences with phrase «series of data points»

«Curve fitting is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, possibly subject to constraints.»

How can one single data point (the average growth for the observation period) correlate with a series of data points (annual growths)?

In it, they listed a series of data points that will determine whether the planet remains habitable.

When you record a series of data points, each one is actually an average.

In amongst the multimedia examples in the column was one from Teddy TV titled «Trend and variation» — purporting to teach the viewer the difference between trend («an average or general tendency of a series of data points to move in a certain direction over time, represented by a line or curve on a graph») and variation («common cause variation is also known as «noise» or «natural patterns,»» the squiggles on a graph).

Both the original red curve from 2009/2010 and the January 2nd, 2012 green curve are based on a series of data points for sales ranks bracketing each other.

Those numbers are just a few of a series of data points that add up quickly.

Not exact matches

Some time after this Decision Point began collecting NYSE common stock only (CSO) breadth and volume data, and we have a set of NYSE CSO indicators that are available to subscribers through our Straight Shots Menu, as well as various indicator series.

Official wage data also show ongoing strength in public - sector wage growth and a significant rise in wage growth in education: the WPI measure of public - sector wage growth increased by 4.2 per cent over the year to December, almost 1 percentage point higher than the equivalent private - sector wage series.

Using the 1974 Filer Commission religion estimate of $ 11.7 billion as a base point, and then using available denominational data on giving, a series of annual figures for the years 1968 through 1973 and 1975 through 1995 can be calculated.

For political surveys, census bureau data provides a starting point and a series of screening questions are used to determine likely voters.

«There aren't any new data presented, but we have a wealth of anecdotal evidence» pointing to a shortage of domestic scientific talent, says Joseph Miller, Corning's chief technology officer and chair of the task force, which has held a series of open meetings to discuss a long - awaited report that it plans to present to the board next week.

Measurements of the time series provide a number of data points, N, that can be geometrically analysed.

The $ 145 - million project, called NEPTUNE Canada (North - East Pacific Time - Series Undersea Networked Experiments), has laid 800 kilometers of cable to transmit power and data, and established five «nodes» that act like giant, 13 - tonne plug - in points for scientific instrumentation, lying up to 2.6 kilometers beneath the waves.

Of course the starting point is the DfE data driven definition — a complex series of criteria over the last three years against changing thresholds and expectationOf course the starting point is the DfE data driven definition — a complex series of criteria over the last three years against changing thresholds and expectationof criteria over the last three years against changing thresholds and expectations.

Significantly minimizing the role of any single standardized test to its appropriate role as one data point in a series of overall performance criteria,

Mercedes - Benz describes this figure as being «unrivalled in the super sportscar segment and one that guarantees exceptionally dynamic performance» — a statement that has led to rumors suggesting the performance data may in fact point to a Black Series variant of next year's GT AMG due to make an appearance in 2016.

Mark Coker, CEO and founder of Smashwords, explained two new data points in this year's survey, gauging the impact of the new pre-order feature and the way series titles were impacted in all of Smashwords» distribution channels.

[5] The organization of a time series object is set by its frequency, which is the integral number of data points in each time cycle.

It would help to have a sense of how well DLC sells, but as longtime developer Ryan Clark points out in a recent episode of his «Shark Tank» series of game dev livestreams, it's very hard to get that data.

By drawing connections between these points, Oursler is filtering surveillance data through the lens of portraiture to arrive at a series of haunting red, black, white, blue and gold - leafed faces — some amalgams, others fixed — that appear trapped behind this mapping matrix.

On the topic of temperature series in general, can anyone point me to an archived copy of the 5.1 version of the UAH lower troposphere data?

They neglect the pre-1980s temperatures, the post-2000 temperatures, and the recent millennium of historical temperatures — they take a few unidentified data points out of a long series that support their desired point — fail to mention those data points and past trends that refute their point — and assert that they have presented a valid overall picture — in short, cherry - picking.

The series is only 42 data points long (equating to 126 years), so is hardly robust, however, it may be a useful predictor of future temps since it is gistemp that lags the SST.

If the time series is inherently discrete, what you really want is the DTFT (Discrete - Time Fourier Transform) but to compute that you'd need an infinite number of data points, obviously an impossibility.

Surely, it is more than just a comparison of two data points of a noisy time series?

Unfortunately for Don, the first data point in the temperature series he's relying on is not from the «top of the core», it's from layers dated to 1855.

You may be interested to read about a very recent analysis that seems to address this kind of point, ie how sensitive is the conclusion to any single data series.

It is very simple to explain: Since the ACC (anthropomorphic climate change, aka «Man - caused global warming») is a by a series of cherry - picked data points represented by constantly flawed and failing models, it was decided to remove the PC motivated opinion aspect.

Someone points out that instead of putting in supposed temperature related data if you put in randomly generated data series you STILL almost always get a hockey stick graph as output.

John S: Any competent signal analyst, not just Parzen, is keenly aware that an exact Fourier decomposition of ANY bounded series of N real - valued data points consists of N complex - valued coefficients specifying the amplitude and phase of a HARMONIC series of sinusoids.

Any competent signal analyst, not just Parzen, is keenly aware that an exact Fourier decomposition of ANY bounded series of N real - valued data points consists of N complex - valued coefficients specifying the amplitude and phase of a HARMONIC series of sinusoids.

Second why not hold out 50 % of your temp time series (random selection of each data point perhaps), do your analysis on on one half and check the fit to the other.

Apparently you've forgotten that you wrote Any competent signal analyst, not just Parzen, is keenly aware that an exact Fourier decomposition of ANY bounded series of N real - valued data points consists of N complex - valued coefficients.

Spencer's theory is just one argument at this point, without a long term series of data that supports it, as far as I am aware.

Methodology for statistics geeks: take the data from the figure I referenced, compute the departure of each data point from the linear regression value corresponding to its ENSO category for the midpoint year (2004), and analyze the resulting time series.

On that point his conclusion was that the data and analysis did not support the conclusions that had been drawn, and the independent evidence cited in its favour was not independent at all — the data sets were full of repeated series and the authors were too interconnected.

My understanding is that this data series is a subset of the ones you refer to, which in turn were cited by the IPCC as a proxy for NH temps, just as I pointed out.

Infact, the procedure of determining the behavior of such processes, a Statistical analytic process titled a «Time series» uses all data points that are collected within the method determined by the pre-procedure of «Experimental Design», made to facilitate the analysis in a manner of known (and best) correlation.

You can take out data points you don't like, you can apply whatever correction factors you want (such as the one that Nasa's GISTEMP series uses to compensate for the dearth of measuring stations across the Arctic), and you can therefore end up with a temperature curve that might look a little different: but don't say it can't be done, because it can.

Another points worth mentioning when comparing temperature series is that there was some sort of instrument change in the satellite data around 1992.

Furthermore, as shown in Table 1 of Koutsoyiannis and Montanari (2007), 150 years of climatic data (the CRU time series) are equivalent to about 2 data points in the classical statistical sense, if the LTP hypothesis is true.

In the coming weeks, we will make a series of inquiries to ensure EPA's process governing the development of the endangerment finding is open and transparent — and that the Agency considers all view - points, and makes use of the best available, and most up - to - date, scientific data.

The trick actually consists of splicing instrumental data onto the reconstructed series (starting at 1980), smoothing the resulting series, then truncating the series at the point the instrumental data had been appended.

Looking at these results, that are admittedly anecdotal at this point, I see generally better fits to a normal distribution and lower autocorrelation (AR1) in the residuals as one goes from monthly to individual months to annual data series and as one goes to sub periods of a long term temperature anomaly series.

I wouldn't have a clue how to find such a thing, but it might be interesting and a very long series of measured data points — about all one could measure and record before thermometers.

The other aspect of this post, which is to look at the RCS average curve for subsets of the data, and then express surprise when differences are found, completely misses the point of the RCS method in the first place which is to first remove the common growth - related signal from the entire series before looking at any environmental influence.

It is pure cyclomania that has no possible point, neglects fundamental physics and has no understanding of why climate data series behave as they do.

Nor do the above caveats of non-robustness properly deal with the dependence of their 20th century uptick on their deletion of 20th century data points from critical series and the importation of earlier data points into the 20th century by unjustifiable coretop re-dating.

As GISS uses now GHCN, and given the structure of the GHCN data (rather short series) and the adjustment method used, ultimately, GISS is not far from BEST on this point.