Sentences with phrase «average variance of»

Not exact matches

Every sport, athlete, and family has different amounts of «investment» needed, and it's probably too difficult to calculate an average expenditure in a meaningful way due to the massive variance.

Longford - Westmeath — The current population levels in Longford - Westmeath are fine for this constituency to remain as a 4 - seat constituency (with a population per TD ratio 0.6 % higher than the state average), but the return of the Castlepollard area to join with the rest of Westmeath county in this constituency would probably not be feasible as this would leave the constituency with a population per TD ratio that would be 7.75 % higher than the state average (close to the 7.89 % maximum degree of variance permitted by past Commission reports).

The one - dimensional Gaussian is completely described by two parameters: the mean, or average, value of the data, and the variance, which is a measure of how quickly the data spreads out around the mean.

The sign and size of the bias would depend on the relative magnitude of the average and variance of the underreporting, as well as the covariance between the underreported, and other variables in the model, and would be typically less than the omitted variable bias were these variables to be left out (10, 11).

The branch lengths of the high - variance exon tree showed a strong positive correlation with GC content and a negative correlation with the average body mass of species, seen at a much lesser magnitude in the low - variance exon tree (Fig. 6, A to D).

Additionally, we performed a Hidden Cookie Test to evaluate general olfaction and observed no difference between uninfected and infected animals (Uninfected, Type I -, and Type III - infected animals found the cookie on average within 96 ± 14, 109 ± 18, and 123 ± 31 seconds, respectively where variance indicates Standard Error of the Mean).

The combination provides for a dramatic increase in record hot weather.27 Here «variance» is a measure of the spread of temperatures around the «mean» or average temperature.

The variance in performance mimics the air of inconsistency that envelops the entire production: a fairy tale concept enlivened with average special effects, a plight predicated upon purportedly epic affection rendered with the most rote and unearned of emotion, and a tale supposedly larger - than - life but lacking in enthusiasm or investment.

Defined as perseverance and passion for long - term goals, grit accounted for an average of 4 percent of the variance in success outcomes, including educational attainment among two samples of adults; grade point average among Ivy League undergraduates; retention among two classes at the United States Military Academy, West Point; and ranking in the Scripps National Spelling Bee.

In Australia in 2012, 55 per cent of the observed between - school variance in PISA mathematics was associated with differences between schools in average socioeconomic background.

If a state with a 0.17 coefficient spent $ 13,000 per pupil, the average variance among district spending within the state would range from $ 11,310 to $ 14,690 per pupil ($ 1,690 above or below the mean of $ 13,000).

In comparing the results of the Program for International Student Assessment in 65 countries, OECD researchers found that differences among countries grade - retention trends could explain up to 15 percent of the variance among average scores on the 2009 PISA.

Extending a theoretical model of causal inference, I define, identify, and estimate the population average and the between - site variance of the direct and indirect effects.

In 2012, one of my graduate students and I explored this question using data of 191 high schools in Connecticut and found that multiple linear regressions revealed that 69 % of the difference (variance) in a school's average student achievement can be explained by the percentage of students living in poverty.

Three analyses were conducted with the cross-sectional data using teachers» WSS ratings of student achievement and students» WJ - R standard scores: a) correlations comparing the students» standard scores on the various subtests of the WJ - R and the WSS checklist and summary report ratings of student achievement within the corresponding WSS domains, b) four - step hierarchical regressions examining the different factors that accounted for the variance in students» spring WJ - R scores, and c) Receiver - Operating - Characteristic (ROC) curves, which make possible a determination of whether a random pair of average and below - average scores on the WJ - R would be ranked correctly in terms of performance on the WSS.

There's only four hundredths of a second variance at 60mph, 4.49 sec in one direction, 4.53 in the other for a 4.51 sec average, beating Porsche's 0 - 62mph claim by 0.09 sec, despite a full tank and two occupants.

In other words, variance is a mathematical expectation of the average squared deviations from the mean.

Portfolio variance is calculated by multiplying the squared weight of each security by its corresponding variance and adding two times the weighted average weight multiplied by the covariance of all individual security pairs.

The annualized return (approximately) equals the average return minus one - half of the standard deviation squared (or one - half of the variance).

Third, realized variance of the hedging portfolio or of the value premium is closely correlated with the average IV, and these variables have similar predictive power for stock returns.

Of course, that is just an average and there can be much variance depending on breed and a particular dog (see our FAQ about heats in dogs.)

Tuning to the seasonal cycle, or to the climatological average, or to the variance of some field — which can be well characterised from observations, is different to tuning to a transient change of over time — which is often less well known.

Averaging as many trees as possible will strengthen the common (climate) signal and reduce the noise, therefore improve the reconstruction quality (without some weighted mean statistics, for two trees, each will contribute 1/2 of the variance of a proxy time series — for 8 trees only 1/8 and so on).

I don't know how to do this perfectly properly, but using paired months (jan - jan, feb - feb etc) to get the average diff and variance (45 minutes of work in a spread sheet), I did paired t on the last 15 years or so (NOAA data), and this is what got and what I probably would say:

Mark, by «VERY GOOD» do you mean the reliability, variances and error bars of measuring average global mean temperatures and CO2 mixing ratios over the past 150 years is about as good as measuring your height over the past 30 years?

This amount of variance suppression is roughly what you would expect if the underlying annual temperature time series had been smoothed with a 400 - year moving average.

For example, average insolation on the 21st day of June at 65 - N has 80 % of its variance at the precession periods (1/21 ky + / - 1/100 ky).

THen the other 12 will cancel out to a very small amplitude average (since the variance of the mean of random data obeys a central limit law) and the HS will emerge out of it.

In the global average and at many locations, it is the dominant source of variance in late 21st century projections, though at some sites oceanographic processes contribute the largest share throughout the century.

That fluctuation is amplified by land surface temperatures in the same latitude band of about the same area, because the land surface temperatures are at a higher average altitude with a lower average specific heat capacity and the (Tmax + Tmin) / 2 method of determining «average» amplifies the variance.

The increase in zonal variance of P — E means that regions that are wetter than the zonal mean will get wetter on average and that regions that are drier than the zonal mean will get drier on average.

A number of analysis methods have a tendency to lose variance at a range of time scales either because they do not explicitly resolve small scale processes (Kaplan et al. 1997, Smith et al. 2008) or because in the absence of data the method tends towards the climatological average (Ishii et al. 2005).

If some area is for part of the year exceptionally variable this particular data may add greatly to the variance of the average while it tells little of the actual warming defined by energy flows.

When an average is calculated to cover all year and all parts of the surface where measurements are available, different parts of the whole contribute both to the average (or its trend) and to the variance of the result.

Owing to the decreased number of spatial degrees of freedom in the earliest reconstructions (associated with significantly decreased calibrated variance before e.g. 1730 for annual - mean and cold - season, and about 1750 for warm - season pattern reconstructions) regional inferences are most meaningful in the mid 18th century and later, while the largest - scale averages are useful further back in time.

The model's ensemble - mean EOF accounts for 43 % of the variance on average across the 40 ensemble members, and is largely similar to observations although the centers - of - action extend slightly farther east and the southern lobe is weaker (maximum amplitude of approximately 2 hPa compared to 3 hPa in observations; Fig. 3c).

In paleoclimate, if you want to know the certainty of the average trend in the blade of the stick, you wouldn't take the extremes of all the inputs to calculate uncertainty, you take the variance in the output and use some method i.e. monte carlo or a DOF estimate.

The latter can also be inferred from maps of the variance of monthly precipitation, so is not simply a consequence of the smaller areas of the southern regions or the four - month averaging.

By the way, although I have not read the paper, «variance corrected means» probably refers to some technique to obtain more accurate estimates of the means, the averages in the series, using information on the variance of the error of estimating these averages which would have varied from year to year.

It seems to me that the variance for a given time span, say some decade, is the sum of two components: the spatial variance (basically, the different averages value between different regions) and the temporal variance, which includes both the trend and the fluctuations.

That is particularly the case in California, where decadal precipitation variance is typically equivalent to 20 — 50 % of mean annual averages, mostly because of changes in precipitation received between November and March [16 — 17].

Note that the HSI is relative to the total variance of the PC1 — averaging the realisations reduces the variance which increases the HSI.

Running ensembles of five simulation runs and averaging them is completely equivalent to a five sample Monte Carlo, which would almost never yield any real variance reduction at all.

A simple precision to what I mean by the sensitivity linked to S - B blackbody radiation should consider both average T, but also the variance of T both spatially and temporally.

The more linear (lower variance) the average output in two models, the higher the r2, purely as a result of increased autocorrelation.

If you have Mandelbrot - type autocorrelation, why are [time] averages or 2nd moments of «climatology» not themselves as transitory as the global average temperature or variance from 3 to 4 pm EST on April 11, 1956?

However, the variances of the terms being averaged arenot the same because of the adjustment step and this means that any confidence intervals for the estimate may vary from year to year depending on the ages of the trees contributing to the that year's average.

More on averaging: When calculating averages and then pretending that the averaged data is the source data, calculations of statistics produce misleadingly reduced variance (and thus misleading estimates of significance).

Taking averages of multiple models and mentioning averages and variances is pretty much nonsense..

To take possible seasonal adaptation or lifecycle effects, the best way is to check the variance of the smoothed time history, smoothed with a moving average on a typical lifetime for the ecosystem (10 years seems fine).