budget variance - meaning and definition. What is budget variance
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What (who) is budget variance - definition

EXPECTATION OF THE SQUARED DEVIATION OF A RANDOM VARIABLE FROM ITS MEAN
Sample variance; True variance; Var(X); Sample Variance Computation; Sample variance computation; Population variance; User:Skbkekas/Population variance; Scaled chi-squared distribution; Random variance; Variance generalizations
  • Example of samples from two populations with the same mean but different variances. The red population has mean 100 and variance 100 (SD=10) while the blue population has mean 100 and variance 2500 (SD=50).

Bias–variance tradeoff         
  • Bias and variance as function of model complexity
PROPERTY OF A SET OF PREDICTIVE MODELS WHEREBY MODELS WITH A LOWER BIAS IN PARAMETER ESTIMATION HAVE A HIGHER VARIANCE OF THE PARAMETER ESTIMATES ACROSS SAMPLES, AND VICE VERSA
Bias variance; Bias-variance tradeoff; Bias-variance dilemma; Bias–variance dilemma; Bias-variance decomposition; Bias–variance decomposition; Bias and variance tradeoff; Bias--variance tradeoff
In statistics and machine learning, the bias–variance tradeoff is the property of a model that the variance of the parameter estimated across samples can be reduced by increasing the bias in the estimated parameters.
Carbon budget         
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LIMIT ON CO2 EMISSION FOR A GIVEN CLIMATE IMPACT
Global carbon budget; Emissions budget; User:Maida h4/sandbox
A carbon budget is "the maximum amount of cumulative net global anthropogenic carbon dioxide () emissions that would result in limiting global warming to a given level with a given probability, taking into account the effect of other anthropogenic climate forcers". When expressed relative to the pre-industrial period it is referred to as the Total Carbon Budget, and when expressed from a recent specified date it is referred to as the Remaining Carbon Budget.
Allan variance         
  • (''y'' − ''y''′)<sup>2</sup>}} is equal to twice the Allan variance (or Allan deviation squared) for observation time ''τ''.
  • Example plot of the Allan deviation of a clock. At very short observation time ''τ'', the Allan deviation is high due to noise. At longer ''τ'', it decreases because the noise averages out. At still longer ''τ'', the Allan deviation starts increasing again, suggesting that the clock frequency is gradually drifting due to temperature changes, aging of components, or other such factors. The error bars increase with ''τ'' simply because it is time-consuming to get a lot of data points for large ''τ''.
MEASURE OF FREQUENCY STABILITY IN CLOCKS AND OSCILLATORS
Allen variance; Allan deviation; Allan Variance; ADEV
The Allan variance (AVAR), also known as two-sample variance, is a measure of frequency stability in clocks, oscillators and amplifiers. It is named after David W.

Wikipedia

Variance

In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its population mean or sample mean. Variance is a measure of dispersion, meaning it is a measure of how far a set of numbers is spread out from their average value. Variance has a central role in statistics, where some ideas that use it include descriptive statistics, statistical inference, hypothesis testing, goodness of fit, and Monte Carlo sampling. Variance is an important tool in the sciences, where statistical analysis of data is common. The variance is the square of the standard deviation, the second central moment of a distribution, and the covariance of the random variable with itself, and it is often represented by σ 2 {\displaystyle \sigma ^{2}} , s 2 {\displaystyle s^{2}} , Var ( X ) {\displaystyle \operatorname {Var} (X)} , V ( X ) {\displaystyle V(X)} , or V ( X ) {\displaystyle \mathbb {V} (X)} .

An advantage of variance as a measure of dispersion is that it is more amenable to algebraic manipulation than other measures of dispersion such as the expected absolute deviation; for example, the variance of a sum of uncorrelated random variables is equal to the sum of their variances. A disadvantage of the variance for practical applications is that, unlike the standard deviation, its units differ from the random variable, which is why the standard deviation is more commonly reported as a measure of dispersion once the calculation is finished.

There are two distinct concepts that are both called "variance". One, as discussed above, is part of a theoretical probability distribution and is defined by an equation. The other variance is a characteristic of a set of observations. When variance is calculated from observations, those observations are typically measured from a real world system. If all possible observations of the system are present then the calculated variance is called the population variance. Normally, however, only a subset is available, and the variance calculated from this is called the sample variance. The variance calculated from a sample is considered an estimate of the full population variance. There are multiple ways to calculate an estimate of the population variance, as discussed in the section below.

The two kinds of variance are closely related. To see how, consider that a theoretical probability distribution can be used as a generator of hypothetical observations. If an infinite number of observations are generated using a distribution, then the sample variance calculated from that infinite set will match the value calculated using the distribution's equation for variance.