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variance$89565$ - vertaling naar grieks

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).

variance      
n. διαφορά, διακύμανση, διαφωνία

Definitie

variance
n. 1) an exception to a zoning ordinance, authorized by the appropriate governmental body such as a planning commission, zoning board, county commissioners or city council. Example: the zoning ordinance requires that no residences can be built within 10 feet of a property's back line, but due to the odd shape of May Matheson's property, she needs to build her dream house within five feet of the property line at one point. The local zoning board listens to her plea, finds that the neighbors do not object, and grants her a variance to build closer to the back line. 2) a difference between what the prosecution has charged and what it has proved against a criminal defendant. 3) a difference between what is alleged in a civil complaint and what is proved. A substantial variance may be fatal to the prosecution's case against the accused or fatal to a plaintiff's (the person who filed the suit) lawsuit. In each case the judge can dismiss the case as a matter of law, without sending the factual issues to the jury. In criminal cases the test of a fatal variance is somewhat stricter than in a civil lawsuit, since a minor difference between the charge and the proof may mislead the defendant and deny him/her "due process." See also: dismissal proof

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.