Search results
Results From The WOW.Com Content Network
An area variance is the most common type. It can be requested by a builder or landowner when an odd configuration of the land, or sometimes the physical improvements (structures) on the land, requires a relaxation of the applicable regulations to avoid denying the landowner the same rights and use of the property enjoyed by owners of ...
Therefore, the variance of the mean of a large number of standardized variables is approximately equal to their average correlation. This makes clear that the sample mean of correlated variables does not generally converge to the population mean, even though the law of large numbers states that the sample mean will converge for independent ...
Using simulated data sets, Richardson et al. (2009) investigate three ex post techniques to test for common method variance: the correlational marker technique, the confirmatory factor analysis (CFA) marker technique, and the unmeasured latent method construct (ULMC) technique.
In the words of one critic: "Thus gives the 'percentage of variance explained' by the regression, an expression that, for most social scientists, is of doubtful meaning but great rhetorical value. If this number is large, the regression gives a good fit, and there is little point in searching for additional variables.
For any index, the closer to uniform the distribution, the larger the variance, and the larger the differences in frequencies across categories, the smaller the variance. Indices of qualitative variation are then analogous to information entropy , which is minimized when all cases belong to a single category and maximized in a uniform distribution.
The Allan variance can be used for applications where the noise disrupts convergence. [2] The Hadamard variance can be used to counteract linear frequency drift sensitivity. [3] For categorical variables, it is less common to measure dispersion by a single number; see qualitative variation. One measure that does so is the discrete entropy.
This follows from the fact that the variance and mean are independent of the ordering of x. Scale invariance: c v (x) = c v (αx) where α is a real number. [22] Population independence – If {x,x} is the list x appended to itself, then c v ({x,x}) = c v (x). This follows from the fact that the variance and mean both obey this principle.
In estimating the mean of uncorrelated, identically distributed variables we can take advantage of the fact that the variance of the sum is the sum of the variances.In this case efficiency can be defined as the square of the coefficient of variation, i.e., [13]