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The mean and the standard deviation of a set of data are descriptive statistics usually reported together. In a certain sense, the standard deviation is a "natural" measure of statistical dispersion if the center of the data is measured about the mean. This is because the standard deviation from the mean is smaller than from any other point.
Specifically, it is the standard deviation of a number of experimental color matches to the central color. Assuming a bivariate normal distribution of these match points, a MacAdam ellipse thus contains about 39% of the color match points. A 2X MacAdam ellipse will contain about 86% of the match points, and a 3X MacAdam ellipse will contain ...
Bias in standard deviation for autocorrelated data. The figure shows the ratio of the estimated standard deviation to its known value (which can be calculated analytically for this digital filter), for several settings of α as a function of sample size n. Changing α alters the variance reduction ratio of the filter, which is known to be
Since the square root introduces bias, the terminology "uncorrected" and "corrected" is preferred for the standard deviation estimators: s n is the uncorrected sample standard deviation (i.e., without Bessel's correction) s is the corrected sample standard deviation (i.e., with Bessel's correction), which is less biased, but still biased
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A land use regression model (LUR model) is an algorithm often used for analyzing pollution, particularly in densely populated areas.. The model is based on predictable pollution patterns to estimate concentrations in a particular area.
A use variance is a variance that authorizes a land use not normally permitted by the zoning ordinance. [2] Such a variance has much in common with a special-use permit (sometimes known as a conditional use permit). Some municipalities do not offer this process, opting to handle such situations under special use permits instead.
The decision boundaries are formed by calculating the mean distance between class pixels and using the standard deviation of the generated training datasets to generate a parallelepiped box. Mahalanobis distance [5] – A system of classification that uses the Euclidean distance algorithm to assign land cover classes from a set of training ...