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2. Weighted arithmetic mean - Wikipedia

   en.wikipedia.org/wiki/Weighted_arithmetic_mean

   The degrees of freedom of this weighted, unbiased sample variance vary accordingly from N − 1 down to 0. The standard deviation is simply the square root of the variance above. As a side note, other approaches have been described to compute the weighted sample variance. [7]

3. Weight function - Wikipedia

   en.wikipedia.org/wiki/Weight_function

   A weight function is a mathematical device used when performing a sum, integral, or average to give some elements more "weight" or influence on the result than other elements in the same set. The result of this application of a weight function is a weighted sum or weighted average .

4. Inverse probability weighting - Wikipedia

   en.wikipedia.org/wiki/Inverse_probability_weighting

   One very early weighted estimator is the Horvitz–Thompson estimator of the mean. [3] When the sampling probability is known, from which the sampling population is drawn from the target population, then the inverse of this probability is used to weight the observations. This approach has been generalized to many aspects of statistics under ...

5. Inverse distance weighting - Wikipedia

   en.wikipedia.org/wiki/Inverse_distance_weighting

   Inverse Distance Weighting as a sum of all weighting functions for each sample point. Each function has the value of one of the samples at its sample point and zero at every other sample point. Inverse distance weighting (IDW) is a type of deterministic method for multivariate interpolation with a known scattered set of points.

6. Weighing matrix - Wikipedia

   en.wikipedia.org/wiki/Weighing_matrix

   Weighing matrices are so called because of their use in optimally measuring the individual weights of multiple objects. [1] [2]In mathematics, a weighing matrix of order and weight is a matrix with entries from the set {,,} such that:

7. Sensitivity analysis - Wikipedia

   en.wikipedia.org/wiki/Sensitivity_analysis

   Figure 2. Sampling-based sensitivity analysis by scatterplots. Y (vertical axis) is a function of four factors. The points in the four scatterplots are always the same though sorted differently, i.e. by Z 1, Z 2, Z 3, Z 4 in turn. Note that the abscissa is different for each plot: (−5, +5) for Z 1, (−8, +8) for Z 2, (−10, +10) for Z 3 and ...