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Weighting. The process of frequency weighting involves emphasizing the contribution of particular aspects of a phenomenon (or of a set of data) over others to an outcome or result; thereby highlighting those aspects in comparison to others in the analysis. That is, rather than each variable in the data set contributing equally to the final ...
The weighted arithmetic mean is similar to an ordinary arithmetic mean (the most common type of average), except that instead of each of the data points contributing equally to the final average, some data points contribute more than others. The notion of weighted mean plays a role in descriptive statistics and also occurs in a more general ...
Weighted statistics. In statistics, there are many applications of "weighting": Weighted mean. Weighted harmonic mean. Weighted geometric mean. Weighted least squares. Category:
Inverse probability weighting. Inverse probability weighting is a statistical technique for estimating quantities related to a population other than the one from which the data was collected. Study designs with a disparate sampling population and population of target inference (target population) are common in application. [1]
A weighting curve is a graph of a set of factors, that are used to 'weight' measured values of a variable according to their importance in relation to some outcome. An important example is frequency weighting in sound level measurement where a specific set of weighting curves known as A-, B-, C-, and D-weighting as defined in IEC 61672 [1] are used.
Spatial weight matrix. The concept of a spatial weight is used in spatial analysis to describe neighbor relations between regions on a map. [1] If location is a neighbor of location then otherwise . Usually (though not always) we do not consider a site to be a neighbor of itself [2] so . These coefficients are encoded in the spatial weight matrix.
Exponential smoothing. Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time.
v. t. e. Weighted least squares (WLS), also known as weighted linear regression, [1][2] is a generalization of ordinary least squares and linear regression in which knowledge of the unequal variance of observations (heteroscedasticity) is incorporated into the regression. WLS is also a specialization of generalized least squares, when all the ...