Search results
Results from the WOW.Com Content Network
All-commodity volume (ACV) is a weighted measure of product availability, or distribution, based on total store sales. In other words, ACV is the percentage of sales in all categories that are generated by the stores that stock a given brand (again, at least one SKU of that brand) (note: ACV can be expressed as a percentage or as a dollar value (total sales of stores carrying brand).
The result of this application of a weight function is a weighted sum or weighted average. Weight functions occur frequently in statistics and analysis, and are closely related to the concept of a measure. Weight functions can be employed in both discrete and continuous settings.
The notion of weighted mean plays a role in descriptive statistics and also occurs in a more general form in several other areas of mathematics. If all the weights are equal, then the weighted mean is the same as the arithmetic mean.
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.
Weight distribution is the apportioning of weight within a vehicle, especially cars, airplanes, and trains. Typically, it is written in the form x / y , where x is the percentage of weight in the front, and y is the percentage in the back.
The lower weighted median is 2 with partition sums of 0.49 and 0.5, and the upper weighted median is 3 with partition sums of 0.5 and 0.25. In the case of working with integers or non-interval measures , the lower weighted median would be accepted since it is the lower weight of the pair and therefore keeps the partitions most equal.
The action (the integration ) of this distribution on a test function can be interpreted as a weighted average of the distribution on the support of the test function, even if the values of the distribution at a single point are not well-defined.
For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().