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The relative change is independent of the unit of measurement employed; for example, the relative change from 2 to 1 m is −50%, the same as for 200 to 100 cm.The relative change is not defined if the reference value (v ref) is zero, and gives negative values for positive increases if v ref is negative, hence it is not usually defined for negative reference values either.
Relative volatility is a measure comparing the vapor pressures of the components in a liquid mixture of chemicals. This quantity is widely used in designing large industrial distillation processes. [1] [2] [3] In effect, it indicates the ease or difficulty of using distillation to separate the more volatile components from the less volatile ...
In probability theory and statistics, the coefficient of variation ( CV ), also known as normalized root-mean-square deviation (NRMSD), percent RMS, and relative standard deviation ( RSD ), is a standardized measure of dispersion of a probability distribution or frequency distribution. It is defined as the ratio of the standard deviation to the ...
It is also possible to identify the types of difference by looking at an (,) plot. Quantity difference exists when the average of the X values does not equal the average of the Y values. Allocation difference exists if and only if points reside on both sides of the identity line. Related measures
The relative change formula is not well-behaved under many conditions and various alternative formulas, called indicators of relative difference or change, have been proposed in the literature. Several authors have found log change and log points to be satisfactory indicators, but these have not seen widespread use.
(200% for the first formula and 100% for the second formula). Provided the data are strictly positive, a better measure of relative accuracy can be obtained based on the log of the accuracy ratio: log( F t / A t ) This measure is easier to analyse statistically, and has valuable symmetry and unbiasedness properties.
It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). Effectively, this overcomes the 'infinite error' issue. Its formula is:
In this example, only the values in the A column are entered (10, 20, 30), and the remainder of cells are formulas. Formulas in the B column multiply values from the A column using relative references, and the formula in B4 uses the SUM() function to find the sum of values in the B1:B3 range.