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What is difference between absolute measure of dispersion and relative measures of dispersion?
The Absolute Measure of dispersion is basically the measure of variation from the mean such as standard deviation. On the other hand the relative measure of dispersion is basically the position of a certain variable with reference to or as compared with the other variables. Such as the percentiles or the z-score.
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What is the difference between absolute dispersion and relative dispersion in statistics?
Absolute dispersion usually refers to the standard deviation, a measure of variation from the mean, the units of st. dev. are the same as for the data. Relative dispersion, sometimes called the coefficient of variation, is the result of dividing the st. dev. by the mean, hence it is dimensionless (it may also be presented as a percentage). So a low value of relative dispersion usually implies that the st. dev. is small in comparison to the magnitude of the mean, as in a st. dev. of 6cm for a mean of 4m would give a figure of 0.015 (1.5%) whereas with a mean of 40cm it would be 0.15 or 15%. However with measurements either side of zero and a mean close to zero the relative dispersion could be greater than 1. As is usual, interpret with caution.
What is the difference of absolute value and relative value?
Absolute value uses a companies cash flow to determine it's worth. Relative value compares a companies worth to other competitors.
What are absolute relative and polar coordinates?
absolute relative and polar coordinates definition
What is absolute error formula?
Absolute and Relative Error Absolute and relative error are two types of error with which every experimental scientist should be familiar. The differences are important. Absolute Error: Absolute error is the amount of physical error in a measurement, period. Let's say a meter stick is used to measure a given distance. The error is rather hastily made, but it is good to ±1mm. This is the absolute error of the measurement. That is, absolute error = ±1mm (0.001m). In terms common to Error Propagation absolute error = Δx where x is any variable. Relative Error: Relative error gives an indication of how good a measurement is relative to the size of the thing being measured. Let's say that two students measure two objects with a meter stick. One student measures the height of a room and gets a value of 3.215 meters ±1mm (0.001m). Another student measures the height of a small cylinder and measures 0.075 meters ±1mm (0.001m). Clearly, the overall accuracy of the ceiling height is much better than that of the 7.5 cm cylinder. The comparative accuracy of these measurements can be determined by looking at their relative errors. relative error = absolute error value of thing measured or in terms common to Error Propagation relative error = Δx x where x is any variable. Now, in our example, relative errorceiling height = 0.001m 3.125m •100 = 0.0003% relativeerrorcylinder height = 0.001m 0.075m •100 = 0.01% Clearly, the relative error in the ceiling height is considerably smaller than the relative error in the cylinder height even though the amount of absolute error is the same in each case.
Is that the value for absolute pressure will always be greater than for gauge pressure?
No. We need to know exactly what is meant by gage here. A piston tyre gauge measures pressures relative to atmospheric. A mercury barometer measures absolute pressure. A gauge that involves uncoiling of a coiled tube will measure absolute pressure (it will have to be calibrated). But a manometer which is open to the atmosphere on one arm will measure pressures relative to atmospheric pressure so the real pressure is the two added together.
