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Why is the mean absolute deviation calculated using absolute value?
Because otherwise it would not be the mean absolutedeviation!
What is an absolute deviation?
An absolute deviation is the difference between a given value and a variate value in statistics, or, in target shooting, the shortest distance between the centre of the target and the point where the projectile hit.
How standard deviation and Mean deviation differ from each other?
There is 1) standard deviation, 2) mean deviation and 3) mean absolute deviation. The standard deviation is calculated most of the time. If our objective is to estimate the variance of the overall population from a representative random sample, then it has been shown theoretically that the standard deviation is the best estimate (most efficient). The mean deviation is calculated by first calculating the mean of the data and then calculating the deviation (value - mean) for each value. If we then sum these deviations, we calculate the mean deviation which will always be zero. So this statistic has little value. The individual deviations may however be of interest. See related link. To obtain the means absolute deviation (MAD), we sum the absolute value of the individual deviations. We will obtain a value that is similar to the standard deviation, a measure of dispersal of the data values. The MAD may be transformed to a standard deviation, if the distribution is known. The MAD has been shown to be less efficient in estimating the standard deviation, but a more robust estimator (not as influenced by erroneous data) as the standard deviation. See related link. Most of the time we use the standard deviation to provide the best estimate of the variance of the population.
Is relative standard deviation an absolute value?
No, as its name suggests, it is a relative measure.
Formula of mean absolute deviation?
Mean absolute deviation = sum[|x-mean(x)|]/n Where mean(x) = sum(x)/n and n is the number of observations. |y| denotes the absolute value of y.
