#math
- the alternative is called mean absolute deviation - $\frac {\sum (x- \bar x)}{n}$
- instead of  standard deviation  - $\sqrt \frac{\sum (x- \bar x)^2}{n-1}$
- reasons:
    - In an earlier era of computation it seemed easier to find the square root of one figure rather than take the absolute values for a series of figures. This is no longer so, because the calculations are done by computer.
    - In those rare situations in which we obtain full response from a random sample with no measurement error and wish to estimate, using the dispersion in our sample, the dispersion in a perfect Gaussian population, then the standard deviation has been shown to be a more stable indicator of its equivalent in the population than the mean deviation has. Note that we can only calculate this via simulation, since in real-life research we would not know the actual population figure
    - modern statistics is largely built on top of the standard deviation.
    - [http://www.leeds.ac.uk/educol/documents/00003759.htm](http://www.leeds.ac.uk/educol/documents/00003759.htm)
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