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The mean is the sum of each sample divided by the number of samples.

The median is the middle sample in a ranked list of samples, or the mean of the middle two samples if the number of samples is even.

The standard deviation is the square root of the sum of the squares of the difference between the mean and each of the samples, such sum then divided by either N or by N-1, before the square root is taken. N is used for population standard deviation, where the mean is known independently of the calculation of the standard deviation. N-1 is used for sample standard deviation, where the mean is calculated along with the standard deviation, and the "-1" compensates for the loss of a "degree of freedom" that such a procedure entails.

Not asked, but answered for completeness sake, the mode is the most probable value, and does not necessarily represent the mean such as in an asymmetrically skewed distribution, such as a Poisson distribution.

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Q: How do you calculate mean median and standard deviation?
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In the same way that you calculate mean and median that are greater than the standard deviation!


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The mean deviation from the median is equal to the mean minus the median.


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The median is least affected by an extreme outlier. Mean and standard deviation ARE affected by extreme outliers.


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