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Standard Deviation:

One of the measures of spread is Standard deviation. If in a normal distribution, the mean and standard deviation are known, it is easy to calculate percentile rank of any given score. The standard deviation is a statistic that tells you how tightly all the values in dataset are clustered around the mean. We can remember like the square root of the variance is standard deviation or mean of the mean.

standard deviation formula(i2tutorials.com)

For each value x, subtract the mean from x,

Multiply that result by itself.

Sum up all those squared values.

Then divide that result by n(population) or (n-1)(sample).

When the values are pretty tightly bunched together and the bell-shaped curve is steep, the standard deviation is small.

When the values are spread apart and the bell curve is relatively flat, that tells you have a relatively large standard deviation.

standard deviation-bell-shaped curve is steep(i2tutorials.com)

One standard deviation away from the mean in either direction on the horizontal axis (-1SD to +1SD) accounts to about 68% of the people in the group. Two standard deviations away from the mean(-2SD to +2SD) can account to roughly 95% of the people. Three standard deviations (all the shaded areas) accounts to 99.7% of the people.

In highly-skewed distributions, standard deviation is not considered as a good measure of spread. In such cases, along with Standard deviation, semi-inter quartile range must be taken into consideration.
In Microsoft Excel, STDEV(A1:Z99) for sample and STDEVP(A1:Z99) if you want to use the “biased” or “n” method for population.

standard deviation (i2tutorials.com)