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### Calculating the Standard Deviation with the STDEVP() and STDEV() Functions

As I mentioned in the previous section, in real-world scenarios, the variance is really used only as an intermediate step for calculating the most important of the measures of variation, the standard deviation. This measure tells you how much the values in the data set vary with respect to the average (the arithmetic mean). What exactly this means won't become clear until you learn about frequency distributions in the next section. For now, however, it's enough to know that a low standard deviation means that the data values are clustered near the mean, and a high standard deviation means the values are spread out from the mean.

The standard deviation is defined as the square root of the variance. This is good because it means that the resulting units will be the same as those used by the data. For example, the variance of the product defects is expressed in the meaningless “defects squared” units, but the standard deviation is expressed in defects.

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