<P> In statistics, the standard deviation (SD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values . A low standard deviation indicates that the data points tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values . </P> <P> The standard deviation of a random variable, statistical population, data set, or probability distribution is the square root of its variance . It is algebraically simpler, though in practice less robust, than the average absolute deviation . A useful property of the standard deviation is that, unlike the variance, it is expressed in the same units as the data . There are also other measures of deviation from the norm, including average absolute deviation, which provide different mathematical properties from standard deviation . </P> <P> In addition to expressing the variability of a population, the standard deviation is commonly used to measure confidence in statistical conclusions . For example, the margin of error in polling data is determined by calculating the expected standard deviation in the results if the same poll were to be conducted multiple times . This derivation of a standard deviation is often called the "standard error" of the estimate or "standard error of the mean" when referring to a mean . It is computed as the standard deviation of all the means that would be computed from that population if an infinite number of samples were drawn and a mean for each sample were computed . </P>

How do you find the standard deviation of a mean
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