The standard deviation for a set of data is a measure of how much the individual observations are spread about their mean. A small value indicates that they are all tightly packed around the mean value whereas a large value indicates that the observations are not so close together.
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The standard deviation.z-score of a value=(that value minus the mean)/(standard deviation)
Let sigma = standard deviation. Standard error (of the sample mean) = sigma / square root of (n), where n is the sample size. Since you are dividing the standard deviation by a positive number greater than 1, the standard error is always smaller than the standard deviation.
The relative standard deviation is the absolute value of the ration of the sample mean to the sample standard deviation. This value appears to be quite small; however, without comparative data it is difficult to know what to make of it. In some contexts it might even be considered large.
The standard deviation is the standard deviation! Its calculation requires no assumption.
z-score of a value=(that value minus the mean)/(standard deviation)