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The standard deviation is directly related to precision of a procedure where low standard deviations are indicative of a high level of precision. There is not a necessary relation between standard deviation and accuracy except that a high level of accuracy requires low standard deviations.
The standard deviation measures the precision of one typical measurement. It's a common experience that the mean of a variety of measurements gives a more precise estimation than one measurement. This experience is quantified by the quality error of the mean. A high variance shows that the information is widely spread (less reliable) and an occasional variance shows that the information is clustered closely round the mean (more reliable).
A standard deviation (or σ) could be a measure of how dispersed the info is in respect to the mean. Low variance means data are clustered round the mean, and high variance indicates data are more unfolded. and also the error rate is that the percentage value of the difference between the observed and therefore the actual value, divided by the particular value.
An experiment that yields data with an occasional variance is claimed to possess high precision. If a high proportion of knowledge points lie removed from the average, then the quality deviation is large. An experiment that yields data with a high variance is claimed to possess low precision. If you are not accurate, they're more displayed (large standard deviation).
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