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In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.
About 68% of values drawn from a normal distribution are within one standard deviation σ from the mean; about 95% of the values lie within two standard deviations; and about 99.7% are within three standard deviations. [6] This fact is known as the 68–95–99.7 (empirical) rule, or the 3-sigma rule.
The 95% confidence interval for the true project work time is approximately E(project) ± 2 × SD(project) The 99.7% confidence interval for the true project work time is approximately E(project) ± 3 × SD(project) Information Systems typically uses the 95% confidence interval for all project and task estimates. [2]
If the standard deviation were zero, then all men would share an identical height of 69 inches. Three standard deviations account for 99.73% of the sample population being studied, assuming the distribution is normal or bell-shaped (see the 68–95–99.7 rule, or the empirical rule, for more information).
as for "three sigma rule", idk, this sounds as if it was a rule dealing with a 3-sigma case, while "68-95-99.7" is actually a list of cases of n sigma, with a modest n=1..3. The page title actually helped me remember "68-95-99.7" by now, but as 4 or 5 sigma also occur in everyday considerations, I keep having to look it up anyway.
The relation between and are given by the following table, where the values for DRMS and 2DRMS (twice the distance root mean square) are specific to the Rayleigh distribution and are found numerically, while the CEP, R95 (95% radius) and R99.7 (99.7% radius) values are defined based on the 68–95–99.7 rule
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Precise values of are given by the quantile function of the normal distribution (which the 68–95–99.7 rule approximates). Note that is undefined for | ...