In the national and state benchmarks for wage trends (all occupations), what is the statistical significance of the mean wage relative standard error (RSE)?
As described by the U.S. Bureau of Labor Statistics (BLS), “The relative standard error (RSE) is the standard error expressed as a percent of the estimate. It can be used to calculate a ‘confidence interval’ around a sample estimate.” As BLS explained further: “Sampling errors occur because observations come only from a sample and not from an entire population. The sample used for this survey is one of a number of possible samples of the same size that could have been selected using the sample design. Estimates derived from the different samples would differ from one another. A measure of the variation among these differing estimates is called the standard error or sampling error. It indicates the precision with which an estimate from a particular sample approximates the average result of all possible samples. The relative standard error (RSE) is the standard error divided by the estimate. . . The standard error can be used to calculate a confidence interval around a sample estimate. A
