Relative Standard Error
The relative standard error (RSE) is simply the standard error divided by the mean and expressed as a percentage. For example, consider two surveys of household income that both result in a sample mean of $50,000. If one survey has a standard error of $10,000 and the other has a standard error of $5,000, then the relative standard errors are 20% and 10% respectively. The survey with the lower relative standard error has a more precise measurement since there is less variance around the mean. In fact, data organizations often set reliability standards that their data must reach before publication. For example, the U.S. National Center for Health Statistics typically does not report an estimate if the relative standard error exceeds 30%. (NCHS also typically requires at least 30 observations - if not more - for an estimate to be reported.)
Read more about this topic: Standard Error
Famous quotes containing the words relative, standard and/or error:
“She went in there to muse on being rid
Of relative beneath the coffin lid.
No one was by. She stuck her tongue out; slid.”
—Gwendolyn Brooks (b. 1917)
“We don’t want bores in the theatre. We don’t want standardised acting, standard actors with standard-shaped legs. Acting needs everybody, cripples, dwarfs and people with noses so long. Give us something that is different.”
—Dame Sybil Thorndike (1882–1976)
“No consensus of men can make an error erroneous. We can only find or commit an error, not create it. When we commit an error, we say what was an error already.”
—Josiah Royce (1855–1916)