Margin of error and benchmark data

The usefulness of benchmark data depends on the number of survey respondents, in part, as minor score differentials (such as the variation between a 4.1 and a 4.2 on a five-point scale) may only be significant with larger sample sizes (See my posts of Dec. 9, 2005 on margin of error generally; and Aug. 29, 2006 on subgroup analyses.). My faithful and intellectually-insatiable readership demands a more precise explanation of margin of error.
n = 2 * z2
D2
This formula calculates a survey’s margin of error, where:

n = sample size
2 = variance
z = z value from a normal table reflecting the degree of confidence, squared
D = level of precision, squared

Nothing more is left to say (except the “2’s” above are supersripts — squares).

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