Understanding Margin of Error
The Census 2000 sample, with data collected using the “long form”, represented approximately 1in6 households and one point in time, April 1, 2000. ACS represents approximately 1in40 households on a rolling sample basis, but the smaller sample sizes can produce larger sampling errors.
With each ACS estimate, the Census Bureau reports a Margin of Error (MOE), or measure of the variability of the estimate due to sampling error. The MOE enables data users to measure the range of uncertainty around each estimate. The larger the MOE, the lower the accuracy of the estimate—and the less confidence one should have that the estimate is close to the true value.
Esri Improves Confidence in Using ACS
Decisions about the quality of an estimate based on the MOE are difficult to make. Esri has simplified this process by adding symbols to flag reliability of data based on sample size. Symbols are based on thresholds of reliability Esri established using an estimate’s Coefficient of Variation (CV).

High Reliability: Small CVs, less than or equal to 12 percent, are flagged green to indicate that the sampling error is small relative to the estimate and the estimate is reasonably reliable.

Medium Reliability: Estimates with CVs between 12 and 40 are flagged yellow—use with caution.

Low Reliability: Large CVs, over 40 percent, are flagged red to indicate that the sampling error is large relative to the estimate. The estimate is considered very unreliable.
The CV is a measure of relative error in the estimate, calculated as the ratio of the standard error to the estimate itself.
Read an indepth explanation of Margin of Error from Esri's Data Team.