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Special Note to ACS Data Users - 2005

Here is how we determine which sub-state geographic areas meet the ACS population threshold of 65,000 for publishing estimates for that area: Wherever possible, we use the most current estimate of the total resident population from official Census Bureau Population Estimates Program (PEP). This number includes both household and group quarters population. PEP provides this estimate for counties, incorporated places, and sub-county areas (e.g. townships), which have a functioning government. If the PEP estimate for any of these areas is 65,000 or more, then we publish ACS data products for that area. However, since the ACS sample is still a sample of the housing unit population, the ACS estimates will often be lower than the PEP estimates. In some cases, the ACS estimate of total (housing unit) population will be less than 65,000. This is an indication that the total resident population for that geographic area is over 65,000 (although probably very close to 65,000). There are 52 geographic areas where this occurs, and they are shown in the table below.

GEOID Area Name
05000US06033 Lake County, California
05000US17001 Adams County, Illinois
05000US20103 Leavenworth County, Kansas
05000US21047 Christian County, Kentucky
05000US22087 St. Bernard Parish, Louisiana
05000US26073 Isabella County, Michigan
05000US36113 Warren County, New York
05000US38035 Grand Forks County, North Dakota
05000US39101 Marion County, Ohio
05000US40119 Payne County, Oklahoma
05000US47141 Putnam County, Tennessee
05000US48021 Bastrop County, Texas
05000US48099 Coryell County, Texas
05000US51019 Bedford County, Virginia
05000US51680 Lynchburg city, Virginia
05000US55097 Portage County, Wisconsin
05000US72005 Aguadilla Municipio, Puerto Rico
06000US1703124595 Evanston township, Cook County, Illinois
06000US1709703220 Avon township, Lake County, Illinois
06000US1711306639 Bloomington City township, McLean County, Illinois
06000US1803511296 Center township, Delaware County, Indiana
06000US1814158734 Penn township, St. Joseph County, Indiana
06000US1816340212 Knight township, Vanderburgh County, Indiana
06000US2501724925 Framingham town, Middlesex County, Massachusetts
06000US2607742160 Kalamazoo city, Kalamazoo County, Michigan
06000US2612565440 Pontiac city, Oakland County, Michigan
06000US3401319390 East Orange city, Essex County, New Jersey
06000US3401774630 Union City city, Hudson County, New Jersey
06000US3402545990 Middletown township, Monmouth County, New Jersey
06000US5513384250 Waukesha city, Waukesha County, Wisconsin
16000US0404720 Avondale city, Arizona
16000US0523290 Fayetteville city, Arkansas
16000US0624638 Folsom city, California
16000US0660018 Redondo Beach city, California
16000US1077580 Wilmington city, Delaware
16000US1207875 Boynton Beach city, Florida
16000US1706613 Bloomington city, Illinois
16000US1724582 Evanston city, Illinois
16000US1805860 Bloomington city, Indiana
16000US1851876 Muncie city, Indiana
16000US2642160 Kalamazoo city, Michigan
16000US2665440 Pontiac city, Michigan
16000US2756896 St. Cloud city, Minnesota
16000US3419390 East Orange city, New Jersey
16000US3474630 Union City city, New Jersey
16000US3563460 Rio Rancho city, New Mexico
16000US3728080 Greenville city, North Carolina
16000US4806128 Baytown city, Texas
16000US4810912 Bryan city, Texas
16000US4848804 Missouri City city, Texas
16000US5147672 Lynchburg city, Virginia
16000US5584250 Waukesha city, Wisconsin

Data Release Rules

Even with the population size thresholds described earlier, in certain geographic areas some very detailed tables might include estimates whose reliability is unacceptable. Data release rules, based on the statistical reliability of the survey estimates, will be used starting with the 2005 ACS data released in the summer of 2006. These release rules apply only to the single-year and three-year data products.

The main data release rule for the ACS tables works as follows. Every base table consists of a series of estimates. If more than half the estimates are not statistically different from 0 (at a 90 percent confidence level), then the table fails. Each estimate is subject to sampling variability that can be summarized by its standard error. Dividing the standard error by the estimate yields the coefficient of variation (CV) for each of the estimates. (If the estimate is 0, a CV of 100 percent is assigned.) To implement this requirement for each table at a given geographic area, CVs are calculated for each of the table's estimates, and the median CV value is determined. If 13-11 the median CV value for the table is less than or equal to 61 percent, the table passes for that geographic area; if it is greater than 61 percent, the table fails. Tables that are too sparse will fail this test. In that case, the table will not be published for that geographic area. Whenever a table fails, a simpler table that collapses some of the detailed lines together can be substituted for the original, more detailed table. The data release rules are then applied to the simpler table. If it passes, the simpler table is released. If it fails, none of the estimates for that particular table is released for this geographic area. These release rules are applied to single-year period estimates and multi-year period estimates based on three years of sample data. No data release rules are applied to the estimates based on five years of sample data.

For more information go to the Design and Methodology document.

Page Last Revised - October 8, 2021
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