Alabama zip codes by population.A Comparison of ZIP Code Population Estimates

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The census conducted every 10 years by the Census Bureau is the only population estimate that makes an attempt to count every member of the population by sending a survey to every household in the country. Completion is required. Over a 5 year period, the U.

That leaves an extremely small amount of room for error. Another way to approximate the population is to use sampling. The answers such as the number of people in the household help to estimate the population as a whole.

To get those huge savings, only a small percentage of the population is surveyed which leaves us with a range the population likely falls within instead of a precise number. The margin of error that determines the size of the range is larger than the expected population growth. Another way to approximate the population is to use an estimator. As confirmed by the Internal Revenue Service IRS , the number of tax returns filed for a ZIP code can be used to approximate the number of households and the number of exemptions can be used to approximate the population.

However, as an estimator, it isn’t perfect. As discussed below, it is affected by economic changes as well as tax policy changes. It also has strict privacy limits on data release such that it underestimates the population by more than the expected population growth. The Census was done precisely to estimate population sizes and so provides estimates for the most ZIP codes. In fact, over of the missing ZIPs are estimated to have a population of less than people. For only legitimate five-digit areas are defined so there is no longer full nation-wide coverage.

The ZCTAs will better represent the actual Zip Code service areas because the Census Bureau initiated a process before creation of blocks to add block boundaries that split polygons with large numbers of addresses using different ZIP Codes.

The first issue with the accuracy of the IRS estimates is that their are using exemptions as an estimator for populations as opposed to directly trying to calculate population size.

Because it is only an estimator, it is still subject to variation due to other variables. For instance, economic changes or changes in tax policy are likely to affect the population estimates. It is highly unlikely that the population shrank by nearly 2 million people in It is much more likely that the economic or taxation changes affected the estimates by changing how the population files their tax returns.

Our research backs up the suggestions put forth by the IRS. Using the number of exemptions as a population estimate results in a root mean square error RMSE of while the alternative formula results in an RMSE of lower is better. Both of which are documented by the IRS. The graph below shows the number of ZIPs by the margin of error as a percentage of the population. Surveying a large portion of the population is expensive especially with the large number of questions besides population included in the ACS.

The Census Bureau publishes population estimates based on ACS surveys using data from the past 1 year, 3 years, or 5 years of data. Including data from more years increases the sample size to improve the precision of the estimate at the cost of using less recent data. We include the estimates based on the past 5 years worth of surveys because they are based on the largest sample to provide the most precise estimates.

To further illustrate this point, the Census population is within the most recent ACS margin of error for the majority of ZIP codes even after a decade. We have included the margin of error with the ACS estimates so that those looking to create their own estimate can make their own judgement calls as to their formula for estimating the population for a given ZIP.

For those diving deeper into population estimates, we have examined whether the IRS and ACS estimates show the same relative change in population over various periods of time. In other words, we asked this question: if the IRS estimates that the population of a ZIP increased over a certain period of time, does the ACS data also indicate a population increase?

We have found that there is a correlation between the two data sets. However, that correlation only becomes apparent on estimates for ZIPs that have a very low margin of error.

Toggle navigation. Looking for our list of all us ZIP codes? We offer a complete downloadable list in Excel and CSV format. Our Recommendation: Unless you have a very specific need for comparing data to a single year, the Census data likely provides a more accurate estimate of current population levels than the more recent but less accurate estimates from the IRS and less precise estimates of the ACS.

Actual population counts from the census are not expected to be released from the Census Bureau until May at the earliest. Other estimates for ZIPs with a very low population should be viewed with skepticism because the IRS data implements other privacy protection measures. Census Bureau. The full U. The IRS documents only around million exemptions compared to a population of million estimated by the Census.

While million exemptions are reported when examining state level data that is not subject to privacy protection, only million are reported after privacy protection eliminates some data.

– Zip Codes in Alabama

 
#1. (Montgomery, AL) Previously 52, ; #2. (Birmingham, AL) Previously 51, ; #3. (Mobile, AL) Previously 49, ; #4. (Birmingham, AL). ZIP Codes in Alabama ; · Moody, Acmar ; · Adamsville ; · Adger ; · Alabaster ; · Alexander City, Alex City. Most Populated Zip Codes in Alabama State ; · Mobile AL, 30, ; · Florence AL, 30, ; · Huntsville AL, 29, ; · Birmingham AL, 29,

Alabama zip codes by population

Tuscaloosa AL. Enterprise AL. Decatur AL. Florence AL. Huntsville AL. Fairhope AL. Prattville AL. Trussville AL. Bessemer AL. Alabaster AL. Hartselle AL. Talladega AL. Theodore AL. Harvest AL. Alexander City AL. Phenix City AL. Opelika AL.

Gulf Shores AL. Albertville AL. Orange Beach AL. Anniston AL. Wetumpka AL. Cullman AL. Gadsden AL. Tuscumbia AL. Jacksonville AL. Sylacauga AL. Muscle Shoals AL. Bay Minette AL. Guntersville AL. Fort Payne AL. Eufaula AL. Gardendale AL. Northport AL. Brewton AL.

Saraland AL. Owens Cross Roads AL. Oneonta AL. Mc Calla AL. Millbrook AL. Clanton AL. Tallassee AL. Warrior AL. Grand Bay AL. Moulton AL. Hazel Green AL. Greenville AL. Odenville AL. Piedmont AL. Montevallo AL. Deatsville AL. Spanish Fort AL. Attalla AL. Haleyville AL. Eight Mile AL. Hanceville AL. Robertsdale AL. Scottsboro AL. New Market AL. Cottondale AL. Smiths Station AL. Russellville AL.

Irvington AL. Andalusia AL. Rainbow City AL. Roanoke AL. Fairfield AL. Pell City AL. Dadeville AL. Hamilton AL. Fayette AL. Monroeville AL. Sheffield AL. Chelsea AL. Springville AL. Vinemont AL. Jackson AL. Elkmont AL. Pleasant Grove AL. Daleville AL. Tuskegee AL. Jemison AL. Rogersville AL. Adamsville AL. Trinity AL. Headland AL. Demopolis AL.

Evergreen AL. Somerville AL. Thomasville AL. Childersburg AL. Altoona AL. Lincoln AL. Columbiana AL. Fultondale AL.

Pike Road AL. Blountsville AL. Slocomb AL. Elberta AL. Citronelle AL. Meridianville AL. Winfield AL. Crossville AL. Falkville AL. Union Springs AL. Rainsville AL. Maylene AL. Abbeville AL. Greensboro AL. Ashville AL. Midland City AL. Town Creek AL. Mount Olive AL. Satsuma AL. Ohatchee AL. Eclectic AL. Moundville AL.

Lineville AL. Centreville AL. Ashford AL. Laceys Spring AL. Hartford AL. Sterrett AL. Lafayette AL. Luverne AL. Cordova AL.

Ardmore AL. West Blocton AL. Danville AL. Henagar AL. Fort Mitchell AL. Phil Campbell AL. Fort Rucker AL. Union Grove AL. Munford AL. Wedowee AL. Lillian AL. New Hope AL. Aliceville AL. Brundidge AL. Summerdale AL. Collinsville AL. Chunchula AL. Cedar Bluff AL. Wilsonville AL. Woodland AL. Goodwater AL. Ashland AL. Alexandria AL. Cherokee AL. Stevenson AL. Duncanville AL. Leighton AL. Double Springs AL. Brookwood AL. Ragland AL. Grove Hill AL. Sulligent AL. Section AL. Cropwell AL. Verbena AL.

Lexington AL. Eastaboga AL. Flat Rock AL. Jacksons Gap AL. Hope Hull AL. Woodville AL. Crane Hill AL. Georgiana AL. Quinton AL. Frisco City AL. Red Bay AL. Cleveland AL. Silverhill AL. Completion is required. Over a 5 year period, the U. That leaves an extremely small amount of room for error. Another way to approximate the population is to use sampling.

The answers such as the number of people in the household help to estimate the population as a whole. To get those huge savings, only a small percentage of the population is surveyed which leaves us with a range the population likely falls within instead of a precise number. The margin of error that determines the size of the range is larger than the expected population growth. Another way to approximate the population is to use an estimator.

As confirmed by the Internal Revenue Service IRS , the number of tax returns filed for a ZIP code can be used to approximate the number of households and the number of exemptions can be used to approximate the population. However, as an estimator, it isn’t perfect. As discussed below, it is affected by economic changes as well as tax policy changes.

It also has strict privacy limits on data release such that it underestimates the population by more than the expected population growth. The Census was done precisely to estimate population sizes and so provides estimates for the most ZIP codes.

In fact, over of the missing ZIPs are estimated to have a population of less than people. For only legitimate five-digit areas are defined so there is no longer full nation-wide coverage. The ZCTAs will better represent the actual Zip Code service areas because the Census Bureau initiated a process before creation of blocks to add block boundaries that split polygons with large numbers of addresses using different ZIP Codes.

The first issue with the accuracy of the IRS estimates is that their are using exemptions as an estimator for populations as opposed to directly trying to calculate population size. Because it is only an estimator, it is still subject to variation due to other variables. For instance, economic changes or changes in tax policy are likely to affect the population estimates. It is highly unlikely that the population shrank by nearly 2 million people in It is much more likely that the economic or taxation changes affected the estimates by changing how the population files their tax returns.

Our research backs up the suggestions put forth by the IRS. Using the number of exemptions as a population estimate results in a root mean square error RMSE of while the alternative formula results in an RMSE of lower is better.