About this application: This application provides summary profiles showing frequently requested data items from various US Census Bureau programs. Profiles are available for the nation, states, and counties.
Per capita income in past 12 months (in 2018 dollars), 2014-2018 - (US Dollars)
County
Value
Autauga
29,372
Baldwin
31,203
Barbour
18,461
Bibb
20,199
Blount
22,656
Bullock
20,346
Butler
20,430
Calhoun
24,706
Chambers
22,827
Cherokee
23,356
Chilton
24,611
Choctaw
22,182
Clarke
21,111
Clay
23,147
Cleburne
21,989
Coffee
27,577
Colbert
24,918
Conecuh
17,542
Coosa
22,963
Covington
23,071
Crenshaw
23,353
Cullman
22,980
Dale
23,837
Dallas
18,910
DeKalb
21,004
Elmore
27,475
Escambia
18,161
Etowah
24,065
Fayette
21,862
Franklin
19,776
Geneva
20,471
Greene
14,209
Hale
20,272
Henry
24,069
Houston
25,990
Jackson
21,608
Jefferson
30,657
Lamar
21,666
Lauderdale
27,189
Lawrence
23,557
Lee
26,960
Limestone
27,699
Lowndes
19,491
Macon
20,125
Madison
35,526
Marengo
23,056
Marion
21,391
Marshall
23,833
Mobile
25,215
Monroe
18,890
Montgomery
28,008
Morgan
25,907
Perry
13,678
Pickens
22,417
Pike
21,137
Randolph
23,247
Russell
22,055
Shelby
36,576
St. Clair
24,861
Sumter
15,882
Talladega
22,498
Tallapoosa
23,655
Tuscaloosa
26,064
Walker
22,772
Washington
22,776
Wilcox
16,584
Winston
21,799
Value for Alabama (US Dollars): $26,846
Sources: U.S. Census Bureau, American Community Survey (ACS) and Puerto Rico Community Survey (PRCS), 5-Year Estimates. The PRCS is part of the Census Bureau's ACS, customized for Puerto Rico. Both Surveys are updated every year.
Definition
Per capita income is the mean income computed for every man, woman, and child in a particular group including those living in group quarters. It is derived by dividing the aggregate income of a particular group by the total population in that group. This measure is rounded to the nearest whole dollar. For the complete definition, go to ACS subject definitions "Income in the Past 12 Months, Per Capita Income."
Source and Accuracy
This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12 month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.
Statistics from all surveys are subject to sampling and nonsampling error. Sampling error is the uncertainty between an estimate based on a sample and the corresponding value that would be obtained if the estimate were based on the entire population (as from a census). Measures of sampling error are provided in the form of margins of error for all estimates included with ACS and PRCS published products. The Census Bureau recommends that data users incorporate this information into their analyses, as sampling error in survey estimates could impact the conclusions drawn from the results. The data for each geographic area are presented together with margins of error at Using margins of error. A more detailed explanation of margins of error and a demonstration of how to use them is provided below.
For more information on sampling and estimation methodology, confidentiality, and sampling and nonsampling errors, please see the Multiyear Accuracy (US) and the Multiyear Accuracy (Puerto Rico) documents at "Documentation - Accuracy of the data."
Margin of Error
As mentioned above, ACS estimates are based on a sample and are subject to sampling error. The margin of error measures the degree of uncertainty caused by sampling error. The margin of error is used with an ACS estimate to construct a confidence interval about the estimate. The interval is formed by adding the margin of error to the estimate (the upper bound) and subtracting the margin of error from the estimate (the lower bound). It is expected with 90 percent confidence that the interval will contain the full population value of the estimate. The following example is for demonstrating purposes only. Suppose the ACS reported that the percentage of people in a state who were 25 years and older with a bachelor's degree was 21.3 percent and that the margin of error associated with this estimate was 0.7 percent. By adding and subtracting the margin of error from the estimate, we calculate the 90-percent confidence interval for this estimate:
Therefore, we can be 90 percent confident that the percent of the population 25 years and older having a bachelor's degree in a state falls somewhere between 20.6 percent and 22.0 percent.