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
Adair
16,851
Alfalfa
27,871
Atoka
20,733
Beaver
24,610
Beckham
24,049
Blaine
25,708
Bryan
23,453
Caddo
22,062
Canadian
30,545
Carter
25,110
Cherokee
20,575
Choctaw
21,329
Cimarron
27,929
Cleveland
30,507
Coal
24,399
Comanche
26,149
Cotton
22,596
Craig
20,704
Creek
25,150
Custer
25,569
Delaware
22,976
Dewey
27,432
Ellis
27,120
Garfield
26,454
Garvin
23,020
Grady
28,577
Grant
29,060
Greer
18,292
Harmon
22,588
Harper
24,714
Haskell
21,280
Hughes
20,438
Jackson
23,226
Jefferson
19,155
Johnston
20,930
Kay
24,853
Kingfisher
32,049
Kiowa
20,888
Latimer
23,842
Le Flore
20,656
Lincoln
24,454
Logan
29,387
Love
21,704
Major
28,801
Marshall
23,872
Mayes
23,861
McClain
29,797
McCurtain
19,692
McIntosh
22,922
Murray
26,837
Muskogee
22,775
Noble
27,828
Nowata
22,147
Okfuskee
17,281
Oklahoma
30,398
Okmulgee
22,400
Osage
24,363
Ottawa
20,209
Pawnee
23,916
Payne
23,589
Pittsburg
24,750
Pontotoc
24,683
Pottawatomie
23,155
Pushmataha
23,346
Roger Mills
26,431
Rogers
30,886
Seminole
20,460
Sequoyah
20,020
Stephens
25,374
Texas
22,120
Tillman
21,673
Tulsa
30,894
Wagoner
28,286
Washington
30,267
Washita
26,744
Woods
27,232
Woodward
28,248
Value for Oklahoma (US Dollars): $27,432
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.