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
Adams
33,652
Barnes
33,868
Benson
21,407
Billings
45,523
Bottineau
35,039
Bowman
36,221
Burke
35,806
Burleigh
37,764
Cass
36,655
Cavalier
43,125
Dickey
32,943
Divide
45,190
Dunn
44,492
Eddy
34,565
Emmons
29,417
Foster
33,737
Golden Valley
32,590
Grand Forks
31,052
Grant
36,287
Griggs
35,069
Hettinger
32,474
Kidder
32,364
LaMoure
36,584
Logan
33,396
McHenry
37,626
McIntosh
32,389
McKenzie
36,798
McLean
35,367
Mercer
38,298
Morton
39,300
Mountrail
37,602
Nelson
33,360
Oliver
33,849
Pembina
36,251
Pierce
28,008
Ramsey
35,059
Ransom
34,691
Renville
33,635
Richland
30,820
Rolette
19,295
Sargent
37,039
Sheridan
32,559
Sioux
16,706
Slope
37,340
Stark
37,897
Steele
39,403
Stutsman
32,001
Towner
36,217
Traill
32,712
Walsh
31,366
Ward
34,382
Wells
34,602
Williams
43,824
Value for North Dakota (US Dollars): $35,373
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.