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
Aurora
31,468
Beadle
26,316
Bennett
16,625
Bon Homme
23,525
Brookings
27,968
Brown
31,977
Brule
28,292
Buffalo
11,471
Butte
26,702
Campbell
39,986
Charles Mix
21,787
Clark
30,339
Clay
26,230
Codington
29,992
Corson
15,984
Custer
30,439
Davison
29,342
Day
28,873
Deuel
29,281
Dewey
16,967
Douglas
29,458
Edmunds
32,492
Fall River
27,266
Faulk
29,065
Grant
31,453
Gregory
27,579
Haakon
24,426
Hamlin
27,777
Hand
33,865
Hanson
25,039
Harding
31,599
Hughes
33,810
Hutchinson
27,995
Hyde
31,692
Jackson
13,595
Jerauld
38,650
Jones
28,850
Kingsbury
32,259
Lake
31,574
Lawrence
31,744
Lincoln
39,797
Lyman
22,097
Marshall
31,307
McCook
28,032
McPherson
27,240
Meade
28,654
Mellette
13,538
Miner
27,570
Minnehaha
30,471
Moody
29,142
Pennington
30,518
Perkins
33,065
Potter
31,467
Roberts
26,537
Sanborn
32,404
Spink
33,597
Stanley
35,936
Sully
42,276
Todd
10,931
Tripp
26,242
Turner
29,465
Union
40,699
Walworth
31,302
Yankton
31,986
Ziebach
14,943
Value for South Dakota (US Dollars): $29,801
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.