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.
Median household income (in 2018 dollars), 2014-2018 - (US Dollars)
County
Value
Aurora
59,293
Beadle
51,700
Bennett
48,348
Bon Homme
54,450
Brookings
56,370
Brown
56,455
Brule
50,839
Buffalo
32,500
Butte
44,387
Campbell
52,500
Charles Mix
46,389
Clark
47,798
Clay
43,189
Codington
54,774
Corson
35,441
Custer
55,472
Davison
47,772
Day
44,145
Deuel
57,930
Dewey
43,954
Douglas
57,419
Edmunds
68,551
Fall River
50,837
Faulk
53,889
Grant
62,532
Gregory
44,479
Haakon
37,420
Hamlin
65,050
Hand
52,438
Hanson
63,036
Harding
57,365
Hughes
63,564
Hutchinson
54,868
Hyde
54,891
Jackson
33,438
Jerauld
49,519
Jones
41,103
Kingsbury
59,375
Lake
59,232
Lawrence
52,245
Lincoln
81,422
Lyman
53,263
Marshall
63,594
McCook
62,234
McPherson
43,804
Meade
59,218
Mellette
31,222
Miner
51,394
Minnehaha
60,028
Moody
58,167
Pennington
55,024
Perkins
56,850
Potter
53,600
Roberts
50,495
Sanborn
54,899
Spink
52,729
Stanley
71,763
Sully
64,028
Todd
24,257
Tripp
51,027
Turner
55,380
Union
69,563
Walworth
52,123
Yankton
54,694
Ziebach
37,143
Value for South Dakota (US Dollars): $56,499
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
Income in the Past 12 Months - Income of Households: This includes the income of the householder and all other individuals 15 years old and over in the household, whether they are related to the householder or not. Because many households consist of only one person, average household income is usually less than average family income. Although the household income statistics cover the past 12 months, the characteristics of individuals and the composition of households refer to the time of interview. Thus, the income of the household does not include amounts received by individuals who were members of the household during all or part of the past 12 months if these individuals no longer resided in the household at the time of interview. Similarly, income amounts reported by individuals who did not reside in the household during the past 12 months but who were members of the household at the time of interview are included. However, the composition of most households was the same during the past 12 months as at the time of interview.
The median divides the income distribution into two equal parts: one-half of the cases falling below the median income and one-half above the median. For households and families, the median income is based on the distribution of the total number of households and families including those with no income. The median income for individuals is based on individuals 15 years old and over with income. Median income for households, families, and individuals is computed on the basis of a standard distribution. For the complete definition, go to ACS subject definitions "Income in the Past 12 Months."
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.
