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
Abbeville
21,185
Aiken
27,526
Allendale
14,744
Anderson
25,807
Bamberg
18,873
Barnwell
19,620
Beaufort
36,306
Berkeley
28,331
Calhoun
25,953
Charleston
37,801
Cherokee
21,432
Chester
21,240
Chesterfield
20,676
Clarendon
20,967
Colleton
21,003
Darlington
21,587
Dillon
16,473
Dorchester
28,704
Edgefield
25,410
Fairfield
22,527
Florence
25,149
Georgetown
29,929
Greenville
30,776
Greenwood
23,945
Hampton
17,523
Horry
26,917
Jasper
22,406
Kershaw
24,253
Lancaster
29,271
Laurens
21,743
Lee
17,544
Lexington
30,316
Marion
19,992
Marlboro
17,034
McCormick
24,419
Newberry
23,344
Oconee
28,076
Orangeburg
19,992
Pickens
24,803
Richland
29,010
Saluda
22,174
Spartanburg
26,072
Sumter
22,272
Union
22,372
Williamsburg
18,454
York
32,227
Value for South Carolina (US Dollars): $27,986
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.