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
Barbour
22,237
Berkeley
28,736
Boone
21,394
Braxton
21,596
Brooke
25,537
Cabell
24,506
Calhoun
19,911
Clay
16,780
Doddridge
22,598
Fayette
21,466
Gilmer
17,313
Grant
22,828
Greenbrier
23,936
Hampshire
23,011
Hancock
25,637
Hardy
26,596
Harrison
27,869
Jackson
24,661
Jefferson
34,750
Kanawha
28,405
Lewis
22,575
Lincoln
19,423
Logan
21,672
Marion
25,909
Marshall
24,882
Mason
21,812
McDowell
14,489
Mercer
21,821
Mineral
23,546
Mingo
19,025
Monongalia
30,641
Monroe
23,412
Morgan
27,642
Nicholas
21,941
Ohio
30,258
Pendleton
24,739
Pleasants
27,522
Pocahontas
24,109
Preston
23,337
Putnam
31,277
Raleigh
24,170
Randolph
24,162
Ritchie
24,442
Roane
20,574
Summers
20,784
Taylor
24,258
Tucker
23,670
Tyler
24,422
Upshur
21,701
Wayne
21,240
Webster
20,507
Wetzel
22,789
Wirt
21,314
Wood
27,201
Wyoming
20,831
Value for West Virginia (US Dollars): $25,479
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.