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
Barbour
39,580
Berkeley
60,615
Boone
38,642
Braxton
42,213
Brooke
49,772
Cabell
38,321
Calhoun
37,610
Clay
35,875
Doddridge
46,449
Fayette
40,379
Gilmer
35,810
Grant
41,071
Greenbrier
39,038
Hampshire
40,099
Hancock
45,580
Hardy
47,186
Harrison
50,433
Jackson
44,783
Jefferson
76,503
Kanawha
45,426
Lewis
39,423
Lincoln
37,679
Logan
38,123
Marion
48,605
Marshall
43,918
Mason
40,347
McDowell
26,547
Mercer
39,372
Mineral
46,354
Mingo
31,305
Monongalia
49,926
Monroe
36,493
Morgan
50,661
Nicholas
38,468
Ohio
48,418
Pendleton
41,210
Pleasants
48,563
Pocahontas
39,702
Preston
48,317
Putnam
59,626
Raleigh
42,296
Randolph
41,094
Ritchie
44,472
Roane
34,300
Summers
36,049
Taylor
47,205
Tucker
45,655
Tyler
41,108
Upshur
40,401
Wayne
36,875
Webster
34,312
Wetzel
42,125
Wirt
40,189
Wood
45,958
Wyoming
40,045
Value for West Virginia (US Dollars): $44,921
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.
