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.
In civilian labor force, female, percent of population age 16 years+, 2014-2018 - (Percent)
County
Value
Barbour
49.1
Berkeley
60.6
Boone
35.3
Braxton
46.3
Brooke
49.6
Cabell
48.8
Calhoun
37.9
Clay
35.0
Doddridge
41.4
Fayette
43.0
Gilmer
50.3
Grant
48.7
Greenbrier
46.7
Hampshire
43.1
Hancock
54.6
Hardy
54.6
Harrison
52.7
Jackson
44.6
Jefferson
58.9
Kanawha
52.0
Lewis
44.5
Lincoln
41.0
Logan
38.9
Marion
52.2
Marshall
45.7
Mason
39.1
McDowell
29.2
Mercer
45.9
Mineral
49.6
Mingo
35.9
Monongalia
55.9
Monroe
48.4
Morgan
48.3
Nicholas
43.5
Ohio
54.6
Pendleton
45.2
Pleasants
47.8
Pocahontas
45.6
Preston
49.6
Putnam
53.4
Raleigh
46.3
Randolph
48.2
Ritchie
41.7
Roane
41.2
Summers
38.9
Taylor
49.8
Tucker
46.1
Tyler
41.4
Upshur
46.7
Wayne
42.9
Webster
42.2
Wetzel
40.6
Wirt
44.5
Wood
51.6
Wyoming
34.3
Value for West Virginia (Percent): 48.9%
Data item: In civilian labor force, female, percent of population age 16 years+, 2014-2018
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
Civilian Labor Force consists of people classified as employed or unemployed in accordance with the criteria described below.
Employed - This category includes all civilians 16 years old and over who either (1) were "at work," that is, those who did any work at all during the reference week as paid employees, worked in their own business or profession, worked on their own farm, or worked 15 hours or more as unpaid workers on a family farm or in a family business; or (2) were "with a job but not at work," that is, those who did not work during the reference week but had jobs or businesses from which they were temporarily absent due to illness, bad weather, industrial dispute, vacation, or other personal reasons. Excluded from the employed are people whose only activity consisted of work around the house or unpaid volunteer work for religious, charitable, and similar organizations; also excluded are all institutionalized people and people on active duty in the United States Armed Forces. For the complete definition, go to ACS subject definitions "Employment Status."
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.
