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
Aurora
62.8
Beadle
58.8
Bennett
53.8
Bon Homme
61.0
Brookings
68.6
Brown
65.3
Brule
64.4
Buffalo
54.6
Butte
59.2
Campbell
59.9
Charles Mix
58.0
Clark
56.2
Clay
67.3
Codington
64.7
Corson
56.6
Custer
48.8
Davison
63.5
Day
54.5
Deuel
61.4
Dewey
62.5
Douglas
58.5
Edmunds
57.9
Fall River
54.9
Faulk
54.4
Grant
57.7
Gregory
56.6
Haakon
44.4
Hamlin
60.6
Hand
58.3
Hanson
62.5
Harding
57.9
Hughes
62.4
Hutchinson
59.9
Hyde
49.0
Jackson
48.3
Jerauld
52.8
Jones
64.8
Kingsbury
61.7
Lake
66.2
Lawrence
63.1
Lincoln
71.6
Lyman
62.4
Marshall
63.4
McCook
67.2
McPherson
52.8
Meade
63.3
Mellette
41.6
Miner
62.0
Minnehaha
71.2
Moody
63.2
Pennington
62.8
Perkins
64.3
Potter
53.7
Roberts
65.1
Sanborn
66.7
Spink
58.3
Stanley
74.6
Sully
55.2
Todd
46.9
Tripp
59.2
Turner
60.6
Union
61.5
Walworth
58.3
Yankton
62.3
Ziebach
63.6
Value for South Dakota (Percent): 64.2%
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.