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 value of owner-occupied housing units, 2014-2018 - (US Dollars)
County
Value
Abbeville
89,000
Aiken
142,200
Allendale
52,100
Anderson
137,200
Bamberg
71,400
Barnwell
79,900
Beaufort
288,900
Berkeley
174,000
Calhoun
104,000
Charleston
295,600
Cherokee
95,300
Chester
90,500
Chesterfield
82,400
Clarendon
93,800
Colleton
85,100
Darlington
87,800
Dillon
72,800
Dorchester
186,300
Edgefield
126,500
Fairfield
102,700
Florence
130,400
Georgetown
187,200
Greenville
172,100
Greenwood
117,300
Hampton
73,000
Horry
172,500
Jasper
154,400
Kershaw
124,700
Lancaster
182,400
Laurens
91,300
Lee
73,300
Lexington
151,900
Marion
76,700
Marlboro
64,000
McCormick
117,700
Newberry
100,000
Oconee
155,200
Orangeburg
93,200
Pickens
138,900
Richland
158,200
Saluda
107,700
Spartanburg
133,700
Sumter
113,900
Union
77,300
Williamsburg
66,700
York
186,000
Value for South Carolina (US Dollars): $154,800
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
Value is the respondent's estimate of how much the property (house and lot) would sell for if it were for sale.
This tabulation includes only specified owner-occupied housing units--one-family houses on less than 10 acres without a business or medical office on the property. These data exclude mobile homes, houses with a business or medical office, houses on 10 or more acres, and housing units in multi-unit structures. Certain tabulations elsewhere include the value of all owner-occupied housing units and vacant-for-sale housing units. Also available are data on mortgage status and selected monthly owner costs.
The median divides the value distribution into two equal parts: one-half of the cases falling below the median value of the property (house and lot) and one-half above the median. Median value calculations are rounded to the nearest hundred dollars.
Owner-Occupied - A housing unit is owner-occupied if the owner or co-owner lives in the unit, even if it is mortgaged or not fully paid for. The owner or co-owner must live in the unit and usually is Person 1 on the questionnaire. The unit is "Owned by you or someone in this household with a mortgage or loan" if it is being purchased with a mortgage or some other debt arrangement such as a deed of trust, trust deed, contract to purchase, land contract, or purchase agreement. The unit also is considered owned with a mortgage if it is built on leased land and there is a mortgage on the unit. Mobile homes occupied by owners with installment loan balances also are included in this category. For the complete definition, go to ACS subject definitions "Tenure."
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.
