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
Adams
201,900
Allegheny
147,700
Armstrong
103,600
Beaver
133,600
Bedford
128,200
Berks
174,200
Blair
120,300
Bradford
146,200
Bucks
323,300
Butler
197,600
Cambria
90,900
Cameron
75,800
Carbon
141,600
Centre
220,500
Chester
347,000
Clarion
114,300
Clearfield
94,000
Clinton
130,900
Columbia
149,100
Crawford
110,900
Cumberland
197,900
Dauphin
165,200
Delaware
239,600
Elk
99,000
Erie
130,000
Fayette
97,200
Forest
89,500
Franklin
175,600
Fulton
156,800
Greene
114,400
Huntingdon
126,800
Indiana
115,500
Jefferson
99,800
Juniata
145,300
Lackawanna
149,700
Lancaster
200,400
Lawrence
106,500
Lebanon
169,200
Lehigh
200,100
Luzerne
125,400
Lycoming
152,400
McKean
79,800
Mercer
119,600
Mifflin
109,900
Monroe
167,000
Montgomery
305,800
Montour
181,500
Northampton
214,200
Northumberland
115,200
Perry
166,200
Philadelphia
156,800
Pike
187,000
Potter
105,500
Schuylkill
97,400
Snyder
161,400
Somerset
104,300
Sullivan
151,800
Susquehanna
162,500
Tioga
138,700
Union
180,200
Venango
85,700
Warren
95,400
Washington
162,600
Wayne
181,000
Westmoreland
148,900
Wyoming
164,000
York
173,200
Value for Pennsylvania (US Dollars): $174,100
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.
