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
Alameda
707,800
Alpine
349,000
Amador
296,400
Butte
248,100
Calaveras
297,700
Colusa
249,800
Contra Costa
582,400
Del Norte
204,000
El Dorado
437,200
Fresno
237,500
Glenn
222,000
Humboldt
296,600
Imperial
177,100
Inyo
262,400
Kern
205,200
Kings
202,800
Lake
195,400
Lassen
184,200
Los Angeles
543,400
Madera
235,200
Marin
959,200
Mariposa
269,500
Mendocino
356,800
Merced
229,500
Modoc
133,300
Mono
326,400
Monterey
477,200
Napa
603,700
Nevada
400,000
Orange
652,900
Placer
443,700
Plumas
234,900
Riverside
330,600
Sacramento
330,100
San Benito
496,200
San Bernardino
305,400
San Diego
526,300
San Francisco
1,009,500
San Joaquin
313,800
San Luis Obispo
537,900
San Mateo
994,100
Santa Barbara
549,900
Santa Clara
913,000
Santa Cruz
711,000
Shasta
242,500
Sierra
173,200
Siskiyou
186,300
Solano
377,500
Sonoma
568,700
Stanislaus
272,400
Sutter
260,300
Tehama
203,400
Trinity
284,600
Tulare
191,200
Tuolumne
278,900
Ventura
559,700
Yolo
395,500
Yuba
231,900
Value for California (US Dollars): $475,900
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.
