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
92,800
Alcorn
92,400
Amite
75,500
Attala
76,000
Benton
68,800
Bolivar
94,700
Calhoun
67,700
Carroll
89,300
Chickasaw
66,000
Choctaw
81,600
Claiborne
63,000
Clarke
79,700
Clay
87,400
Coahoma
67,200
Copiah
97,900
Covington
78,600
DeSoto
162,000
Forrest
120,700
Franklin
76,500
George
109,800
Greene
80,900
Grenada
99,700
Hancock
144,400
Harrison
144,500
Hinds
115,200
Holmes
56,100
Humphreys
68,900
Issaquena
57,500
Itawamba
89,500
Jackson
129,400
Jasper
73,400
Jefferson
62,300
Jefferson Davis
84,200
Jones
92,100
Kemper
71,200
Lafayette
188,600
Lamar
170,400
Lauderdale
93,100
Lawrence
93,200
Leake
78,500
Lee
131,300
Leflore
79,700
Lincoln
99,600
Lowndes
131,800
Madison
215,100
Marion
85,100
Marshall
108,000
Monroe
88,200
Montgomery
80,000
Neshoba
81,400
Newton
83,000
Noxubee
60,800
Oktibbeha
161,100
Panola
77,400
Pearl River
128,600
Perry
83,700
Pike
91,400
Pontotoc
102,700
Prentiss
91,800
Quitman
52,300
Rankin
160,000
Scott
68,700
Sharkey
61,800
Simpson
84,200
Smith
95,400
Stone
117,800
Sunflower
73,900
Tallahatchie
63,500
Tate
117,800
Tippah
83,100
Tishomingo
85,300
Tunica
101,600
Union
95,000
Walthall
90,400
Warren
118,600
Washington
74,700
Wayne
84,000
Webster
83,100
Wilkinson
70,000
Winston
84,100
Yalobusha
83,100
Yazoo
81,400
Value for Mississippi (US Dollars): $114,500
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.
