Indiana Homeownership rate, 2014-2018 by City

Data Item State
Owner-occupied housing unit rate, 2014-2018 - (Percent)
City Value
Anderson 56.6
Angola 48.3
Auburn 68.5
Avon 82.9
Batesville 64.4
Bedford 63.3
Beech Grove 54.6
Bloomington 34.6
Bluffton 66.5
Boonville 72.1
Brazil 57.4
Bright 84.3
Brownsburg 71.0
Carmel 77.1
Cedar Lake 77.4
Charlestown 61.6
Chesterton 69.2
Clarksville 58.2
Columbia City 70.1
Columbus 62.5
Connersville 59.5
Crawfordsville 53.5
Crown Point 80.9
Cumberland 73.7
Danville 67.6
Decatur 63.4
Dunlap 89.5
Dyer 89.9
East Chicago 45.5
Elkhart 48.1
Ellettsville 73.6
Elwood 63.3
Evansville 54.8
Fort Wayne 61.7
Frankfort 60.3
Franklin 63.8
Garrett 68.7
Gary 51.3
Gas City 67.0
Goshen 55.1
Granger 95.5
Greencastle 47.5
Greenfield 59.3
Greensburg 55.3
Greenwood 57.8
Griffith 68.4
Grissom AFB 22.7
Hammond 60.7
Hartford City 72.2
Hidden Valley 96.1
Highland 79.3
Hobart 73.8
Huntingburg 60.9
Huntington 63.9
Jasper 75.4
Jeffersonville 68.0
Kendallville 61.3
Kokomo 61.3
La Porte 57.9
Lafayette 47.5
Lake Station 70.3
Lakes of the Four Seasons 92.7
Lawrence 64.0
Lawrenceburg 43.8
Lebanon 63.0
Linton 68.8
Logansport 61.1
Lowell 80.2
Madison 58.0
Marion 55.5
Martinsville 52.7
Merrillville 65.8
Michigan City 53.7
Mishawaka 50.4
Monticello 68.4
Mooresville 66.1
Mount Vernon 64.1
Muncie 51.3
Munster 87.5
Nappanee 64.5
New Albany 54.5
New Castle 60.0
New Haven 74.3
New Whiteland 86.9
Noblesville 70.0
North Manchester 58.6
North Vernon 51.8
Notre Dame 0.0
Peru 62.6
Plainfield 66.9
Plymouth 55.9
Portage 67.6
Portland 60.6
Princeton 60.9
Rensselaer 60.0
Richmond 56.4
Rochester 64.7
Rushville 56.5
Salem 63.6
Schererville 78.5
Scottsburg 53.0
Sellersburg 76.1
Seymour 63.6
Shelbyville 58.6
South Bend 56.9
South Haven 68.4
Speedway 46.2
St. John 97.5
Tell City 69.0
Terre Haute 52.5
Tipton 70.8
Valparaiso 56.3
Vincennes 51.2
Wabash 65.8
Warsaw 52.9
Washington 63.3
West Lafayette 34.6
Westville 75.8
Yorktown 82.1
Zionsville 81.3

Data item: Owner-occupied housing unit rate, 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

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."

The homeownership rate is computed by dividing the number of owner-occupied housing units by the number of occupied housing units or households.

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:

21.3% - 0.7% = 20.6% => Lower-bound estimate
21.3% + 0.7% = 22.0% => Upper-bound 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.

For this Fact, its estimates and margins of error along with percents and percent margins of errors can be found on American Community Survey, Data Profiles-Housing Characteristics

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