Indiana Population Percentage Living in Same House 1 Year and Over by City

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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.
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Data Item State
Living in same house 1 year ago, percent of persons age 1 year+, 2014-2018 - (Percent)
City Value
Anderson 79.3
Angola 73.1
Auburn 80.9
Avon 85.8
Batesville 84.2
Bedford 83.7
Beech Grove 90.1
Bloomington 57.0
Bluffton 86.7
Boonville 85.5
Brazil 83.1
Bright 91.8
Brownsburg 85.0
Carmel 84.5
Cedar Lake 89.6
Charlestown 86.0
Chesterton 91.2
Clarksville 87.3
Columbia City 86.1
Columbus 82.6
Connersville 83.6
Crawfordsville 74.5
Crown Point 84.9
Cumberland 94.3
Danville 80.6
Decatur 78.0
Dunlap 93.3
Dyer 92.3
East Chicago 86.5
Elkhart 84.3
Ellettsville 85.3
Elwood 78.9
Evansville 80.2
Fort Wayne 83.2
Frankfort 85.5
Franklin 82.1
Garrett 87.9
Gary 84.1
Gas City 87.6
Goshen 82.9
Granger 93.4
Greencastle 64.0
Greenfield 79.6
Greensburg 80.3
Greenwood 79.4
Griffith 87.5
Grissom AFB 73.5
Hammond 85.7
Hartford City 90.2
Hidden Valley 90.4
Highland 91.1
Hobart 88.7
Huntingburg 90.4
Huntington 81.8
Jasper 88.8
Jeffersonville 88.8
Kendallville 81.3
Kokomo 81.6
La Porte 80.8
Lafayette 76.0
Lake Station 82.8
Lakes of the Four Seasons 92.1
Lawrence 89.4
Lawrenceburg 79.2
Lebanon 79.8
Linton 81.7
Logansport 83.6
Lowell 86.6
Madison 76.5
Marion 81.1
Martinsville 72.5
Merrillville 86.0
Michigan City 78.2
Mishawaka 85.6
Monticello 82.2
Mooresville 89.4
Mount Vernon 88.2
Muncie 69.4
Munster 89.0
Nappanee 89.0
New Albany 85.0
New Castle 83.3
New Haven 85.2
New Whiteland 78.1
Noblesville 81.6
North Manchester 72.3
North Vernon 77.9
Notre Dame 38.7
Peru 80.8
Plainfield 78.4
Plymouth 86.7
Portage 86.6
Portland 78.6
Princeton 80.7
Rensselaer 80.5
Richmond 82.4
Rochester 89.1
Rushville 84.0
Salem 79.9
Schererville 90.4
Scottsburg 81.6
Sellersburg 89.0
Seymour 84.3
Shelbyville 82.6
South Bend 83.4
South Haven 82.7
Speedway 81.2
St. John 94.3
Tell City 91.8
Terre Haute 73.0
Tipton 82.7
Valparaiso 78.3
Vincennes 76.2
Wabash 80.6
Warsaw 67.3
Washington 82.8
West Lafayette 52.9
Westville 60.9
Yorktown 88.5
Zionsville 88.6

Data item: Living in same house 1 year ago, percent of persons age 1 year+, 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

Residence 1 year ago is used in conjunction with location of current residence to determine the extent of residential mobility of the population and the resulting redistribution of the population across the various states, metropolitan areas, and regions of the country. For the complete definition, go to ACS subject definitions "Residence 1 year ago."

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-Social Characteristics

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