Utah Average Commute Time by County

Data Item State
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Mean travel time to work (minutes), workers age 16+, 2009-2013 - (Minutes)
County Value
Beaver 16.9
Box Elder 22.6
Cache 16.6
Carbon 15.9
Daggett 15.0
Davis 22.3
Duchesne 22.5
Emery 19.1
Garfield 13.3
Grand 14.5
Iron 18.2
Juab 24.0
Kane 16.5
Millard 17.6
Morgan 26.1
Piute 20.3
Rich 22.0
Salt Lake 22.2
San Juan 20.5
Sanpete 21.0
Sevier 15.3
Summit 24.1
Tooele 29.5
Uintah 19.0
Utah 21.1
Wasatch 23.9
Washington 18.1
Wayne 14.4
Weber 21.4

Value for Utah (Minutes): 21.4

Data item: Mean travel time to work (minutes), workers age 16+, 2009-2013

Source: U. S. Census Bureau, American Community Survey, 5-Year Estimates. Updated every year. http://factfinder2.census.gov


Travel time to work refers to the total number of minutes that it usually took the person to get from home to work each day during the reference week. The elapsed time includes time spent waiting for public transportation, picking up passengers in carpools, and time spent in other activities related to getting to work.

Data were tabulated for workers 16 years old and over--that is, members of the Armed Forces and civilians who were at work during the reference week--who reported that they worked outside their home.

Mean travel time to work is obtained by dividing the total number of minutes by the number of workers 16 years old and over who did not work at home. Mean travel time to work is rounded to the nearest tenth of a minute.

Scope and Methodology:

These data are collected in the American Community Survey (ACS). The data for each geographic area are presented together with margins of error at factfinder2.census.gov. The data are period estimates, that is, they represent the characteristics of the population and housing over a specific 60-month data collection period.

Margins of Error (MOE). ACS estimates are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a MOE. The MOE used with ACS estimates can be interpreted as providing a 90 percent probability that the interval defined by the estimate plus the MOE and the estimate minus the MOE (the upper and lower confidence bounds) contains the full population value of the estimate.

For example, suppose the 5-year ACS reported the percentage of people 25 years and older in Birmingham, Alabama who had a bachelor's degree was 21.3 percent and that the MOE associated with this estimate is plus or minus (+/-) 0.9 percent. By adding and subtracting the MOE from the estimate, we can calculate the 90-percent confidence interval for this estimate at 21.3%, +/-0.9%:

21.3% - 0.9% = 20.4% = Lower-bound estimate
21.3% + 0.9% = 22.2% = Upper-bound estimate

Therefore, we can be 90 percent confident that the percent of the population in Birmingham, Alabama of age 25 years and older having a bachelor's degree in 2007-2011 falls somewhere between 20.4 percent and 22.2 percent.

For this Fact and other 5-year Economic Characteristic Facts (listed below), their estimates and margins of error or percents and percent margins of errors can be found on Data Profile - Economic Characteristics. This profile is displayed by geography. Click on the link for "Browse for Data sets (geography picked)" near the top of the Quick facts profile page, click on the link for People QuickLinks/American Community Survey - "Economic Characteristics" for the data profile.

Mean travel time to work (minutes), workers age 16 and over;
Per capita money income in the past 12 months,
Median household income,
Persons below poverty level, percent

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