Pennsylvania 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
Adams 27.7
Allegheny 26.0
Armstrong 27.9
Beaver 25.1
Bedford 28.0
Berks 24.5
Blair 19.0
Bradford 22.5
Bucks 28.3
Butler 26.4
Cambria 22.7
Cameron 15.2
Carbon 30.5
Centre 19.9
Chester 27.4
Clarion 22.8
Clearfield 25.1
Clinton 23.3
Columbia 21.1
Crawford 22.4
Cumberland 21.2
Dauphin 21.3
Delaware 27.7
Elk 16.8
Erie 18.6
Fayette 25.2
Forest 26.7
Franklin 23.2
Fulton 33.0
Greene 26.9
Huntingdon 28.1
Indiana 22.8
Jefferson 21.9
Juniata 29.3
Lackawanna 20.0
Lancaster 22.5
Lawrence 22.4
Lebanon 22.9
Lehigh 24.2
Luzerne 22.2
Lycoming 19.8
McKean 20.0
Mercer 21.0
Mifflin 23.0
Monroe 38.9
Montgomery 27.5
Montour 18.7
Northampton 27.3
Northumberland 23.5
Perry 31.6
Philadelphia 31.8
Pike 41.5
Potter 21.9
Schuylkill 25.6
Snyder 23.1
Somerset 23.2
Sullivan 26.5
Susquehanna 27.0
Tioga 23.5
Union 21.3
Venango 21.6
Warren 19.8
Washington 26.2
Wayne 28.8
Westmoreland 26.4
Wyoming 26.2
York 26.6

Value for Pennsylvania (Minutes): 25.9

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.


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 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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