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.
Mean travel time to work (minutes), workers age 16 years+, 2014-2018 - (Minutes)
County
Value
Autauga
25.8
Baldwin
27.4
Barbour
22.7
Bibb
29.2
Blount
35.1
Bullock
28.6
Butler
24.0
Calhoun
25.0
Chambers
23.6
Cherokee
28.1
Chilton
33.2
Choctaw
32.2
Clarke
24.4
Clay
29.0
Cleburne
33.0
Coffee
22.3
Colbert
23.2
Conecuh
25.1
Coosa
29.2
Covington
25.0
Crenshaw
27.9
Cullman
26.4
Dale
21.5
Dallas
22.5
DeKalb
23.7
Elmore
27.7
Escambia
22.7
Etowah
24.0
Fayette
28.5
Franklin
28.6
Geneva
27.5
Greene
31.9
Hale
30.3
Henry
26.3
Houston
21.1
Jackson
25.2
Jefferson
23.9
Lamar
27.9
Lauderdale
23.6
Lawrence
28.2
Lee
22.2
Limestone
26.0
Lowndes
32.0
Macon
23.3
Madison
21.4
Marengo
25.5
Marion
24.1
Marshall
24.6
Mobile
25.0
Monroe
25.7
Montgomery
20.5
Morgan
23.6
Perry
27.0
Pickens
35.6
Pike
21.1
Randolph
26.8
Russell
25.4
Shelby
28.4
St. Clair
29.3
Sumter
25.7
Talladega
25.0
Tallapoosa
26.1
Tuscaloosa
22.6
Walker
28.7
Washington
34.8
Wilcox
25.4
Winston
29.3
Value for Alabama (Minutes): 24.7
Data item: Mean travel time to work (minutes), workers age 16 years+, 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
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.
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. For the complete definition, go to ACS subject definitions "Travel Time to Work."
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.
