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
Albany
20.5
Allegany
21.7
Broome
19.7
Cattaraugus
21.6
Cayuga
22.9
Chautauqua
17.9
Chemung
19.6
Chenango
24.3
Clinton
19.5
Columbia
25.8
Cortland
20.9
Delaware
24.4
Dutchess
32.8
Erie
21.5
Essex
21.8
Franklin
21.8
Fulton
24.9
Genesee
22.2
Greene
27.4
Hamilton
25.3
Herkimer
23.3
Jefferson
17.8
Lewis
24.3
Livingston
25.4
Madison
23.4
Monroe
20.2
Montgomery
25.1
Nassau
36.2
Niagara
22.6
Oneida
19.8
Onondaga
20.0
Ontario
23.4
Orange
33.3
Orleans
25.0
Oswego
25.0
Otsego
22.8
Putnam
39.3
Rensselaer
24.3
Rockland
31.6
Saratoga
25.4
Schenectady
22.8
Schoharie
29.9
Schuyler
24.9
Seneca
21.6
St. Lawrence
20.7
Steuben
21.8
Suffolk
32.4
Sullivan
30.6
Tioga
23.3
Tompkins
18.9
Ulster
28.4
Warren
22.6
Washington
26.6
Wayne
24.7
Westchester
34.6
Wyoming
24.9
Yates
22.1
Value for New York (Minutes): 33.3
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.
