The data on place of work were derived from answers to Question 30, which was asked of people who indicated in Question 29 that they worked at some time during the reference week. (See "Reference Week.")

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. Data on place of work refer to the geographic location at which workers carried out their occupational activities during the reference week. In the American Community Survey, the exact address (number and street name) of the place of work was asked, as well as the place (city, town, or post office); whether the place of work was inside or outside the limits of that city or town; and the county, state or foreign country, and ZIP Code. In the Puerto Rico Community Survey, the question asked for the exact address, including the development or condominium name, as well as the place; whether or not the place of work was inside or outside the limits of that city or town; the municipio or U.S. county. Respondents also were asked to enter Puerto Rico or name of U.S. state or foreign country and the ZIP Code. If the respondent's employer operated in more than one location, the exact address of the location or branch where he or she worked was requested. When the number and street name were unknown, a description of the location, such as the building name or nearest street or intersection, was to be entered. People who worked at more than one location during the reference week were asked to report the location at which they worked the greatest number of hours. People who regularly worked in several locations each day during the reference week were requested to give the address at which they began work each day. For cases in which daily work did not begin at a central place each day, the respondent was asked to provide as much information as possible to describe the area in which he or she worked most during the reference week.

Place-of-work data may show a few workers who made unlikely daily work trips (e.g., workers who lived in New York and worked in California). This result is attributable to people who worked during the reference week at a location that was different from their usual place of work, such as people away from home on business.

In areas where the workplace address was geographically coded to the block level, people were tabulated as working inside or outside a specific place based on the location of that address regardless of the response to Question 30c concerning city/town limits. In areas where it was impossible to code the workplace address to the block level, or the coding system was unable to match the employer name and street address responses, people were tabulated as working inside or outside a specific place based on the combination of state, county, ZIP Code, place name, and city limits indicator. The city limits indicator was used only in coding decisions when there were multiple geographic codes to select from, after matching on the state, county, place, and ZIP Code responses. The accuracy of place-of-work data for census designated places (CDPs) may be affected by the extent to which their census names were familiar to respondents, and by coding problems caused by similarities between the CDP name and the names of other geographic jurisdictions in the same vicinity.

Place-of-work data are given for selected minor civil divisions (MCDs), (generally cities, towns, and townships) in the 12 strong MCD states (Connecticut, Maine, Massachusetts, Michigan, Minnesota, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Wisconsin), based on the responses to the place of work question. Many towns and townships are regarded locally as equivalent to a place, and therefore, were reported as the place of work. When a respondent reported a locality or incorporated place that formed a part of a township or town, the coding and tabulating procedure was designed to include the response in the total for the township or town.

The characteristics of workers may be shown using either residence-based or workplace-based geography. If you are interested in the number and characteristics of workers living in a specific area, you should use the standard (residence-based) journey-to-work tables. If you are interested in the number and characteristics of workers who work in a specific area, you should use the workplace-based journey-to-work tables. Because place-of-work information for workers cannot always be specified below the place level, the workplace-based tables are presented only for selected geographic areas.

The data on means of transportation to work were derived from answers to Question 31, which was asked of people who indicated in Question 29 that they worked at some time during the reference week. (See "Reference Week".) Means of transportation to work refers to the principal mode of travel or type of conveyance that the worker usually used to get from home to work during the reference week.

People who used different means of transportation on different days of the week were asked to specify the one they used most often, that is, the greatest number of days. People who used more than one means of transportation to get to work each day were asked to report the one used for the longest distance during the work trip. The category, "Car, truck, or van", includes workers using a car (including company cars but excluding taxicabs), a truck of one-ton capacity or less, or a van. The category, "Public transportation", includes workers who used a bus or trolley bus, streetcar or trolley car, subway or elevated, railroad, or ferryboat, even if each mode is not shown separately in the tabulation. "Carro público" is included in the public transportation category in Puerto Rico. The category, "Other means," includes workers who used a mode of travel that is not identified separately within the data distribution. The category, "Other means," may vary from table to table, depending on the amount of detail shown in a particular distribution.

The means of transportation data for some areas may show workers using modes of public transportation that are not available in those areas (for example, subway or elevated riders in a metropolitan area where there is no subway or elevated service). This result is largely due to people who worked during the reference week at a location that was different from their usual place of work (such as people away from home on business in an area where subway service was available), and people who used more than one means of transportation each day but whose principal means was unavailable where they lived (for example, residents of nonmetropolitan areas who drove to the fringe of a metropolitan area, and took the commuter railroad most of the distance to work).

The median age is the age that divides the population into two equal-size groups. Half of the population is older than the median age and half is younger. Median age is based on a standard distribution of the population by single years of age and is shown to the nearest tenth of a year. (See the sections on "Standard Distributions" and "Medians" under "Derived Measures".)

The age dependency ratio is derived by dividing the combined under 18 years and 65 years and over populations by the 18-to-64 population and multiplying by 100.

The old-age dependency ratio is derived by dividing the population 65 years and over by the 18-to-64 population and multiplying by 100.

The child dependency ratio is derived by dividing the population under 18 years by the 18-to-64 population, and multiplying by 100.

The 1996-2002 American Community Survey question asked for month, day, and year of birth before age. Since 2003, the American Community Survey question asked for age, followed by month, day, and year of birth. In 2008, an additional instruction was provided with the age and date of birth question on the American Community Survey questionnaire to report babies as age 0 when the child was less than 1 year old. The addition of this instruction occurred after 2005 National Census Test results indicated increased accuracy of age reporting for babies less than one year old.

Beginning in 2006, the population living in group quarters (GQ) was included in the American Community Survey population universe. Some types of group quarters have populations with age distributions that are very different from that of the household population. The inclusion of the GQ population could therefore have a noticeable impact on the age distribution for a given geographic area. This is particularly true for areas with a substantial GQ population. For example, in areas with large colleges and universities, the percent of individuals 18-24 would increase due to the inclusion of GQs in the American Community Survey universe.

Caution should be taken when comparing population in age groups across time. The entire population continually ages into older age groups over time, and babies fill in the youngest age group. Therefore, the population of a certain age is made up of a completely different group of people in one time period than in another (e.g. one age group in 2000 versus same age group in 2009). Since populations occasionally experience booms/increases and busts/decreases in births, deaths, or migration (for example, the postwar Baby Boom from 1946-1964), one should not necessarily expect that the population in an age group in one year should be similar in size or proportion to the population in the same age group in a different period in time. For example, Baby Boomers were age 36 to 54 in Census 2000 while they were age 45 to 63 in 2009 ACS. The age structure and distribution would therefore shift in those age groups to reflect the change in people occupying those age-specific groups over time.

Data users should also be aware of methodology differences that may exist between different data sources if they are comparing American Community Survey age data to data sources, such as Population Estimates or Decennial Census data. For example, the American Community Survey data are that of a respondent-based survey and subject to various quality measures, such as sampling and nonsampling error, response rates and item allocation error. This differs in design and methodology from other data sources, such as Population Estimates, which is not a survey and involves computational methodology to derive intercensal estimates of the population. While ACS estimates are controlled to Population Estimates for age at the nation, state and county levels of geography as part of the ACS weighting procedure, variation may exist in the age structure of a population at lower levels of geography when comparing different time periods or comparing across time due to the absence of controls below the county geography level. For more information on American Community Survey data accuracy and weighting procedures, please see www.census.gov/acs.

It should also be noted that although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates theofficial estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties. (Please refer to: factfinder.census.gov/home/en/official_estimates_2008.html)