This question is based on the count of people in occupied housing units. All people occupying the housing unit are counted, including the householder, occupants related to the householder, and lodgers, roomers, boarders, and so forth.

A measure obtained by dividing the number of people living in occupied housing units by the total number of occupied housing units. This measure is rounded to the nearest hundredth.

A measure obtained by dividing the number of people living in owner-occupied housing units by the total number of owner-occupied housing units. This measure is rounded to the nearest hundredth.

A measure obtained by dividing the number of people living in renter-occupied housing units by the total number of renter-occupied housing units. This measure is rounded to the nearest hundredth.

The Census Bureau does not recommend trend analysis using the 2003-2006 data with years prior to 2003 due to the 2003 questionnaire change. For more information regarding the 2003 questionnaire change, view "Disability Data From the American Community Survey: A Brief Examination of the Effects of a Question Redesign in 2003" ( http://www.census.gov/hhes/www/disability/ACS_disability.pdf).

For the 1996-1998 American Community Survey, the data on going-outside-home limitations were derived from answers to Question 16a, which was asked of persons 16 years old and over. The question was slightly different from the 1999-2002 question and asked the respondents if they had a long-lasting physical or mental condition that made it difficult to "go outside the home alone to shop or visit a doctor's office." In the 1999-2002 American Community Survey, the going-outside-home question was part of Question 16. The 2003 questionnaire moved go-outside-home limitations to Question 17a and introduced a new skip instruction between Questions 16 and 17.

The review process involves both review of the editing process and a reasonableness review. After editing and imputation are complete, Census Bureau subject matter analysts review the resulting data files. The files contain both unedited and edited data, together with the accompanying imputation flag variables that indicate which missing, inconsistent, or incomplete items have been filled by imputation methods. Subject matter analysts first compare the unedited and edited data to see that the edit process worked as intended. The subject analysts also undertake their own analyses, looking for problems or inconsistencies in the data from their perspectives. When conducting the initial edit review, they determine whether the results make sense through a process known as a reasonableness review. If year-to-year changes do not appear to be reasonable, they institute a more comprehensive review to reexamine and resolve the issues. Allocation rates from the current year are compared with previous years to check for notable differences. A reasonableness review is done by topic, and results on unweighted data are compared across years to see if there are substantial differences. The initial reasonableness review takes place with national data, and another final review compares data from smaller geographic areas, such as counties and states (Jiles, 2007).

These processes also are carried out after weighting and swapping data (discussed in Chapter 12). Analysts also examine unusual individual cases that were changed during editing to ensure accuracy and reasonableness.

The analysts also use a number of special reports for comparisons based on the edit outputs and multiple years of survey data. These reports and data are used to help isolate problems in specifications or processing. They include detailed information on imputation rates for all data items, as well as tallies representing counts of the number of times certain programmed logic checks were executed during editing. If editing problems are discovered in the data during this review process, it is often necessary to rerun the programs and repeat the review.

Once the subject matter analysts have approved data within the edited files, and their associated recodes, the files are ready to serve as inputs to the data products processing operation. If errors attributable to editing problems are detected during the creation of data products, it may be necessary to repeat the editing and review processes.

Median fire, hazard, and flood insurance divides the fire, hazard, and flood insurance distribution into two equal parts: one-half of the cases falling below the median fire, hazard, and flood insurance and one-half above the median. Median fire, hazard, and flood insurance is computed on the basis of a standard distribution (see the "Standard Distributions" section under "Derived Measures.") Median fire, hazard, and flood insurance is rounded to the nearest whole dollar. (For more information on medians, see "Derived Measures.")

The American Community Survey questions have been the same since 1996.

The data on vehicles available were obtained from Housing Question 12 in the 2006 American Community Survey. The question was asked at occupied housing units. These data show the number of passenger cars, vans, and pickup or panel trucks of one-ton capacity or less kept at home and available for the use of household members. Vehicles rented or leased for one month or more, company vehicles, and police and government vehicles are included if kept at home and used for non-business purposes. Dismantled or immobile vehicles are excluded. Vehicles kept at home but used only for business purposes also are excluded.

The 1996-1998 American Community Survey question provided a space for the respondent to enter the number of vehicles. Since 1999, the American Community Survey question provided pre-coded response categories.