The data on sex were derived from answers to Question 3. Individuals were asked to mark either "male" or "female" to indicate their biological sex. For most cases in which sex was invalid, the appropriate entry was determined from other information provided for that person, such as the person's given (i.e., first) name and household relationship. Otherwise, sex was allocated from a hot deck.

Sex is asked for all persons in a household or group quarters. On the mailout/mailback paper questionnaire for households, sex is asked for all persons listed on the form. This form accommodates asking sex for up to 12 people listed as living or residing in the household for at least 2 months. If a respondent indicates that more people are listed as part of the total persons living in the household than the form can accommodate, or if any person included on the form is missing sex, then the household is eligible for Failed Edit Follow-up (FEFU). During FEFU operations, telephone center staffers call respondents to obtain missing data. This includes asking sex for any person in the household missing sex information. In Computer Assisted Telephone Interviews (CATI) and Computer Assisted Personal Interview (CAPI) instruments sex is asked for all persons. In 2006, the ACS began collecting data in group quarters (GQs). This included asking sex for persons living in a group quarters. For additional data collection methodology, please see www.census.gov/acs.

Data on sex are used to determine the applicability of other questions for a particular individual and to classify other characteristics in tabulations. The sex data collected on the forms are aggregated and provide the number of males and females in the population. These data are needed to interpret most social and economic characteristics used to plan and analyze programs and policies. Data about sex are critical because so many federal programs must differentiate between males and females. The U.S. Departments of Education and Health and Human Services are required by statute to use these data to fund, implement, and evaluate various social and welfare programs, such as the Special Supplemental Food Program for Women, Infants, and Children (WIC) or the Low-Income Home Energy Assistance Program (LIHEAP). Laws to promote equal employment opportunity for women also require census data on sex. The U.S. Department of Veterans Affairs must use census data to develop its state projections of veteran's facilities and benefits. For more information on the use of sex data in Federal programs, please see www.census.gov/acs.

The data on work experience were derived from answers to Questions 38, 39, and 40. This term relates to work status in the past 12 months, weeks worked in the past 12 months, and usual hours worked per week worked in the past 12 months. To comply with provisions of the Civil Rights Act, the U.S. Department of Justice uses these data to determine the availability of individuals for work. Government agencies, in considering the programmatic and policy aspects of providing federal assistance to areas, have emphasized the requirements for reliable data to determine the employment resources available. Data about the number of weeks and hours worked last year are essential because these data allow the characterization of workers by full-time/part-time and full-year/part-year status. Data about working last year are also necessary for collecting accurate income data by defining the universe of persons who should have earnings as part of their total income.

Earnings are defined as the sum of wage or salary income and net income from self-employment. "Earnings" represent the amount of income received regularly for people 16 years old and over before deductions for personal income taxes, Social Security, bond purchases, union dues, Medicare deductions, etc. An individual with earnings is one who has either wage/salary income or self-employment income, or both. Respondents who "break even" in self-employment income and therefore have zero self-employment earnings also are considered "individuals with earnings."

People may have chosen to provide two or more races either by checking two or more race response check boxes, by providing multiple responses, or by some combination of check boxes and write-in responses. The race response categories shown on the questionnaire are collapsed into the five minimum races identified by the OMB, and the Census Bureau's "Some other race" category. For data product purposes, "Two or More Races" refers to combinations of two or more of the following race categories:

1. White

2. Black or African American

3. American Indian and Alaska Native

4. Asian

5. Native Hawaiian and Other Pacific Islander

6. Some other race

There are 57 possible combinations (see Appendix A) involving the race categories shown above. Thus, according to this approach, a response of "White" and "Asian" was tallied as two or more races, while a response of "Japanese" and "Chinese" was not because "Japanese" and "Chinese" are both Asian responses.

Given the many possible ways of displaying data on two or more races, data products will provide varying levels of detail. The most common presentation shows a single line indicating Two or more races. Some data products provide totals of all 57 possible race combinations, as well as subtotals of people reporting a specific number of races, such as people reporting two races, people reporting three races, and so on. In other presentations on race, data are shown for the total number of people who reported one of the six categories alone or in combination with one or more other race categories. For example, the category, "Asian alone or in combination with one or more other races" includes people who reported Asian alone and people who reported Asian in combination with White, Black or African American, Native Hawaiian and Other Pacific Islander, and/or Some other race. This number, therefore, represents the maximum number of people who reported as Asian in the question on race. When this data presentation is used, the individual race categories will add to more than the total population because people may be included in more than one category.