Data Sources and Estimates

The data in this report were obtained from many different sources, including state education agencies, local schools, and colleges and universities using surveys and compilations of administrative records. Users of The Condition of Education should be cautious when comparing data from different sources. Differences in procedures, timing, question phrasing, interviewer training, and so forth can all affect the comparability of results across data sources.

Most indicators in The Condition of Education summarize data from surveys conducted by NCES or by the Census Bureau with support from NCES. Brief explanations of the major NCES surveys used in this website can be found in supplemental notes 3 and 4 of this volume. More detailed explanations can be obtained at the NCES website under “Surveys and Programs.” Information about the Current Population Survey (CPS), another frequent source of survey data used in The Condition of Education, can be obtained in supplemental note 2 as well as at http://www.census.gov/cps/.

Data for indicators are obtained primarily from two types of surveys: universe surveys and sample surveys. Some indicators report data taken from entire populations (universe surveys), such as indicator 37 (Public Elementary and Secondary Expenditures by District Poverty). With this type of survey, information is collected from every member of the population. For example, data for indicator 37 were obtained for each school district (approximately 17,000) in the United States. When data from an entire population are available, estimates of the total population or a subpopulation are made by simply summing the units in the population or subpopulation. A universe survey is usually expensive and time consuming, so researchers often opt to collect data from a sample of the population of interest (sample survey). Other indicators report data from such sample surveys, such as indicator 16 (Trends in the Achievement Gaps in Reading and Mathematics). Indicator 16 reports information from the National Assessment of Educational Progress (NAEP), which assesses a representative sample of students each year, rather than the entire population of students. When a sample survey is used, the statistical uncertainty introduced from having data from only a portion of the entire population must be considered in reporting estimates and making comparisons.

Various types of estimates are reported in The Condition of Education using universe and sample surveys. Many indicators report the size of a population or a subpopulation, and often the size of a subpopulation is expressed as a percentage of the total population. In addition, the average (or mean) values of some characteristic of the population or subpopulation may be reported. The average is obtained by summing the values for all members of the population and dividing the sum by the size of the population. An example is the annual average salaries of full-time instructional faculty at degree-granting institutions (indicator 42). Another population measure that is sometimes used is the median. The median is the value of a population characteristic at or above which 50 percent of the population is estimated to fall and at or below which 50 percent of the population is estimated to fall. An example is the median annual earnings of young adults who are full-time, full-year wage and salary workers (indicator 20).

Estimates based on universe and sample survey data may be affected by a wide range of potential data collection errors, such as coverage errors, response errors, data coding errors, and data entry errors. Estimates of the size of these types of errors are typically not available.

Using estimates calculated from data based on a sample of the population requires consideration of several factors before the estimates become meaningful. However conscientious an organization may be in collecting data from a sample of a population, some margin of error will always be present in estimations of the size of the actual total population or subpopulation because the data are available from only a portion of the total population. Consequently, data from samples can provide only an approximation of the true or actual value. The margin of error, or the range, of an estimate depends on several factors, such as the amount of variation in the responses, the size and representativeness of the sample, and the size of the subgroup for which the estimate is computed. The magnitude of this margin of error is measured by what statisticians call the “standard error” of an estimate.