What's It Worth? Educational Background And Economic StatusDIANE Publishing, 1993 - 75 pages Shows that education pays off; the more education adults received, the bigger their paychecks were. Examines the relationship between educational level and earnings; also looks at earnings based on post-secondary degree field, the amount of time it takes to earn degrees, work-related training, and occupations associated with educational background. |
Common terms and phrases
0.02 Doctorate advanced degree holders Agriculture/Forestry associate or vocational average monthly earnings Biology Blacks Business/Management Economics Census characteristics completed high school computed confidence interval Consumer Price Index Degree and Field degree beyond high degree levels degrees held Economic Status educational attainment Engineering English/Journalism error Total Female Field of Degree field of study high school diploma High school graduate highest degree Hispanic Origin Home Economics household hypothesis test interview month Liberal Arts/Humanities Male Mean error Mean monthly income noninterviews nonresponse nonsampling error number of persons Numbers in thousands Nursing/Pharmacy/Technical Health original sample persons parameters Persons 18 Persons of Hispanic Physical/Earth Sciences Police Science/Law Enforcement possible samples Post-Secondary Degrees professional degrees professional specialty Psychology race received training reference period Religion/Theology respondents sexes SIPP estimates SIPP sample Social Sciences table C-2 tion topical modules Training History Vo-tech Studies vocational degree Whites women work-related training X1 Don't know
Popular passages
Page 2 - Data reliability The data in this bulletin are estimates from a scientifically selected probability sample. There are two types of errors possible in an estimate based on a sample survey, sampling and nonsampling. Sampling errors occur because observations come only from a sample and not from an entire population. The sample used for this survey is one of a number of possible samples of the same size that could have been selected using the sample design. Estimates derived from the...
Page 2 - Nonsampling variability. Nonsampling errors can be attributed to many sources, eg, inability to obtain information about all cases in the sample, definitional difficulties, differences in the interpretation of questions, inability or unwillingness...
Page 3 - D are approximations to the standard errors of various estimates shown in this report. In order to derive standard errors that would be applicable to a wide variety of items and could be prepared at a moderate cost, a number of approximations were required. As a result, the tables of standard errors provide an indication of the order of magnitude of the standard errors rather than the precise standard error for any specific item.
Page 2 - Since the estimates are based on a sample, they may differ somewhat from the figures that would have been obtained if a complete census had been taken using the same schedules, instructions and enumerators.