with youth who do not live in households with telephones.Sampling ErrorsThe sample of households with telephones selected for the NHES:93 is just one of many possible samples that could have been selected. Therefore, estimates produced from the NHES:93 sample may differ from estimates that would have been produced from other samples. This type of variability is called sampling error because it arises from using a sample of household with telephones, rather than all households with telephones./2/The standard error is a measure of the variability due to sampling when estimating a statistic; standard errors for estimates presented in this report were computed using a replication method known as "jackknife" replication (Wolter 1985). Standard errors can be used as a measure of the precision expected from a particular sample. The probability that a complete census count would differ from the sample estimate by less than 1 standard error is about 68 percent. The chance that the difference would be less than 1.65 standard errors is about 90 percent; and that the difference would be less than 1.96 standard errors, about 95 percent.Standard errors for all of the estimates are presented in the table. These standard errors can be used to produce confidence intervals. For example, an estimated 43.8 percent of students reported peer approval of drinking alcohol (rounded to 44 percent for this report). This figure has an estimated standard error of 0.8. Therefore, the estimated 95 percent confidence interval for this statistic is approximately 42.2 to 45.4 percent.The tests of significance used in this analysis are based on Student's t statistics. As the number of comparisons at the same significance level increases, it becomes more likely that at least one of the estimated differences will be significant merely by chance, that is, it will be erroneously identified as different from zero. Even when there is no statistical difference between the mean...
