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Sampling errors occur because inferences about the survey population are based on data from a sample of that population rather than the entire population. The sample design, the variability of the characteristic being measured, and the sample size will all contribute to the magnitude of the sampling error.
The standard error is a common measure of sampling error. The standard error measures the degree of variation introduced in estimates by selecting one particular sample rather than another of the same size and design. Another widely used measure of the sampling error is the coefficient of variation (CV), which is the estimated standard error expressed as a percentage of the estimate.
In SLID, the bootstrap approach is used for the calculation of standard errors. This is a resampling method of variance estimation, often used when dealing with estimates from a complex sample design. Table 3.1 shows CV levels at the provincial and national level for a sample of key SLID estimates.
Table 3.1 National and provincial coefficients of variation (%), 2006
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