TECHNICAL NOTE
SAMPLING VARIABILITY
Estimation Procedure
1 The estimates in this publication were obtained using a post-stratification procedure. This procedure ensured that the survey estimates conformed to an independently estimated distribution of the population, by state, part of state, age, sex and labour force status, rather than the distribution among respondents.
Reliability of Estimates
2 When interpreting the results of a survey it is important to take into account factors that may affect the reliability of estimates. Such factors can be classified as either sampling or non-sampling error.
Non-sampling Errors
3 Errors other than those due to sampling may occur in any type of collection and are referred to as non-sampling error. For this survey, non-sampling error can be introduced through inadequacies in the questionnaire, non-response, inaccurate reporting by respondents, errors in the application of survey procedures, incorrect recording of answers and errors in data entry and processing. The extent to which non-sampling error affects the results of the survey is not precisely quantifiable. Every effort was made to minimise non-sampling error by careful design and testing of the questionnaire, efficient operating procedures and systems and the use of appropriate methodology.
Sampling Errors
4 Sampling error is the error which occurs by chance because the data were obtained from a sample, rather than from the entire population.
Estimates of Sampling Error
5 One measure of the likely difference is given by the standard error (SE), which indicates the extent to which an estimate might have varied by chance because only a sample of persons was surveyed.
6 There are about two chances in three (67%) that a sample estimate will differ by less than one SE from the figure that would have been obtained if all persons had been included in the survey and approximately 19 chances in 20 (95%) that the difference will be less than two SEs.
7 Sampling variability can also be measured by the relative standard error (RSE) which is obtained by expressing the SE as a percentage of the estimate to which it refers, that is:
8 The RSE is a useful measure in that it provides an immediate indication of the sampling error in percentage terms.
9 The RSEs of all of the estimates are available in the attached spreadsheet of publication tables.
10 In this publication, only estimates with RSEs of 25% or less are considered reliable for most purposes. Estimates with RSEs greater than 25% but less than or equal to 50% have a notation to indicate they are subject to high SEs and should be used with caution. Estimates with RSEs of greater than 50%, indicated by a notation, are considered too unreliable for general use and should only be used to aggregate with other estimates to provide derived estimates with RSEs of 25% or less.
11 Proportions and percentages formed from the ratio of two estimates are also subject to sampling error. The size of the error depends on the accuracy of both the numerator and the denominator. The formula for the RSE of a proportion or percentage is:
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