**TECHNICAL NOTE** SAMPLING VARIABILITY

**Estimation Procedure**

**1 **Estimates derived from this survey were obtained using a post-stratification procedure. This procedure ensured that the survey estimates conformed to an independently estimated distribution of the population, by the number of adults and children within the household, and part of state, rather than the distribution among respondents.

**Reliability of Estimates**

**2 **Estimates in this publication are subject to non-sampling and sampling errors.

**Non-sampling Errors**

**3 **Non-sampling errors may arise as a result of errors in the reporting, recording or processing of the data and can occur even if there is a complete enumeration of the population. Non-sampling errors 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.

**4 **It is difficult to measure the size of the non-sampling errors. The extent of these errors could vary considerably from survey to survey and from question to question. Every effort is made in the design of the survey and development of survey procedures to minimise the effect of these errors.

**Sampling Errors**

**5 **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**

**6 **One measure of the variability of estimates which occurs as a result of surveying only a sample of the population is the standard error (SE).

**7 **There are about two chances in three (67%) that a survey estimate is within one SE of the figure that would have been obtained if all households/persons had been included in the survey. There are about 19 chances in 20 (95%) that the estimate will lie within two SEs.

**8 **The SE can also be expressed as a percentage of the estimate. This is known as the relative standard error (RSE). The RSE is a measure of the error likely to have occurred due to sampling. The RSE is determined by dividing the SE of an estimate SE(x) by the estimate x and expressing it as a percentage. That is:

**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:

**12 **Where differences between data items have been noted in the Summary of Findings, they are statistically significant unless otherwise specified. In this publication a statistically significant difference is one where there are 19 chances in 20 that the difference noted reflects a true difference between population groups of interest rather than being the result of sampling variability.

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