TECHNICAL NOTE DATA QUALITY
RELIABILITY OF THE ESTIMATES
1 When interpreting the results of a survey it is important to take into account factors that may affect the reliability of the estimates. Estimates provided in this release are subject to non-sampling and sampling errors.
2 Non-sampling errors may arise as a result of errors in the reporting, recording or processing of the data. These errors can be introduced through inadequacies in the questionnaire, treatment of non-response, inaccurate reporting by respondents, errors in the application of survey procedures, incorrect recording of answers and errors in data capture and processing.
3 The extent to which non-sampling error affects the results of the survey is difficult to measure. Every effort is 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.
4 The 2006-07 ICT industries survey had an initial sample size of 3,900 businesses. The final response rate was 94%.
5 The estimates presented in this release are based on information obtained from a sample of businesses in the surveyed population. Consequently, the estimates are subject to sampling variability, that is, they may differ from the figures that would have been obtained if all units had been included in the survey. 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 was taken. There are about two chances in three that a sample estimate will differ by less than one SE from the figure that would have been obtained if a census had been conducted, and approximately 19 chances in 20 that the difference will be less than two SEs.
6 In this release, sampling variability is measured by the relative standard error (RSE) which is obtained by expressing the SE as a percentage of the estimate to which it refers. The RSE is a useful measure in that it provides an immediate indication of the sampling error in percentage terms, and this avoids the need to refer also to the size of the estimate.
7 To illustrate, the estimated total income of all businesses classified to the Information media and telecommunications industry grouping is $40,208 million, the relative standard error (RSE) is 0.7%, giving a standard error of $281 million (0.7% of $40,208 million). Therefore, there would be two chances in three that, if all units had been included in the survey, a figure in the range of $39,927 million to $40,489 million would have been obtained, and 19 chances in 20 (i.e. a confidence interval of 95%) that the figure would have been within the range of $39,646 million to $40,770 million.
8 Estimates that have a RSE between 10% and 25% are annotated with the symbol '^'. These estimates should be used with caution as they are subject to sampling variability too high for some purposes. Estimates with an RSE between 25% and 50% are annotated with the symbol '*', indicating that the estimates should be used with caution as they are subject to sampling variability too high for most practical purposes. Estimates with an RSE greater than 50% are annotated with the symbol '**' indicating that the sampling variability causes the estimates to be considered too unreliable for general use.
9 Estimates of RSEs for the key indicators in this release are shown in the table below.
Summary of operations, by ICT industry grouping(a): relative standard errors
Information media and telecommunications
Computer system design and related services
Electronic and precision equipment repair and maintenance
Total ICT industry
|Wages and salaries |
|ICT income |
|Total income |
|Operating expenses |
|Operating profit before tax |
|Capital expenditure |
|Industry value added |
|(a) Refer to the Glossary for ANZSIC classes contributing to each industry grouping. |
This page last updated 3 October 2008