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 publication are subject to non-sampling and sampling errors.
NON-SAMPLING ERRORS
2 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. 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 Where government organisations provided consolidated returns for more than one agency, additional effort was made to ensure that coverage was complete.
5 The overall response rate for units selected in the 2002-03 GTS was 99%.
STANDARD ERRORS
6 The estimates presented in this publication are based on information obtained from a total of 1,418 government units. This total was comprised of a census of 111 federal, 474 state/territory government and 76 vocational education reporting units. 249 local government, 8 tertiary and 500 school education units were sampled from a possible total population of 7,787.
7 Due to the sampled component of the survey, 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.
8 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.
9 In this publication, 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.
10 Most published estimates have RSEs less than 10%. 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.
11 Estimates of RSEs for the key indicators in this publication are shown in the following table:
RELATIVE STANDARD ERRORS
|
 | Total ICT employees as at 30 June | Wages and salaries of ICT employees | Total selected ICT operating expenses (a) | Total selected ICT capital expenditure |
|
| % | % | % | % |
|
| | | | |
| Federal (b) | 3.6 | 3.5 | 2.0 | 1.8 |
| State/Territory (c) | 0.7 | 0.5 | 0.6 | 1.1 |
| Local | 4.0 | 3.9 | 3.3 | 6.8 |
| | | | |
| Total | 1.8 | 1.8 | 1.0 | 1.1 |
| | | | |
|
(a) Includes wages and salaries, ICT hardware, computer software, telecommunications services, payments to contractors.
(b) Includes tertiary education.
(c) Includes vocational and school education.
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