RELIABILITY OF ESTIMATES
1 As the estimates in this publication are based on information relating to a sample of employers, they are subject to sampling variability. That is, they may differ from the estimates that would have been produced if the information had been obtained from all employers. This difference, called sampling error, should not be confused with inaccuracy that may occur because of imperfections in reporting by respondents or in processing by the ABS. Such inaccuracy is referred to as non-sampling error and may occur in any enumeration whether it be a full count or a sample. Efforts have been made to reduce non-sampling error by careful design of questionnaires, detailed checking of returns and quality control of processing.
2 The sampling error associated with any estimate can be estimated from the sample results. One measure of sampling error is given by the standard error which indicates the degree to which an estimate may vary from the value which would have been obtained from a full enumeration (the ‘true value’). There are about two chances in three that a sample estimate differs from the true value by less than one standard error, and about nineteen chances in twenty that the difference will be less than two standard errors.
3 An example of the use of a standard error is as follows. If the estimated average earnings was $500.00 with a standard error of $4.00, then there would be about two chances in three that a full enumeration would have given an estimate in the range $496.00 to $504.00 and about nineteen chances in twenty that it would be in the range $492.00 to $508.00.
4 An example of the use of a standard error for a quarterly change estimate is as follows. If the estimate of quarterly change between two quarters was $1.50 and the standard error on this estimate was $1.00, then there would be about two chances in three that a full enumeration would have given a quarterly change estimate in the range +$0.50 to +$2.50 and about nineteen chances in twenty that it would be in the range -$0.50 to +$3.50.
5 Quarterly movements in estimates of average weekly earnings are considered to be statistically significant where they exceed two standard errors.
SPECIAL DATA SERVICE
INTRODUCTION
As well as the statistics included in this publication, other data are available from the Survey of Average Weekly Earnings on request. These data can be produced for clients as customised reports. The variables are listed below.
HOW TO PLACE AN ORDER
Firstly, determine the variables (see following) that you require estimates for. A covering letter indicating these requirements and the intended uses of the data requested should be addressed to:
Labour Employer Surveys Section
Australian Bureau of Statistics
GPO Box K881
PERTH WA 6842
CONTACT OFFICER
If you wish to discuss individual requests, especially in regard to reliability of estimates for particular cross-classifications and the charges involved, please telephone Colin Fallows on Perth 08 9360 5304 .
VARIABLES
The following variables are available from this survey.
Note: The more variables included in any one tabulation the more likely it is that confidentiality provisions associated with the data will be invoked and some data suppressed.
| Type of estimate | Original |
 | Seasonally adjusted
Trend |
|
|
| Composition of earnings | Full-time adult ordinary time earnings |
| Full-time adult total earnings |
| All employees total earnings |
|
|
| States and Territories | New South Wales |
| Victoria |
| Queensland |
| South Australia |
| Western Australia |
| Tasmania |
| Northern Territory |
| Australian Capital Territory |
|
|
| Sector | Private sector |
| Public sector |
|
|
| Sex | Males |
| Females |
| Persons |
|
|
| Industry (ANZSIC classification) | ANZSIC Division (1-digit code)-as shown in table 10 |
| ANZSIC Sub-division (2-digit code) |
| ANZSIC Group (3-digit code) |
| ANZSIC Class (4-digit code) |
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