TECHNICAL NOTE 2 DATA RELIABILITY
ABS SURVEY DATA
1 For 2003-04 the mining collection was, in part, a sample survey designed primarily to deliver industry subdivision and selected class estimates for Australia. Industry division estimates (excluding Subdivision 15 SERVICES TO MINING) for states and territories for key data variables are also produced, but the survey was not specifically designed for these purposes.
Sample error
2 The majority of data in Chapters 1 to 3 of this publication have been obtained from a sample of mining businesses. As such, these data are subject to sampling variability; that is, they may differ from the figures that would have been produced if the data had been obtained from all mining businesses in the population. The measure of the likely difference as used by the ABS is given by the standard error, which indicates the extent to which an estimate might have varied by chance because the data were obtained from only a sample of units. There are about two chances in three that a sample estimate will differ by less than one standard error from the figure that would have been obtained if the data had been obtained from all units, and about 19 chances in 20 that the difference will be less than two standard errors.
3 The standard error can also be expressed as a percentage of the estimate, and this is known as the relative standard error (RSE). The relative standard errors of the Australian estimates of employment, sales and service income, wages and salaries, and IVA presented in this publication are mainly less than 5% for industry subdivisions (see Technical Note 3) and all are less than 4% for the industry classes shown. The relative standard errors of the selected estimates for the states and territories are mainly 5% or less.
4 Relative standard errors at the industry subdivision and selected class level for Australia for selected data items representing the full range of data contained in this publication are shown in Technical Note 3. Detailed relative standard errors can be made available on request.
5 The size of the RSE may be a misleading indicator of the reliability of some of the estimates for trading profit, OPBT, EBIT and IVA. Estimates of these variables may legitimately include positive and negative values, reflecting the financial performance of individual businesses. In these cases the aggregated estimate can be small relative to the contribution of individual businesses, resulting in a standard error which is large relative to the estimate.
Non-sample error
6 The imprecision due to sampling variability, which is measured by the standard error, should not be confused with inaccuracies that may occur because of inadequacies in available sources from which the population frame was compiled, imperfections in reporting by providers, errors made in collection such as in recording and coding data, and errors made in processing data. Inaccuracies of this kind are referred to collectively as non-sampling error and they may occur in any enumeration, whether a full census or a sample.
7 Although it is not possible to quantify non-sampling error, every effort is made to reduce it to a minimum. Collection forms are designed to be easy to complete and assist businesses to report accurately. Efficient and effective operating procedures and systems are used to compile the statistics. The ABS compares data from different ABS (and non-ABS) sources relating to the one industry, to ensure consistency and coherence.
8 There are also non-sampling errors associated with the BIT data sourced from the ATO. For example, the ATO treats any non-response by either bringing forward the previous year's data for a non-responding business, or imputing the data as zero if there are no previous data to use.
NON-ABS DATA
9 The mineral production data shown in Chapter 4 are mainly compiled from data produced by the state and Northern Territory departments responsible. For information about the comparability of these data, please see the introduction to that chapter.
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