TECHNICAL NOTE - STANDARD ERRORS
The estimates in this publication are based on information gained from the occupants of a sample survey of dwellings. Because the entire population is not surveyed, the published estimates are subject to sampling error. The most common way of quantifying such sampling error is to calculate the standard error for the published estimate or statistic. For more information, see the Reliability of Estimates section of the Explanatory Notes of publication Labour Force, Australia (cat. no. 6202.0).
To illustrate, let us say the published level estimate for couple families with children aged 0–4 years is 950,000 and the associated standard error is 15,000. The standard error is then used to interpret the level estimate of 950,000. For instance, the standard error of 15,000 indicates that:
- There are approximately two chances in three (66%) that the real value falls within the range 935,000 to 965,000 (950,000 + or - 15,000)
- There are approximately 19 chances in 20 (95%) that the real value falls within the range 920,000 to 980,000 (950,000 + or - 30,000).
The real value in this case is the result we would obtain if we could enumerate the total population.
The ABS considers that estimates with a relative standard error of 25% or more may be subject to sampling variability too high for most practical purposes.
To determine if an item has a relative standard error of 25% or more, in SuperTABLE, right click in the centre of the table, select annotate cells - standard annotations, and select 'Annotate RSE cut-off values'.
To indicate those cells in spreadsheets with a relative standard error of 25% or more, annotations have been applied.
Additional information on how standard errors for LFS person level estimates are produced is available in Labour Force Survey Standard Errors
(cat. no. 6298.0). A spreadsheet that calculates standard errors for annual family estimates is available in Labour Force Survey Standard Errors, Data Cube
(cat. no. 6298.0.55.001).