6291.0.55.001 - Labour Force, Australia, Detailed - Electronic Delivery, Monthly, Jan 2007  
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 15/02/2007   
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Classifications

SexMale, Female
Age15-19, 20-24, 25-34, 35-44, 45-54, 55-59, 60-64, 65+
Geographical AreaState
Looking for work/availability to start workWhether actively looking for work, whether available to start work in next four weeks, whether looking for work, permanently not intending to work, permanently unable to work
MonthAll months from April 2001
Standard Errors
Estimates from the Labour Force Survey (LFS) are based on information collected from people in a sample of dwellings, rather than the entire population. Hence the estimates produced may differ from those that would have been produced if the entire population had been included in the survey. The most common measure of the likely difference (or 'sampling error') is the standard error (SE).New models for calculating standard errors for these estimates were introduced in August 2005 and apply to estimates from the LFS from November 2002 onwards.

The estimates in this data file are from a sample survey and some estimates may be subject to sampling variability too high for most practical purposes. To annotate an item with 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'. See the SuperTABLE reference manual for more information (available from Space-Time Research - see link above).

Additional information on how standard errors for LFS estimates are produced is available in the paper Labour Force Survey Standard Errors, 2005
StandardErrors.xls



Explanatory Information
Explanatory Information about the Labour Force Survey and associated products, including a glossary of terms used and links to related publications, can be found at Explanatory Notes from 6202.0 (cat. no. 6298.0). The attached document (free download) also provides the tables to allow the annotation of historical estimates with a standard error of 25% or more.