 Explanatory Notes, January 2004
 Explanatory Notes, February 2004
 Explanatory Notes, March 2004
 Explanatory Notes, April 2004
 Explanatory Notes, May 2004
 Explanatory Notes, June 2004
 Explanatory Notes, July 2004
 Explanatory Notes, August 2004
 Changes in this issue, August 2004
 Explanatory Notes, September 2004
 Explanatory Notes, October 2004
 Explanatory Notes, November 2004
 Explanatory Notes, December 2004
 Glossary
 Abbreviations
 Data Quality Issues (Appendix), January 2004
 Data Quality Issues (Appendix), February 2004
 Data Quality Issues (Appendix), March 2004
 Data Quality Issues (Appendix), April 2004
 Data Quality Issues (Appendix), May 2004
 Data Quality Issues (Appendix), June 2004
 Data Quality Issues (Appendix), July 2004
 Data Quality Issues (Appendix), August 2004
 Data Quality Issues (Appendix), September 2004
 Data Quality Issues (Appendix), October 2004
 Data Quality Issues (Appendix), November 2004
 Data Quality Issues (Appendix), December 2004
 Trend Revisions (Technical Note), January 2004
 Standard Errors (Technical Note), January 2004
 Standard Errors (Technical Note), February 2004
 Trend Revisions (Technical Note), February 2004
 Trend Revisions (Technical Note), March 2004
 Standard Errors (Technical Note), March 2004
 Trend Revisions (Technical Note), April 2004
 Standard Errors (Technical Note), April 2004
 Trend Revisions (Technical Note), May 2004
 Standard Errors (Technical Note), May 2004
 Trend Revisions (Technical Note), June 2004
 Standard Errors (Technical Note), June 2004
 Trend Revisions (Technical Note), July 2004
 Standard Errors (Technical Note), July 2004
 Trend Revisions (Technical Note), August 2004
 Standard Errors (Technical Note), August 2004
 Trend Revisions (Technical Note), September 2004
 Standard Errors (Technical Note), September 2004
 Trend Revisions (Technical Note), October 2004
 Standard Errors (Technical Note), October 2004
 Trend Revisions (Technical Note), November 2004
 Standard Errors (Technical Note), November 2004
 Trend Revisions (Technical Note), December 2004
 Standard Errors (Technical Note), December 2004
 Data Source

STANDARD ERRORS
RELIABILITY OF ESTIMATES
Estimates based on a sample are subject to sampling variability that is, they may differ from those that would be obtained from full enumeration.
The sampling error associated with any estimate can be estimated from the sample results and one measure so derived is the standard error. Given an estimate and the standard error on that estimate, there are about two chances in three that the sample estimate will differ by less than one standard error from the figure that would have been obtained from full enumeration, and about nineteen chances in twenty that the difference will be less than two standard errors. The relative standard error is the standard error on the estimate expressed as a percentage of the estimate.
It would be impractical to publish estimates of standard errors for all figures in individual tables. However, the following table of standard errors and relative standard errors gives an indication of the magnitude of the sampling error associated with any estimate of a particular size for shortterm and total movement.

APPROXIMATE STANDARD ERRORS ON ESTIMATES FOR STRATIFIED SAMPLE 
        
 SHORTTERM
DEPARTURE OR ARRIVAL
OF AUSTRALIAN RESIDENTS   SHORTTERM
ARRIVAL OR DEPARTURE
OF OVERSEAS VISITORS   TOTAL
ARRIVALS OR
DEPARTURES 

 
 

Estimated   Relative    Relative    Relative 
number of  Standard  standard   Standard  standard   Standard  standard 
movements  error  error   error  error   error  error 
        
 no.  %   no.  %   no.  % 

10,000  550  6   490  5   550  6 
5,000  450  9   330  7   410  8 
2,000  280  14   230  11   250  13 
1,000  200  20   150  15   170  17 
750  180  24   140  19   150  20 
500  130  26   110  22   125  25 
400  120  30   100  25   115  29 
300  110  36   84  28   97  32 
200  90  45   70  35   80  40 
100  63  63   49  49   56  56 

An example of the use of this table is as follows. If the estimate of the number of Australian resident departures for shortterm visits abroad is 500, then the standard error on this estimate is 130 i.e. there are two chances in three that the actual number of Australian resident departures for shortterm visits abroad will lie between 370 and 630 and nineteen chances in twenty that it will lie between 240 and 760.
The larger the size of an estimate the smaller the relative standard error. For any estimate of greater than 10,000 the relative standard error will be less than 6%.
The estimate of the difference between an estimate in two different periods or between different estimates from the same period is also subject to sampling error. The standard error on the difference between any two estimates which are subject to sampling error can be approximated by using the larger standard error of the estimates inflated by a factor of 1.4.
An example of the use of this procedure is as follows. Assume the estimates of the number of arrivals to Australia from Taiwan during January 2002 and January 2003 are 1,500 and 750 respectively. The difference between the 2002 and 2003 figures is 750 and the standard errors on these estimates are approximately 190 and 140. The standard error on the difference is approximately 266 (1.4 x 190), and there are nineteen chances in twenty that the estimate of the difference between the two years will lie between 218 and 1,282.
ESTIMATED NUMBER OF MOVEMENTS, GREATER THAN 10,000
Currently, standard errors are provided for estimates up to 10,000. The ABS is reviewing the Standard Error table with the view of providing standard errors for movements greater than 10,000. Standard errors should be considered when comparing movements in the levels of estimates for different time periods, or in comparing estimates of various characteristics.

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