Sampling errors (RSE)

Only a small number of farms out of the total number of farms in a particular industry are surveyed. Despite the use of sample weights, estimates derived from these farms are likely to be different from those that would have been obtained if information had been collected from a census of all farms. These differences are called 'sampling errors'.

The size of the sampling errors is influenced by the number of farms in the sample, the variability of farms in the population and most importantly the design of the survey and the estimation procedures used. The more farms there are in the sample, the lower the sampling error is likely to be. So regional estimates are likely to have greater sampling errors than state estimates, and state estimates are likely to have greater sampling errors than national estimates.

To give a guide to the reliability of the survey estimates, standard errors are calculated and expressed as a percentage of the survey estimates. These are termed 'relative standard errors '. In general, the smaller the relative standard error, the more reliable the estimate. However, numerically small estimates tend to have large relative standard errors. To obtain the standard error from the relative standard error, multiply the relative standard error by the survey estimate and divide by 100.

For example, if the average total cash receipts are estimated to be $100 000 with a relative standard error of 6 per cent, the standard error for this estimate is $6 000.
There is roughly a two in three chance that the 'census value' (the value which would have been obtained if all farms in the target population had been surveyed) is within one standard error of the survey estimate. There is roughly a nineteen in twenty chance that the census value is within two standard errors of the survey estimates.

Thus, in the above example, there is an approximately two in three chance that the census value is between $94 000 and $106 000, and approximately a nineteen in twenty chance that the census value is between $88 000 and $112 000.

Non-Sampling Errors

The values obtained in a survey can also be affected by errors other than those relating directly to the sampling procedure. For example, it may not be possible to contact certain types of farms, respondents may provide inaccurate information on non-respondents may differ from respondents in a variable being surveyed.

ABARE's experience in conducting surveys of rural industries has resulted in procedures designed to minimise non-sampling errors. In addition, survey interviewers employed by ABARE undergo extensive training and generally have strong industry backgrounds.