INTRODUCTION
1 This publication contains final estimates for the computer and Internet use indicators collected in the 2003-04 Agricultural Survey. Some comparable data from the 2002-03 Agricultural Survey have also been included.
SCOPE AND COVERAGE
2 The estimates are based on information obtained from the Agricultural Survey for the year ended 30 June 2004. The scope of the 2003-04 Agricultural Survey was farms with an estimated value of agricultural operations (EVAO) of $5,000 or more. The sample for the 2003-04 Agricultural Survey included the same 28,000 units selected for the 2002-03 survey, plus a further 3,000 units to cover sample loss due to units in the original selection having ceased farming.
GEOGRAPHICAL, INDUSTRY AND SIZE CLASSIFICATIONS
3 The data contained in this publication have, where appropriate, been classified on a geographical, industry and farm size basis by classifying farms:
- to Statistical Divisions (SD) within states and territories as set out in the Australian Standard Geographical Classification (ASGC) (cat. no. 1216.0);
- to industry according to the methodology described in the Australian and New Zealand Standard Industry Classification (ANZSIC) (cat. no. 1292.0); and
- to EVAO ranges according to the estimated value of agricultural operations (or activity) undertaken by a farm. These are recalculated each year, so farms may move between EVAO size ranges.
SAMPLE ERROR
4 The estimates in this publication are based on information obtained from a sample drawn from the total farm population in scope of the collection. Because the entire population is not surveyed, the published estimates are subject to sampling variability and may differ from the figures that would have been produced if all farms had been included in the Agricultural Survey. The most common way of quantifying sampling error is to calculate the standard error (SE) for the published estimate or statistic. There are about two chances in three (67%) that the survey estimate is within one SE of the 'true' value of the estimate, and about nineteen chances in twenty (95%) that it is within two SEs. The 'true' value in this case is the result that would have been obtained if all farms were included in the survey.
5 In this publication, 'sampling' variability is measured by the relative standard error (RSE), which is obtained by expressing the SE as a percentage of the estimate. It is used to compare the accuracy between different estimates. Estimates with higher RSEs are considered less reliable those with lower RSEs.
6 Most estimates in this publication have RSEs of less than 5%. Estimates that have an estimated relative standard error between 10% and 25% are annotated with the symbol '^'. These estimates should be used with caution as they are subject to sampling variability too high for some purposes. Estimates with an RSE between 25% and 50% are annotated with a symbol '*', indicating that the estimate should be used with caution as it is subject to sampling variability too high for most practical purposes. Estimates with an RSE greater than 50% are annotated with a symbol '**', indicating that the sampling variability causes an estimate to be considered too unreliable for general use.
RELATIVE STANDARD ERRORS FOR SELECTED INDICATORS: 2003-04 |
| |
| | Farms using a computer | Farms using the internet | |
| |
State | | | |
| New South Wales | 2 | 2 | |
| Victoria | 2 | 3 | |
| Queensland | 2 | 3 | |
| South Australia | 2 | 2 | |
| Western Australia | 2 | 2 | |
| Tasmania | 3 | 4 | |
| Northern Territory | - | - | |
| Australian Capital Territory | - | - | |
| Australia | 1 | 1 | |
Industry | | | |
| Horticulture & fruit growing | 2 | 2 | |
| Grain, sheep and beef cattle farming | 1 | 2 | |
| Dairy cattle farming | 4 | 5 | |
| Poultry farming | 9 | 9 | |
| Other livestock | 7 | 8 | |
| Other crop growing | 5 | 5 | |
Farm size | | | |
| Less than $50,000 | 4 | 4 | |
| $50,000-$149,999 | 3 | 3 | |
| $150,000-$249,999 | 3 | 4 | |
| $250,000-$499,999 | 2 | 2 | |
| $500,000-$999,999 | 2 | 2 | |
| $1 million or more | 2 | 2 | |
| |
- nil or rounded to zero (including null cells) |
7 Note that the RSEs shown in this table may be considerably lower than the RSEs which result when these indicators are cross classified (eg. state by industry, industry by farm size, etc.) in tables of this publication.
8 Proportions formed from the ratio of two estimates are also subject to sampling error. The size of the error depends on the accuracy of both the numerator and the denominator. As a result, the RSE of the ratio may differ from the RSEs of the numerator and denominator.
ACKNOWLEDGEMENT
9 ABS publications draw extensively on information provided freely by individuals, businesses, governments and other organisations. Without their continued, and much appreciated, support the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.
RELATED PUBLICATIONS
10 Other recent ABS publications relating to the use and production of information technology and telecommunication goods and services in Australia include:
Business Use of Information Technology, Australia, 2003-04 (cat. no. 8129.0)
Government Technology, Australia, 2002-03 (cat. no. 8119.0)
Household Use of Information Technology, Australia, 2002 and 2003 (cat. no. 8146.0)
Information and Communication Technology, Australia, 2002-03 (cat. no. 8126.0)
Innovation in Australian Business, 2003 (cat. no. 8158.0)
Internet Activity, Australia, March quarter 2005 (cat. no. 8153.0)
Use of Information Technology on Farms, Australia, 2002-03 (cat. no. 8150.0)
ABS DATA AVAILABLE ON REQUEST
11 In addition to the statistics included in this and related publications, the ABS may have other relevant data available on request. Inquiries should be made to Nicholas Deverson, Perth, on (08) 9360 5323 or the National Information Referral Service on 1300 135 070.