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8150.0 - Use of Information Technology on Farms, Australia, 2004-05  
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 22/08/2006   
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EXPLANATORY NOTES


INTRODUCTION

1 This publication contains final estimates for the computer and Internet use indicators collected in the 2004-05 Agricultural Survey. Some comparable data from the 2003-04 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 2005. The scope of the 2004-05 Agricultural Survey was farms with an estimated value of agricultural operations (EVAO) of $5,000 or more. The sample for the 2004-05 Agricultural Survey included the same 30,500 units selected for the 2003-04 survey, which represents 23% of all farms.



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.


SAMPLING AND NON-SAMPLING ERRORS

4 When interpreting the results of a survey it is important to take into account factors that may affect the reliability of the estimates. Estimates in this publication are subject to both sampling and non-sampling errors.


SAMPLING ERROR

5 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.


6 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.


7 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 - 2004-05

Farms using
a computer
Farms using
the internet
%
%

State
New South Wales
2
2
Victoria
2
3
Queensland
2
2
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
1
Dairy cattle farming
4
4
Poultry farming
4
7
Other livestock
7
8
Other crop growing
4
4
Farm size
Less than $50,000
4
4
$50,000-$149,999
3
3
$150,000-$249,999
3
3
$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)


8 Note that the RSEs shown in this table may be considerably lower than the RSEs which result when these indicators are cross classified (e.g. state by industry, industry by farm size, etc.) in tables of this publication.


9 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.


NON-SAMPLING ERRORS

10 Non-sampling errors may arise as a result of errors in the reporting, recording or processing of the data and can occur even if there is a complete enumeration of the population. These errors can be introduced through inadequacies in the questionnaire, treatment of non-response, inaccurate reporting by respondents, errors in the application of survey procedures, incorrect recording of answers and errors in data capture and processing.


11 The extent to which non-sampling error affects the results of the survey is difficult to measure. Every effort is made to reduce non-sampling error by careful design and testing of the questionnaire, efficient operating procedures and systems, and the use of appropriate methodology.


12 In the 2004-05 Agricultural Survey, 5,597 (4%) farms reported using the Internet during 2004-05 but were unable to specify the type of connection at 30 June 2005. There has been no attempt to impute connection type for these farms in tables showing detailed breakup.



ACKNOWLEDGEMENT

13 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

14 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, 2004-05 (cat. no. 8129.0)
      Government Technology, Australia, 2002-03 (cat. no. 8119.0)
      Household Use of Information Technology, Australia, 2004 and 2005 (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, 2003-04 (cat. no. 8150.0)


ABS DATA AVAILABLE ON REQUEST

15 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 Tim Landrigan, Perth, on (08) 9360 5104 or the National Information Referral Service on 1300 135 070.

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