8129.0 - Business Use of Information Technology, 2004-05  
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 17/03/2006   
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TECHNICAL NOTE: DATA QUALITY


INTRODUCTION

1 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 non-sampling and sampling errors.



NON-SAMPLING ERRORS

2 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.


3 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.


4 The BUIT survey is dynamic in nature and the concepts measured are subject to evolution and refinement over time. This results in regular changes to questions used to measure the various attributes and features of IT use. The potential impacts of these changes on survey outputs are assessed during questionnaire testing and where these changes impact on data continuity, they are referred to in the publication commentary or Explanatory Notes.


5 The 2004-05 survey had a response rate of approximately 94%; this was above the target response rate.



SAMPLING ERROR

6 The difference between estimates obtained from a sample of businesses, and the estimates that would have been produced if the information had been obtained from all businesses, is called sampling error. The expected magnitude of the sampling error associated with any estimate can be estimated from the sample results. One measure of sampling error is given by the standard error (SE) which indicates the degree to which an estimate may vary from the value that would have been obtained from a full enumeration (the 'true' figure). There are about two chances in three that a sample estimate differs from the true value by less than one standard error, and about nineteen chances in twenty that the difference will be less than two standard errors.


7 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 to which it refers. The RSE is a useful measure in that it provides an immediate indication of the sampling error in percentage terms, and this avoids the need to refer also to the size of the estimate.


8 To illustrate, the estimated percentage of businesses with a web presence is 27% and the RSE is 3.3%, giving a standard error of 0.9 percentage points (3.3% of 27%). Therefore, there would be about two chances in three that, if all units had been included in the survey, a figure in the range of 26.1% to 27.9% would have been obtained, and 19 chances in 20 (i.e. a confidence interval of 95%) that the figure would have been within the range of 25.2% to 28.8%.


9 Most published estimates have RSEs less than 10%. Estimates that have a RSE 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 the symbol '*', indicating that the estimates should be used with caution as they are subject to sampling variability too high for most practical purposes. Estimates with an RSE greater than 50% are annotated with the symbol '**' indicating that the sampling variability causes the estimates to be considered too unreliable for general use.


10 The sampling variability for estimates at the state/territory or industry level is higher than that for Australian level aggregates. Within states/territories, the sampling variability, and therefore the RSEs of estimates for Tasmania, Northern Territory and the Australian Capital Territory are higher than for other states. Survey estimates for these states should therefore be viewed with more caution than those for other states.


11 Estimates of RSEs for the key indicators in this publication are shown in the following table:

RELATIVE STANDARD ERRORS OF BUSINESS USE OF TECHNOLOGIES, by selected business characteristics
Number of businesses
Businesses with computer use
Businesses with Internet use
Businesses with web presence
Businesses which placed orders via the Internet or web
Businesses which received orders via the Internet or web
%
%
%
%
%
%
Employment size
0-4 persons
1.5
1.0
1.5
6.1
4.4
8.3
5-19 persons
3.0
0.9
1.5
4.5
4.6
9.0
20-99 persons
6.2
1.7
2.6
5.9
7.4
11.2
100 or more persons
9.4
-
0.4
2.8
6.8
17.4
Total Income
Less than $100,000
3.9
2.1
3.3
12.3
9.0
19.1
$100,000 to less than $1m
1.8
0.9
1.3
5.1
4.1
7.8
$1m - $4.9m
4.3
1.0
1.6
5.1
5.8
10.1
$5m or more
6.3
-
0.9
5.0
6.1
12.6
Industry
Mining
2.3
2.1
2.6
7.7
8.7
22.9
Manufacturing
1.6
2.7
4.4
9.1
9.9
15.0
Electricity, gas and water supply
3.0
1.8
2.7
8.8
7.6
21.0
Construction
1.0
1.6
2.6
9.6
7.1
12.6
Wholesale trade
2.5
2.0
3.2
9.1
8.9
14.6
Retail trade
1.6
2.5
3.4
10.1
9.2
16.1
Accommodation, cafes and restaurants
1.8
3.1
4.3
8.1
10.0
12.3
Transport and storage
1.2
2.0
3.0
9.1
7.9
11.0
Communication services
1.3
1.8
3.2
8.2
6.4
11.9
Finance and insurance
3.4
1.1
1.9
7.7
6.2
16.0
Property and business services
2.1
1.5
2.2
8.4
6.9
15.2
Health and community services
0.9
1.2
2.3
8.5
5.7
21.8
Cultural and recreational services
2.4
1.6
2.8
7.9
8.9
15.7
Personal and other services
1.6
2.7
4.0
9.2
9.5
14.9
State
New South Wales
1.3
1.3
1.9
6.5
5.6
11.6
Victoria
1.2
1.4
2.3
6.6
6.2
11.7
Queensland
1.4
1.5
2.2
7.7
6.7
12.5
South Australia
1.3
1.4
2.2
6.9
6.5
11.1
Western Australia
1.3
1.7
2.7
7.6
7.7
12.8
Tasmania
7.3
2.8
3.9
15.0
11.4
19.7
Northern Territory
11.6
4.0
6.5
18.7
16.2
27.9
Australian Capital Territory
7.9
3.1
4.4
14.5
11.2
19.8
Region
Capital cities
1.4
0.8
1.2
3.8
3.5
6.5
Other areas
2.9
1.3
1.9
6.9
5.5
10.2
Total
0.6
0.7
1.0
3.3
2.9
5.5
- nil or rounded to zero (including null cells)