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8158.0 - Innovation in Australian Business, 2005  
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 07/12/2006   
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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 There continues to be problems with the collection of innovation specific financial items (income from sales of new goods or services and expenditure on innovative activity). Businesses do not generally keep their records on a basis that allows for easy extraction of these data, therefore, they generally report estimates only. Furthermore, businesses could report either dollars or percentages for these items.


5 The Innovation survey is dynamic in nature and the concepts measured are subject to evolution and refinement over time. As noted in the Appendix, improvements have been made to the questionnaire and survey procedures, however it is not possible to measure the impact of all of these changes on data quality.


6 The 2005 Innovation Survey had a response rate of approximately 93%; this was above the target response rate and substantially higher than the response rate of 82% achieved for the 2003 Innovation Survey.



SAMPLING ERROR

7 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.


8 .An example of the use of standard error on the total proportion of innovating businesses is as follows. From Table 1.1, the estimated proportion of total innovation-active businesses was 34.9%. The standard error of this estimate was 1.3%. There would be about two chances in three that a full enumeration would have given a figure in the range 33.6% to 36.2%, and about nineteen chances in twenty that it would be in the ranges 32.3% to 37.5%. Detailed standard errors are available on request.


9 In this publication, indications of sampling variability are measured by relative standard errors (RSEs). The relative standard error is a useful measure in that it provides an immediate indication of the percentage errors likely to have occurred due to sampling, and thus avoids the need to refer also to the size of the estimate. Relative standard errors are shown in the Relative Standard Error table in this section.


10 To annotate proportion estimates a value of 50% has been used in the calculation of RSE rather than the estimated proportion from the survey data. This avoids inconsistencies between the way very low and very high proportions are annotated. Relative standard errors for estimates in this publication have been calculated using the actual standard error and the survey estimate (referred to as x) in the following manner:

      RSE%(x) = (SE(x)*100)/50

11 Using the previous example, the standard error for the estimated proportion of total innovation-active businesses was 1.3%. Multiplied by 100 and then divided by 50 gives an RSE calculated on this basis of 2.6%. It is these figures that appear in the table appended to this chapter.


12 For the tables in this publication, estimates with RSEs 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 RSEs 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.


13 For estimates of proportion the symbol '^' means that the estimate from full enumeration could lie more than a decile away so the estimate should be used with caution. For example a proportion estimate of 30% annotated with '^' means the full enumeration value could lie beyond the range 20% to 40%. The symbol '*' means the estimate from full enumeration could lie more than a quartile away and is subject to sampling variability too high for most practical purposes. A proportion estimate of 30% annotated with '*' means the full enumeration value could lie beyond the range 5% to 55%. Proportion estimates annotated with the symbol '**' have a sampling error that causes the estimates to be considered too unreliable for general use.

Relative Standard Errors, 2004 and 2005(a), by innovation type(b)

Businesses which introduced or implemented
Total number of businesses at 31 December 2005
Any new or significantly improved
goods or
services
Any new or
significantly
improved
operational
processes
Any new or
significantly
improved
organisational/
managerial
processes
Any new
goods,
services or processes
Proportion of
businesses which
started but did
not yet complete
or abandoned any
innovative activity
Proportion
of businesses
innovating
%
%
%
%
%
%
%

Employment size
5-19 persons
1.6
2.3
2.3
2.5
3.2
2.0
3.3
20-99 persons
4.7
5.1
5.2
5.0
5.4
4.2
5.4
100 or more persons
8.8
6.5
7.5
9.2
9.2
4.9
8.6
Income size
Less than $1m
3.0
3.3
3.4
3.5
4.3
2.9
4.3
$1m-Less than $5m
3.4
3.7
3.4
4.0
4.3
2.8
4.5
$5m or more
4.6
4.6
4.9
5.4
5.4
3.2
5.2
State/territory
New South Wales
1.0
4.0
3.5
4.0
4.8
3.0
4.9
Victoria
1.5
3.7
3.8
4.7
4.9
3.5
4.9
Queensland
0.9
4.6
4.9
5.5
6.0
2.7
6.0
South Australia
2.1
8.3
10.4
11.4
11.5
10.2
11.4
Western Australia
1.7
8.6
8.1
9.4
9.4
6.4
9.4
Tasmania
4.0
14.5
11.2
12.0
17.0
9.3
17.1
Northern Territory
4.5
11.4
16.8
18.1
18.8
3.8
18.7
Australian Capital Territory
0.7
9.9
10.0
12.5
11.2
5.5
11.2
Region
Capital cities
2.1
2.5
2.4
2.3
2.9
2.2
3.0
Other areas
4.9
4.2
4.2
4.5
4.9
3.1
5.1
Industry
Mining
2.1
6.1
6.6
8.6
9.3
6.5
9.5
Manufacturing
0.7
2.3
2.7
2.4
2.8
2.5
2.9
Electricity, gas and water
2.4
7.1
5.6
6.7
7.4
7.0
8.2
Construction
1.5
5.3
6.7
6.7
7.5
4.3
7.5
Wholesale trade
2.0
7.2
6.6
8.2
8.7
5.7
8.3
Retail trade
1.8
6.2
6.0
6.5
8.1
3.9
8.3
Accommodation, cafes and restaurants
1.8
6.7
7.0
6.7
7.1
4.9
7.1
Transport and storage
2.1
5.7
6.3
6.8
7.3
4.4
7.3
Communication services
1.5
7.1
5.9
7.2
7.3
5.9
7.1
Finance and insurance
4.4
4.8
5.4
6.3
6.6
4.4
6.6
Property and business services
1.2
4.4
4.7
5.4
5.6
3.9
5.5
Cultural and recreational services
2.0
5.3
6.0
6.6
6.9
6.0
7.3
Total
0.6
2.0
2.0
2.2
2.6
1.7
2.6

(a) Calendar years.
(b) Calculated using methodology described in paragraphs 9-13 in this chapter.


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