TECHNICAL NOTE DATA QUALITY


NON-SAMPLING ERROR

1 Non-sampling errors may arise as a result of errors in the reporting, recording or processing of data. These errors can be introduced through inadequacies in the questionnaire, treatment of non-response, inaccurate reporting by data providers, errors in the application of survey procedures, incorrect recording of answers and errors in data capture and processing.

2 The extent to which non-sampling error affects the results is difficult to measure. Every effort is made to minimise non-sampling error by careful design and testing of the collection instrument, the use of efficient operating procedures and systems, and the use of appropriate methodologies.

3 When interpreting the statistics in this release, the reliability and comparability of the estimates may be affected by the following specific non-sampling errors:

• Many businesses provided estimates due to a lack of separately recorded data on R&D activity.
• Some businesses may not have reported data as per the definition of R&D used in this survey. This is potentially a result of slight differences in the survey definition of R&D and those used in industry R&D schemes for the allocation of grants, and the AusIndustry administered R&D Tax Concession scheme for tax deductibility for specific R&D activities.
• Data were self-classified by businesses to type of activity, fields of research and socio-economic objective at the time of reporting. Some businesses may have experienced difficulty in classifying their R&D projects. The ABS makes every effort to ensure correct and consistent interpretation and reporting of these data by applying consistent processing methodologies.
• The estimation method for R&D related overhead costs varied across businesses and reference periods.

SAMPLING ERROR

4 As the estimates in this publication are based on information relating to a sample of businesses, they are subject to sampling variability, that is, they may differ from the estimates that would have been produced if the information had been obtained from all businesses.

5 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. This should not be confused with inaccuracy that may occur because of imperfections in reporting by respondents or in processing by the ABS. Please see the section on Non-Sampling Error for more detail regarding these types of errors. 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.

6 An example of the use of a standard error is as follows. From the publication, the estimated total expenditure on R&D was $18,321,322, with a standard error of $333,448. There would be about two chances in three that a full enumeration would have given an estimate in the range $17,987,874 to $18,654,770 and about nineteen chances in twenty that it would be in the range $17,654,426 to $18,988,218.

7 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 to the size of the estimate. RSEs are obtained using the formula: RSE = SE/estimate x 100. RSEs are shown in the Relative Standard Error tables in this section. RSEs for all data included in this release (including data cube content) are available upon request.

8 Estimates with RSEs between 25% and 50% are annotated to indicate they are subject to high sample variability and should be used with caution. In addition, estimates with RSEs greater than 50% have been included and annotated to indicate they are considered too unreliable for general use. In the publication, the symbol '*' indicates an estimate has an RSE of between 25% and 50%, and estimates with the symbol '**' have an RSE greater than 50%. All cells in the data cubes with RSEs greater than 25% contain a comment indicating the size of the RSE. These cells can be identified by a red indicator in the corner of the cell. The comment appears when the mouse pointer hovers over the cell.

RELATIVE STANDARD ERROR, Business expenditure on R&D - Summary statistics, 2011 - 12
			2011-12
			%
Employment size
	0 - 4 persons		6.78
	5 - 19 persons		3.51
	20 - 199 persons		3.49
	200 or more persons		2.30
Type of expenditure
	Capital expenditure
		Land, buildings and other structures	4.14
		Other capital expenditure	5.44
		Total capital expenditure	4.68
	Current expenditure
		Labour costs	2.83
		Other current expenditure	1.28
		Total current expenditure	1.79
Source of funds
	Own funds		1.90
	Other business		4.52
	Commonwealth government		3.74
	State and local government		3.16
	Other Australian(a)		4.97
	Overseas		11.90
Location of expenditure(b)
	New South Wales		3.64
	Victoria		1.20
	Queensland		1.79
	South Australia		3.45
	Western Australia		3.63
	Tasmania		6.84
	Northern Territory		5.58
	Australian Capital Territory		11.96
	Overseas		5.46
Type of activity
	Pure basic research		4.15
	Strategic basic research		2.18
	Applied research		2.29
	Experimental development		2.30
Total expenditure on R&D			1.82
(a) Includes funding from Joint business/government, Higher education and Private non-profit organisations.
(b) For the definition of location, see Explanatory Note 26.

RELATIVE STANDARD ERROR, Business expenditure on R&D - by industry, 2011 - 12
	2011-12
	%
Agriculture, Forestry and Fishing	2.19
Mining	3.34
Manufacturing	0.91
Electricity, Gas, Water and Waste Services	0.21
Construction	2.22
Wholesale Trade	3.17
Retail Trade	3.98
Accommodation and Food Services	-
Transport, Postal and Warehousing	1.02
Information Media and Telecommunications	2.41
Financial and Insurance Services	8.87
Rental, Hiring and Real Estate Services	4.39
Professional, Scientific and Technical Services	1.84
Administrative and Support Services	1.55
Public Administration and Safety	0.99
Education and Training	-
Health Care and Social Assistance	1.27
Arts and Recreation Services	9.13
Other Services	4.02
Total	1.82
- nil or rounded to zero (including null cells)

COMPARABILITY OF ESTIMATES OVER TIME

9 The comparability of estimates over time may be affected by the following changes in classifications:

• Employment size classification groups are defined on data reported in the reference period, and as such businesses may be categorised to different employment size groups across different reference periods.
• Businesses can also be classified to different industry divisions across survey reference periods as a consequence of structural change. See paragraphs 23 and 24 of the Explanatory Notes for more information.

REVISIONS

10 Revisions to previous cycle data occur on discovery of:

• errors in reported data, typically a result of the specific non-sampling errors outlined in the Non-Sampling Error section above; and
• newly identified R&D performers who indicated they had significant levels of R&D in earlier years (details are collected and used to revise previously released estimates).

11 Revisions are applied up to two cycles prior to the current cycle, but only where the impact on:

• R&D expenditure is equal to $5 million or more;
• Human resources devoted to R&D is equal to 25 PYE or more; or
• Published level data is of proportional significance.

12 In processing 2011-12 data, revisions were applied to 2009-10 and 2010-11 estimates. Revisions must be taken into consideration when interpreting results, particularly when comparing estimates over time.