8109.0 - Research and Experimental Development, Government and Private Non-Profit Organisations, Australia, 2008-09 Quality Declaration 
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 15/07/2010   
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1 Non-sampling errors may arise as a result of errors in the reporting 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.

Reliability of Statistics

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 organisations provided estimates due to a lack of separately recorded data on R&D activity. This was most prevalent for government organisations without a specific research focus.
  • Data were self-classified by organisations to Field of research, Socio-economic objective and Type of activity, at the time of reporting. Some organisations 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 organisations and reference periods.


4 Revisions to previous cycle data occur on discovery of:
  • errors in previously reported data, typically a result of the specific non-sampling errors outlined in the Reliability of statistics section above; and
  • newly identified R&D performers who indicated they had significant levels of R&D in the previous cycle (details are collected and used to revise previously released estimates).

5 Revisions are only applied to previous cycle data 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.

6 In processing 2008-09 data, revisions were applied to 2006-07 estimates. Revisions were primarily the result of: provider reassessment of application of definitions and classifications; and newly identified R&D performers. The effect of revisions is most noticeable in component item data.

7 Users are advised to refer to the most recently released data cubes, as revisions must be taken into consideration when interpreting results, particularly when comparing estimates over time.