TECHNICAL NOTE DATA QUALITY
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.
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).
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.
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.
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.
This page last updated 15 July 2010