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 institutions provided estimates due to a lack of separately recorded data on R&D activity.
- Data were self-classified by institutions to fields of research (FOR), socio-economic objective (SEO) and type of activity at the time of reporting. Some institutions 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 institutions (See Explanatory Notes 12 and 13) and reference periods.
REVISIONS
4 Revisions to previous cycle data occur on discovery of errors in the data, typically a result of the specific non-sampling errors outlined in the Non-Sampling Error section above.
5 Revisions are applied one cycle prior to the current cycle, but only where the impact on:
- R&D expenditure is equal to $5 million or more; or
- Human resources devoted to R&D is equal to 25 PYE or more.
6 Where new information was identified, revisions were applied to 2010 estimates. Revisions must be taken into consideration when interpreting results, particularly when comparing estimates over time.