1. How to interpret experimental statistics
Experimental statistics are official statistics that are in the testing phase and not yet fully developed.
Users should be aware that experimental statistics will potentially have a wider degree of uncertainty. The limitations of the statistics will be clearly explained within the release.
Back to table of contents2. Labelling experimental statistics
The experimental statistics label is typically used where:
the statistics remain subject to testing of quality, volatility and ability to meet user needs
new methods are being tested and are still subject to modification or further evaluation
there is partial coverage (for example, of subgroups, regions or industries) at that stage of the development
there may be potential modification following user feedback about their usefulness and credibility
3. Why we publish experimental statistics
The reasons include:
consultation - experimental statistics are published to involve potential users and stakeholders at an early stage in assessing their quality and suitability
acclimatisation - where the experimental statistics are alternative versions of existing official statistics, it can help users become familiar with and understand the impact of new methods and approaches
use - experimental statistics can provide useful information for users as long as their nature is well-explained and understood
4. Experimental statistics evaluation
Once the evaluation of the experimental statistics is completed the label may be removed and the statistics can be published as official statistics. This decision will consider factors such as:
when it is judged that statistical methods used are robust
when coverage reaches a good level
when user feedback indicates that these statistics are useful and credible
when the defined development phase has ended