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.

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2. 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

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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

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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

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