Quality
Data and methods that produce assured statistics
Quality is about using suitable data and appropriate methods to produce reliable statistics that meet the needs of the people who use them. Statistics should inform rather than mislead, and producers must uphold high standards of transparency and quality assurance.
To ensure the statistics are of suitable quality:
5. Prioritise quality
- Do promote and take a proactive approach to quality and continuous improvement, learning constructively from both mistakes and good practice
- Don’t discourage innovation or collaboration or dismiss quality issues raised by staff, data suppliers, partners, topic experts or users
6. Be rigorous
- Do use suitable data sources and sound methods to meet intended uses, applying recognised professional standards
- Don’t assume data are suitable or ignore quality issues or the implications of system and method changes on their continued suitability
7. Be open about quality
- Do describe clearly the quality of data and statistics, including uncertainty and bias in estimates and impacts on appropriate interpretation and use
- Don’t assume quality remains static or fail to communicate key quality or methods information that could result in a misleading interpretation or wrong decision
Showing the quality of your work
An organisation publishing data or analysis should ensure the public can have confidence in the quality of its data and methods.
An organisation can show the Quality principle is achieved by considering and describing how it sources and selects data, how it chooses and tests methodology, how it assures itself about the quality of the data and methods and by informing users about the quality and/or limitations of its statistics and analysis.
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