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Quality as confidence in use
Statistical quality is often treated as a specialist concept, focused on matters such as accuracy, methods and data validity. These factors matter, but they are not enough on their own. Quality also depends on whether users are given a clear account of what the statistics show, what is uncertain, which conclusions are well supported, and which uses the evidence cannot support.
A fuller view of quality is broader than methodological correctness alone. It brings together organisational culture, professional judgement, effective quality assurance and clear communication with users. It also recognises that quality is not static; as data sources evolve, technologies change and user needs develop, producers must continue to question, review and improve their statistics.
The three Quality standards in the Code show how producers can put this broader view of quality into practice.
- Standard 5 Prioritise Quality focuses on the culture and conditions that support quality
- Standard 6 Be Rigorous focuses on the evidence, methods and assurance behind the statistics
- Standard 7 Be Open About Quality focuses on communicating strengths, limitations and uncertainty clearly
Together, the standards show that quality is a continuous and open process. They provide a practical way of responding to uncertainty: creating the right culture to recognise and challenge it, applying rigorous data and methods to understand and reduce it where possible, and being open with users about strengths, limitations and areas for improvement. Professional humility is central to this: acknowledging what the evidence can and cannot show, inviting scrutiny and avoiding claims that go beyond what the statistics can support.