Producers of statistics and data should explain clearly how they assure themselves that statistics and data are accurate, reliable, coherent and timely.
What you should commit to
Q3.1 Statistics should be produced to a level of quality that meets users’ needs. The strengths and limitations of the statistics and data should be considered in relation to different uses, and clearly explained alongside the statistics.
Q3.2 Quality assurance arrangements should be proportionate to the nature of the quality issues and the importance of the statistics in serving the public good. Statistics producers should be transparent about the quality assurance approach taken throughout the preparation of the statistics. The risk and impact of quality issues on statistics and data should be minimised to an acceptable level for the intended uses.
Q3.3 The quality of the statistics and data, including their accuracy and reliability, coherence and comparability, and timeliness and punctuality, should be monitored and reported regularly. Statistics should be validated through comparison with other relevant statistics and data sources. The extent and nature of any uncertainty in the estimates should be clearly explained.
Q3.4 Scheduled revisions, or unscheduled corrections that result from errors, should be explained alongside the statistics, being clear on the scale, nature, cause and impact.
Q3.5 Systematic and periodic reviews on the strengths and limitations in the data and methods should be undertaken. Statistics producers should be open in addressing the issues identified and be transparent about their decisions on whether to act.
Guidance and resources
|A guide that provides some questions that analysts producing statistics can use in considering quality at each stage of production. It is not a checklist but is designed to be used alongside your own organisation’s guidance, as well as alongside external resources.||Thinking about quality when producing statistics||OSR|
|Guidance on quality assuring administrative data used to create statistics. It includes explanatory notes, case examples, Frequently Asked Questions, the actual toolkit (audit questionnaire), and questions to prompt thinking when conducting the audit.||Quality Assurance of Administrative Data (QAAD)||OSR|
|Guidance on quality assuring management information (MI) – aggregate information collated during the normal course of business to inform operational delivery, policy development or the management of performance. It includes examples of the practices to use.||Quality Assurance of Management Information (QAMI)||OSR|
|This guidance supports statistics producers in meeting the quality requirements of the UK Code of Practice for Statistics and understanding of Eurostat’s European Statistics Code of Practice, which sets out five dimensions for measuring the quality of statistical outputs.||Quality statistics in government||GSS|
|This strategy aims to improve statistical quality across the Government Statistical Service (GSS) to produce statistics that serve the public good. It sets out what the GSS should be doing to improve the quality of its statistics and manage the processes surrounding their production.||GSS Quality Strategy||GSS|
|These case studies provide examples of successful improvements to the quality of GSS statistics.||GSS Quality Strategy case studies||GSS|
|A webpage with links to a series of guidance documents on harmonisation, including what harmonisation is and its aims, the Harmonisation Handbook and the GSS Harmonised Principles.||Harmonisation within the GSS webpage||GSS|
|Guidance that provides practical advice on how to communicate quality, uncertainty and change for different types of statistics and for a range of audiences.||Communicating quality, uncertainty and change||GSS|
|Guidance for producing quality analysis for government. It is used by the UK Government Policy Profession. For those within the Policy Profession, the Code of Practice for Statistics does not supercede the Aqua Book, but complements it.||The Aqua Book||UK Government|
|The Quality Assurance Framework of the European Statistical System (ESS) is a supporting document of the European Statistics Code of Practice. It contains recommendations on activities, methods and tools that facilitate the practical and effective implementation of quality.||ESS Quality Assurance Framework (PDF, 0.43MB)||Eurostat|
|The ESS Handbook for Quality Reports provides recommendations on how to prepare comprehensive quality reports for the full range of statistical processes and their output. It also provides detailed guidelines and examples of quality reporting practices.||ESS Handbook for Quality Reports (PDF, 3.06MB)||Eurostat|
|A template developed by the United Nations (UN) to help countries develop and implement national quality frameworks of their own, or to build on existing ones. The website includes a list of tools and resources.||UN Generic National Quality Assurance Framework (NQAF)||UN|
|The United Nations Economic Commission for Europe’s (UNECE) handbook for using administrative and secondary sources for official statistics provides international methodological guidelines to help those in the early stages of using administrative data.||Using Administrative and Secondary Sources for Official Statistics: A Handbook of Principles and Practices (2011)||UNECE|