Everyone can apply or draw on the Code of Practice for Statistics. It can help anyone using data and producing statistics to work in a way that allows others to have confidence in their commitment to delivering the best possible outputs.
The Code is based on three core principles, Trustworthiness, Quality and Value (TQV), with ten underpinning principles.
Adhering to these Code Principles helps show you are trustworthy and that your data and statistics are of appropriate quality and valuable:
Trustworthiness is when users can have confidence in the people and organisations that produce statistics and data
- Principle 1: Show integrity
- Principle 2: Lead responsibly
- Principle 3: Be transparent
- Principle 4: Manage data responsibly
Quality is when users can have confidence that the data and methods produce assured statistics
- Principle 5: Prioritise quality
- Principle 6: Be rigorous
- Principle 7: Be open about quality
Value is when users can have confidence that published statistics support society’s needs for information
- Principle 8: Be relevant
- Principle 9: Be clear
- Principle 10: Be accessible
Check out the Code Principles to see relevant dos and don’ts, aligned to each principle, when working data and statistics.
Why not join the TQV Voluntary Application Scheme? Our community of practice is open to anyone interested in applying the Code Principles. Find out more in our introduction to Voluntary Application.
Questions to consider when putting the Code Principles into practice
1. Impartiality and transparency
How can you demonstrate objectivity and impartiality? (principle 1) In what ways can you be transparent about your plans and work? (principle 3) For example, do you provide reasonable advance notice of release? Have you established a publication timetable? (principle 3)
2. Organisational matters
How can you enhance your organisational arrangements to ensure you work in trustworthy ways? (principle 2) In what ways do your data handling and security arrangements meet common data standards and legal requirements? (principle 4)
3. Understanding quality
What is the quality of your data/outputs and how robust are your methods and processes? (principle 6) Are there ways of further enhancing your methods or new, more effective ways of working that you can adopt? (principle 5) Are there ways of better measuring or understanding uncertainty? (principles 5 and 6)
4. Communicating quality
What are the limitations in the data you use? (principle 7) Do you clearly explain the quality of your outputs and analysis to your users and stakeholders? (principle 7)
5. Effective engagement
How do you ensure the work you do and your statistics are valuable? (principle 8) Do you have a good understanding of key stakeholders’ needs? (principle 8) Can you improve accessibility and clarity of your outputs? (principles 9 and 10)
Related guidance
Civil Service
Office for Statistics Regulation:
- Guidance about Accountability
- Statistical Practice Capability Framework
- Guidance on producing official statistics in development
- Guidance for Models: Trustworthiness, Quality and Value
- Thinking about quality when producing statistics
- Quality assurance of management information
- Collecting and reporting data about sex and gender identity in official statistics
- Approaches to presenting uncertainty in the statistical system
- User engagement framework
- Unlocking the value of data through onward sharing
Analysis Function guidance hub:
- Guide to GSS statistical techniques and tools
- Leadership and analysis
- Data sharing for national crisis response
- National Statistician’s guidance: management information and official statistics
- Government Data Quality Framework
- Quality questions and red flags
- Writing about data
- User engagement top tips
- Communicating quality, uncertainty and change
- Making analytical publications accessible
RSS’s new Principles to support statisticians making trade-offs:
Good practice examples from the TQV voluntary application community
Experiences of applying TQV prepared by organisations that voluntarily apply the Code:
- UK Health Security Agency Data Dashboard
- Human Fertilisation and Embryology Authority Dashboard
- Fable Data
- COVID-19 dashboard
- Department for Health and Social Care
- The Department for Business, Energy and Industrial Strategy (BEIS)
- Scottish Fiscal Commission
- Ministry of Housing, Communities and Local Government
- University and Colleges Admissions Service
- Department for Work and Pensions
- Financial Conduct Authority
Code of Practice for Statistics
- Understanding TQV
- The Code Principles
- Standards for Official Statistics
- Standards for the Public Use of Statistics, Data and Wider Analysis
- Code Guidance – further information and examples for each principle are given in the short guides for the Standards for Official Statistics