resources.qmd

::: {.callout-important}
This version of the AQuA book is a preliminary ALPHA draft.  It is still in development, and we are still working to ensure that it meets user needs. 

The draft currently has no official status. It is a work in progress and is subject to further revision and reconfiguration (possibly substantial change) before it is finalised. 
:::

# Resources

## Written resources

The key additional resources referred to in the AQuA Book:

* The [Analysis Function Standard](https://www.gov.uk/government/publications/government-analysis-functional-standard--2)
* The [Green Book](https://www.gov.uk/government/publications/the-green-book-appraisal-and-evaluation-in-central-government/the-green-book-2020)
* The [Magenta Book](https://www.gov.uk/government/publications/the-magenta-book)
* The [Orange Book](https://www.gov.uk/government/publications/orange-book)

### Guidance and advice for performing analysis

* The [Uncertainty Toolkit for Analysts in Government](https://analystsuncertaintytoolkit.github.io/UncertaintyWeb/index.html) provides support for handling uncertainty in analysis.
* [Advice for policy professionals using statistics and analysis](https://analysisfunction.civilservice.gov.uk/policy-store/advice-for-policy-professionals-using-statistics/) helps policy professionals work effectively with statisticians and other analysts. It introduces some important statistical ideas and concepts to help policy professionals ask the right questions when working with statistical evidence.    
* The [Data Ethics Framework](https://www.gov.uk/government/publications/data-ethics-framework/data-ethics-framework-2020) guides appropriate and responsible data use in government and the wider public sector. It helps public servants understand ethical considerations, address these within their projects, and encourages responsible innovation.    
* The [Government Data Quality Framework](https://www.gov.uk/government/publications/the-government-data-quality-framework/the-government-data-quality-framework) supports the production of sustainable high quality data.    
* The [Reproducible Analytical Pipelines](https://analysisfunction.civilservice.gov.uk/support/reproducible-analytical-pipelines/) guidance sets out what a Reproducible Analytical Pipeline is and points to resources for analysts who need to build them.

### Guidance and advice for performing assurance

* The Department for Education's Quality Assurance Model (hyperlink required) helps to evaluate organisational strengths and weaknesses in Quality Assurance related to analysis.
* The [National Audit Office Framework to review models](https://www.nao.org.uk/wp-content/uploads/2016/03/11018-002-Framework-to-review-models_External_4DP.pdf) provides a structured approach to review models which organisations can use to determine whether the modelling outputs they produce are reasonable, robust and have a minimal likelihood of errors being made. 
* [Department for Energy Security and Net Zero modelling tools and QA guidance](https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.gov.uk%2Fgovernment%2Fpublications%2Fenergy-security-and-net-zero-modelling-quality-assurance-qa-tools-and-guidance&data=05%7C02%7Cmodellingintegrity%40energysecurity.gov.uk%7Cc42f8ed850c24245b91f08dc28c9b298%7Ccbac700502c143ebb497e6492d1b2dd8%7C0%7C0%7C638430094188459392%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=6pFuTNcJcz5EddPnuIE8CmbU%2BrzUcZvYKdHpdVPkGgk%3D&reserved=0) provides resources to help quality assure new and existing models, including those developed by third parties.       
*  [Introduction to AI assurance](https://www.gov.uk/government/publications/introduction-to-ai-assurance/introduction-to-ai-assurance) outlines considerations for the design and assurance of AI models, including risk assessment, bias audits and considering the ongoing 'health' of the model.
* The [Duck Book](https://best-practice-and-impact.github.io/qa-of-code-guidance/intro.html) provides guidance on assuring code.

### Guidance and advice for communicating analysis

* The Office for Statistical Regulation’s [Approaches to presenting uncertainty in the statistical system](https://osr.statisticsauthority.gov.uk/publication/approaches-to-presenting-uncertainty-in-the-statistical-system/) explores ways of communicating uncertainty in statistics.
* The Government Analysis Function guidance note [Communicating quality, uncertainty and change](https://analysisfunction.civilservice.gov.uk/policy-store/communicating-quality-uncertainty-and-change/) explains how to communicate information about quality, uncertainty and change to users.
* The Analysis Function's [Making Analytical Publications Accessible Toolkit](https://analysisfunction.civilservice.gov.uk/policy-store/making-analytical-publications-accessible/) gives guidance to help ensure that any that websites, tools, and technologies produced from analysis are designed and developed so that they are accessible.
* If you are publishing statistics you shall follow your organisation's guidance and the [regulatory guidance for publishing official statistics and national statistics](https://osr.statisticsauthority.gov.uk/wp-content/uploads/2018/10/Publishing_official_statistics_National_Statistics_1218.pdf).   
* If you are publishing research, you shall follow your organisations guidance and the [Government Social Research Publication protocol](https://www.gov.uk/government/publications/government-social-research-publication-protocols).   
* If you are publishing an evaluation, refer to any recommendations from the [Evaluation Task Force](https://www.gov.uk/government/organisations/evaluation-task-force).    
 
## External sources of quality assurance

The [Government Actuary’s Department (GAD)](https://www.gov.uk/government/publications/gad-services/government-actuarys-department-services) can provide expert quality assurance reviews of models across the public sector. GAD are a team of financial risk professionals and are experts in reviewing models on all modern platforms, including Excel, R, and Python. As a non-ministerial department, GAD can offer unique support from within government.