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Guidance

Statistical quality principles and procedures

Updated 30 July 2026

Applies to England

© Crown copyright 2026

This publication is licensed under the terms of the Open Government Licence v3.0 except where otherwise stated. To view this licence, visit nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: psi@nationalarchives.gov.uk.

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This publication is available at https://www.gov.uk/government/publications/standards-for-official-statistics-published-by-the-department-for-education/statistical-quality-principles-and-procedures

This guidance was last updated in April 2013.

Overview

Principal 7 of the Code of Practice for Official Statistics requires producers of official statistics to publish quality guidelines for their official statistics.

Statistical policy statement on statistical quality: principles and procedures

Statistical quality at the Department for Education (DfE) is defined as meeting users’ needs with particular reference to the 6 quality dimensions of the statistics collected, analysed and reported:

  • relevance
  • accuracy
  • timeliness and punctuality
  • accessibility and clarity
  • comparability
  • coherence

The following principles underpin the delivery of statistical quality at DfE:

  • users are identified and we engage with them in a spirit of consultation and responsiveness, and their needs are prioritised and met within available resources
  • suppliers are respected and dealt with ethically, legally and effectively
  • methodologies, processes and practices are documented to the correct level of detail for their purpose, kept up to date and made available where appropriate
  • statistical processes and outputs are monitored and measured against standards with a view to their maintenance and improvement

Statistical quality dimensions: definitions and key components

The following lists the definitions and key components of the 6 statistical quality dimensions at DfE.

Relevance

Definition

Relevance is the degree to which the statistical produce meets user needs for both coverage and content.

Key components

Any assessment of relevance needs to consider:

  • the users of the statistics
  • the users’ needs
  • the extent to which the output meet these needs

Accuracy – survey data

Definition

For survey data, accuracy is the degree of closeness between an estimate derived from the survey data and the (unknown) true value.

Key components

Accuracy can be split into sampling error and non-sampling error, where non-sampling error includes:

  • coverage error
  • non-response error
  • measurement error
  • processing error
  • model assumption error

Accuracy – administrative databases

Definition

For administrative databases, accuracy is how well the information is recorded and transmitted.

Key components

Accuracy can be measured in terms of:

  • completeness
  • timeliness or recording and transmission
  • accuracy of recording of data items, including data matching
  • correct use of coding, including recording
  • correct interpretation

Timeliness and punctuality

Definition

Timeliness is related to the time elapsed from the period to which the statistics relate to the date of release of the statistics.

For example, if the statistics relate to the 2008 to 2009 financial year and they are released in January 2010, then the elapsed time is 10 months. The timeliness could be improved by one month if the statistics for the 2009 to 2010 financial year could be released in December 2010.

Punctuality is elapsed time between the actual and planned (and published) time and date of release.

Key components

An assessment of timeliness and punctuality should consider the:

  • production time
  • frequency of release
  • punctuality of release

Accessibility and clarity

Definition

Accessibility is the ease with which users are able to access the data. It also relates to the format in which the data are available and the availability of supporting information.

Clarity refers to the quality and sufficiency of the metadata, illustrations and accompanying advice.

Key components

Specific areas where accessibility and clarity may be addressed include:

  • needs of expert and non-expert users
  • consistency of standard in relation to revisions, rounding, data suppression and spreadsheet type
  • assistance to locate information

Comparability

Definition

Comparability is the degree to which data can be compared over time and domain.

Key components

Comparability should be addressed in terms of comparability over:

  • time
  • spatial domains – for example, sub-national, national or international
  • domain of sub-population – for example, type of school or ethnicity of pupils

Coherence

Definition

Coherence is the degree to which data derived from different sources or methods but that refer to the same phenomenon are similar.

Key components

Coherence should be addressed in terms of:

  • data produced at different frequencies
  • other statistics in the same domain
  • sources and outputs
  • coverage of different databases
  • definitions and coding used for different databases

Delivering quality statistics

To put the quality principles into practice, reference should be made to the following statistical policy notices (as well as more specific information contained in DfE’s statistical releases), which overlap with and reinforce particular aspects of delivering statistical quality.

Relevance

Users should expect that they will be appropriately consulted about quality principles and procedures in line with DfE’s public involvement and engagement strategy

Accuracy

Users should expect that:

  • statistical releases will contain a description of data quality issues relating to the release, and any impact that has on analysis of changes over time or comparisons between different groups will be transparent to a lay and expert audience
  • statistical releases will be compliant with, and contain specific details on, the implementation of DfE’s statistical revisions and corrections policy
  • survey and administrative data will be published with details of how the data is collected to allow users to understand its strengths and limitations
  • survey data will be presented with full information on sampling variability, confidence intervals, response rates and other relevant criteria to allow users to make informed judgements on quality

Timeliness and punctuality

Users should expect that:

Accessibility and clarity

User should expect that:

  • statistical releases and other information posted on DfE’s research and statistics gateway will comply with DfE’s internet accessibility policies
  • all publications will use plain English wherever possible

Comparability

Users should expect that:

  • DfE will use harmonised concepts and definitions in statistical releases wherever these are available
  • any statistical release that does not use harmonised definitions will clearly explain why the harmonised definition has not been used and any plans to move to harmonised definitions

Coherence

Users should expect that:

  • DfE will release related statistical releases at the same time and on the same day to aid user understanding unless this requires significant delay to the release of one or more of the statistical releases
  • where related statistics are released across more than one release, we will make it clear to users where the related statistics can be located

Monitoring and reporting

DfE supports transparent monitoring and reporting of the statistical quality of its statistical releases and outputs.

We are also actively involved in the Government Statistical Service Task Force on data quality, and any improvements in statistical quality policies and procedures from the task force will be incorporated into DfE’s policies and procedures.

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