Highest qualification levels of working age adults by NUTS2 area, qualification and year
- High level information
- Summary information
- Statistical quality information
- Open Data
TitleLevels of highest qualifications held by working age adults by UA and gender
Last updateApril 2017
Next updateApril 2018 (provisional)
Publishing organisationWelsh Government
Source 1Annual Population Survey, Office for National Statistics
Lowest level of geographical disaggregationLocal authorities
Languages coveredEnglish only
Data licensingYou may use and re-use this data free of charge in any format or medium, under the terms of the Open Government License - see http://www.nationalarchives.gov.uk/doc/open-government-licence
General descriptionData are presented for working age adults i.e. on basis of 1. males and females aged 18-64 and 2. males aged 18-64 and females aged 18-59 as referred to in earlier releases (prior to 2015 data) – according to their age at the start of the academic year. Note that data for working age adults, on the basis of males and females aged 18-64, are only available from 2008 onwards.
Data collection and calculationSource: Annual Population Survey/Annual Local Labour Force Survey, Office for National Statistics
The data are based on the results of the Annual Population Survey for 2004 onwards, and from the annual Local Labour Force Survey for Wales for 2001-2003, both of which are household surveys carried out by the Office for National Statistics.
From 2001, annual Local Labour Force Survey (LLFS) data collected in Wales were based on a significantly enhanced sample.
The survey asks respondents for qualifications that they hold, and from this information the highest qualification held by the respondent is calculated. The highest qualifications are grouped into National Qualification Framework (NQF) levels. Figures are provided for those obtaining qualifications at least at a certain level, and qualifications up to and including a certain level.
Data have previously been presented as NVQ equivalencies. From September 2004, the National Qualification Framework (NQF) was expanded and the former levels 4 and 5 were divided into more precise levels (4-8). Data are now presented according to this classification.
Frequency of publicationAnnual
Data reference periodsFor years labelled 2001 to 2003 in this dataset, the actual periods covered are the 12 months running from March in the year given to February in the following year (e.g. 2001 = 1 March 2001 to 28 February 2002).
Since 2004, the annual data have been produced on a rolling annual basis, updated every three months. The rolling annual averages are on a calendar basis with the first rolling annual average presented here covering the period 1 January 2004 to 31 December 2004.
Note therefore that there is a two-month overlap between the last period presented on the former March to February basis, and the first period on the new basis.
Users, uses and contextThe statistics are used within the Welsh Government to monitor trends in qualification levels and specifically are included within the Skills Performance measures and the Tackling Poverty Action Plan.
Rounding appliedPercentages are rounded to one decimal place.
Revisions informationSince the previous publication, the Annual Population Survey data back to 2013 had been reweighted, and this StatsWales cube has been updated with these new data. The reweighted data has made a slight change to data from 2013.
Statistical qualityThe figures for local authorities in Wales (not the figures for all of Wales) for 2001, 2002 and 2003 in these tables may not be the same as published elsewhere, as the numbers here are estimated using Welsh specific weights. These weights better reflect the population estimates for Welsh local authorities in these years.
As the data come from a survey, the results are sample-based estimates and therefore subject to differing degrees of sampling variability, i.e. the true value for any measure lies in a differing range about the estimated value. This range or sampling variability increases as the detail in the data increases; for example local authority data are subject to higher variability than regional data.