### Methodology

The Annual Population Survey is a continuous household survey. Most people are interviewed in person first, and later by telephone. The sample is formed partly from waves 1 and 5 of the Labour Force Survey (in which selected addresses are contacted every 3 months) and partly from boost cases that are in the sample for 4 waves, spread one year apart.

Participants are randomly selected from the Royal Mail Postcode address File (PAF). The NHS communal accommodation list is also used and (in the case of remote parts of Scotland) telephone directories. All eligible individuals found at the selected address may be interviewed. Individuals are included in the dataset for this analysis if they respond themselves or if a family member responds on their behalf. The complex survey design has been taken into account when calculating confidence intervals.

Weighting:

The achieved sample of approximately 275,000 undergoes weighting which is structured at local authority level and uses age and sex dimensions.

Weighting is used to adjust the results of a survey to make them representative of the population and improve their accuracy.

For example, a survey which contains 25% females and 75% males will not accurately reflect the views of the general population, which we know is around 50% male and 50% female.

Statisticians rebalance or ‘weight’ the survey results to more accurately represent the general population. This helps to make them more reliable.

Survey weights are usually applied to make sure the survey sample has broadly the same gender, age, ethnic and geographic make up as the general population.

The Office for National Statistics population estimates and projections are used as the basis for this weighting process.

Confidence intervals:

Confidence intervals for each ethnic group are available if you download the data.

The APS is based on a sample of 16 to 64 year olds, rather than all 16 to 64 year olds in England, Wales and Scotland. This measure makes reliable estimates of the percentage of people in this age bracket who were employed, but it’s impossible to be 100% certain of the true percentage.

Based on the APS results, it’s estimated that 48% of of White 16 to 64 year olds with no qualifications who are not in full-time education were economically inactive in 2017.

The APS is based on a sample of 16 to 64 year olds, rather than all 16 to 64 year olds in England, Wales and Scotland. This measure makes reliable estimates of the percentage of people in this age bracket in England, Wales and Scotland who were economically inactive, but it’s impossible to be 100% certain of the true percentage.

It’s 95% certain, however, that somewhere between 47.2% and 49.0% of all White 16 to 64 year olds with no educational qualifications in England, Wales and Scotland who were not in full-time education were economically inactive in 2017. In statistical terms, this is a 95% confidence interval. This means that if 100 random samples were taken, then 95 times out of 100 the estimate would fall in this range (that is, between the upper and lower confidence interval). But 5 times out of 100 it would fall outside this range.

The smaller the survey sample, the more uncertain the estimate and the wider the confidence interval. For example, fewer 16 to 64 year olds from the Asian ethnic group responded to the survey than their White counterparts, so we can be less certain about the estimate for the smaller group. This greater uncertainty is expressed by a wider confidence interval, for example of between 52.0% and 60.5% for Asians aged 16 to 64 in 2017.

Statistically significant findings have been determined where the 95% confidence intervals of an ethnic group do not overlap with the confidence interval for the group to which they are being compared.

### Suppression rules and disclosure control

In data covering all ethnic groups together, estimates based on sample sizes of less than 30 have been suppressed. For data broken down by ethnic groups, estimates based on sample sizes under 100 have been suppressed.

‘Suppression’ means these figures have not been included in the data, to protect confidentiality and because the numbers involved are too small to draw any reliable conclusions.

Breaking the figures down by gender and the relatively smaller overall population of those who are unemployed reduces sample sizes further and makes the figures less reliable.

Data been suppressed at some qualification levels for the Mixed and Other groups because of the very small numbers.

### Rounding

Estimates in the charts and tables are rounded to whole percentages. Estimates in the download file are rounded to 1 decimal place.

Quality and methodology information