You asked
I would like to know the very latest immigration statistics of Milton Keynes as a percentage in relation to the population?
What are the latest percentages of migrants from within the EU that are currently in Milton Keynes?
What are the latest percentages of migrants from outside the EU that are currently in Milton Keynes?
We said
Thank you for contacting the Office for National Statistics (ONS) regarding the migration estimates of EU and Non-EU immigrants in Milton Keynes.
Local Authority migration estimates are published annually in August within our Local Area Migration Indicators Suite.
A Quality and Methodology Information document for this is available here.
The migration inflow estimate for Milton Keynes (geographical code E06000042) for the year ending June 2013 is 1,600. The outflow estimate is 1,800. These are 0.6% and 0.7% respectively (to one decimal place) of the population estimate which is 255,700.
The non-UK born population estimate of Milton Keynes for the year ending 2013 is 49,000 (with a confidence interval of 8,000 +/-). This is 19.4% of the population estimate for this period which is 252,000.
These estimates are based on sample surveys and therefore contain a level of uncertainty. This level of uncertainty increases as the estimates become disaggregated (for example, by geography or by migrant grouping). Due to the uncertainty surrounding low estimates it is not possible to provide international migration estimates down to Local Authority level with an EU /Non-EU breakdown.
Background notes:
Percentages are based on rounded figures.
Migration Flow estimates are based on the International Passenger Survey (IPS).
Stock migration (Non-UK population) estimates are based on the Annual Passenger Survey (APS).
Confidence intervals are indicators of the extent to which the estimate may differ from the true value. The larger the confidence interval, the less precise is the estimate. The central value within the confidence interval is the best estimate of the true value. The confidence interval around the estimate captures the uncertainty of the estimate, and gives an interval within which we can say that there is a high probability that the true value lies.
At the 95% confidence level, over many repeats of the sample under the same conditions, we would expect the confidence interval to contain the true population value 95 times out of 100. Equivalently, we can say that there would be a 1 in 20 chance that the true population value would lie outside of the range of the 95% confidence interval.