Annex B : Proportion of learners with different characteristics
1 . Table B1 shows the numbers and proportions of English 16-year-old learners in the Key Stage 4 population with different characteristics , according to whether they lived in a Uni Connect area , for all GCSE cohorts between summer 2014 and 2019 combined .
2 . Numbers are rounded to the nearest five and proportions are rounded to one decimal place .
Table B1 : Number and proportion of English 16-year-old learners in Key Stage 4 population with different characteristics for all GCSE cohorts between summer 2014 and 2019 combined
Factor
Number of learners from Uni Connect areas
Proportion of learners from Uni Connect areas
Number of learners from non-
Uni Connect areas
Proportion of learners from non-
Uni Connect areas
GCSEs summer 2014 90,450 17.4 % 453,960 17.2 % GCSEs summer 2015 89,470 17.3 % 449,530 17.0 % GCSEs summer 2016 86,410 16.7 % 439,150 16.6 % GCSEs summer 2017 83,440 16.1 % 429,330 16.3 % GCSEs summer 2018 82,810 16.0 % 425,675 16.1 % GCSEs summer 2019 85,855 16.6 % 441,455 16.7 % GCSEs : 0 GCSEs A * to C ( or 9 to 4 ) 95,325 18.4 % 274,960 10.4 % GCSEs : 1 GCSEs A * to C ( or 9 to 4 ) 54,900 10.6 % 176,665 6.7 % GCSEs : 2 GCSEs A * to C ( or 9 to 4 ) 40,080 7.7 % 140,540 5.3 % GCSEs : 3 GCSEs A * to C ( or 9 to 4 ) 34,680 6.7 % 131,550 5.0 % GCSEs : 4 GCSEs A * to C ( or 9 to 4 ) 32,240 6.2 % 129,470 4.9 % GCSEs : 5 GCSEs A * to C ( or 9 to 4 ) 31,325 6.0 % 133,840 5.1 % GCSEs : 6 GCSEs A * to C ( or 9 to 4 ) 32,515 6.3 % 148,770 5.6 % GCSEs : 7 GCSEs A * to C ( or 9 to 4 ) 37,625 7.3 % 180,870 6.9 % GCSEs : 8 GCSEs A * to C ( or 9 to 4 ) 44,170 8.5 % 246,585 9.3 % GCSEs : 9 GCSEs A * to C ( or 9 to 4 ) 48,260 9.3 % 357,105 13.5 % GCSEs : 10 GCSEs A * to C ( or 9 to 4 ) 37,895 7.3 % 372,815 14.1 %
GCSEs : 11 or more GCSEs A * to C ( or 9 to 4 )
29,425 5.7 % 345,935 13.1 %
English GCSE : No 214,160 41.3 % 739,160 28.0 % English GCSE : Yes 304,280 58.7 % 1,899,945 72.0 % Maths GCSE : No 212,890 41.1 % 725,085 27.5 % Maths GCSE : Yes 305,545 58.9 % 1,914,020 72.5 % Sex : Female 259,495 50.1 % 1,302,470 49.4 %
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