A Level


Qualification Type

A Level

Additional Entry Requirements

Grade 6 – 9 in GCSE Mathematics


Initial assessment during enrolment.

Opportunities for Work Related Activities

‘Women in Engineering’, robotics, statistics and mechanics taster sessions. ‘Maths Inspiration’ at the Bristol Hippodrome.

“Facts are stubborn things, but statistics are pliable”.

Course Overview

Year 1

A level Statistics builds from GCSE level mathematics and distributions, hypothesis testing and their applications. It draws on ideas from data analysis and probability covered at GCSE and extends them in to new ideas. Students will cover a range of topics involving new ideas and some they have already covered. They will look at applied statistics and how these may be used in real life contexts. Students will be encouraged to solve problems and will be expected to answer questions with less scaffolding than GCSE questions combining their subject knowledge and problem solving skills.

Year 2

Year 2 A level Statistics builds on statistics covered in year 1 and develops ideas around the statistical enquiry cycle and the ability to analyse problems and draw conclusions. The use of technology to analyse data is also a key element of the course and the ability to use hypothesis testing to draw conclusions. It emphasises how statistical ideas are interconnected and how statistics can be applied to model situations with data using probability, distributions, graphs and charts. There are opportunities to solve problems in a variety of contexts, including social sciences and business. It prepares students for further study and employment in a wide range of disciplines involving the use statistics


A level Statistics will be a huge benefit to many University courses that involve a large element of statistics including Biology, Geography, Psychology, economics, business and you can also take your statistics further by studying it at university which can lead you into a variety of roles.


Accountancy/finance; actuary; air traffic controller; forensics; data analyst; statistician.