Mathematics (GCE A Level)

Why study Mathematics?

An A Level in Mathematics will help you immensely with other A Level subjects.

Physics, Chemistry, Computing, Geography, Psychology and Business all use some type of maths.

All of the sciences use mathematical techniques and doing A Level maths will give you a head start in these subject areas.

The strengths of A Level mathematicians are in their logical and analytical thought processes and problem - solving talents, usually linked with good IT skills. Maths teaches you to think in a logical way, which is vital when putting your point across.

What do I need to know or be able to do before taking this course?

You will be expected to have achieved at least a grade B in your GCSE Maths course.

What will I learn on the A Level course?

Mathematics at AS and A level is a course worth studying in its own right. It is challenging but interesting. It builds on work you will have met at GCSE, but also involves new ideas that some of the greatest minds of the last millennium have produced. It serves as a very useful support for many other qualifications as well as being a sought after qualification for the workplace and courses in Higher Education.

While studying Mathematics you will be expected to

• Use mathematical skills and knowledge to solve problems.

• Solve quite complicated problems by using mathematical arguments and logic. You will have to understand and demonstrate what is meant by proof in mathematics.

• Simplify real life situations so that you can use mathematics to show what is happening and what might happen in different circumstances.

• Use the mathematics that you learn to solve problems that are given to you in a real-life context.

• Use calculator technology and other resources (such as formula booklets or statistical tables) effectively and appropriately; understand when not to use such technology, and its limitations.

Mathematics at AS and A level is divided into four branches:

Core Mathematics

When studying core mathematics at AS and A level you will be extending your knowledge of such topics as algebra and trigonometry as well as learning some brand new ideas such as calculus. If you enjoyed the challenge of problem solving at GCSE using such techniques then you should find the prospect of this course very appealing.

Although many of the ideas you will meet in the core mathematics are interesting in their own right, they also serve as an important foundation for other branches of mathematics, especially mechanics and statistics.

Statistics

When you study statistics you will learn how to analyse and summarise numerical data in order to arrive at conclusions about it. You will extend the range of probability problems that you started for GCSE by using the new mathematical techniques studied on the pure mathematics course.

Many of the ideas you will meet in this course have applications in a wide area of other fields – from assessing what your car insurance is going to cost, to how likely the earth is going to be hit by a comet in the next few years.

Mechanics

When you study mechanics you will learn how to describe mathematically the motion of objects and how they respond to forces acting upon them, from cars in the street to satellites revolving around the planet. You will learn the technique of mathematical modelling; that is, of turning a complicated physical problem into a simpler one that can be analysed and solved using mathematical methods.

Many of the ideas you will meet in the course form an essential introduction to such important modern fields of study such as cybernetics, robotics, biomechanics and sports science, as well as the more traditional ideas of engineering and physics.

Decision Maths

There are strong links between development of computer technology and the development of decision maths. When studying decision maths you will learn how to use and understand and algorithm. This is a precise set of instructions so clear that it will allow anyone, even a computer to use it. You will be able to use the techniques of critical path analysis and linear programming which is used to solve problems in a wide variety of area including finance, design and management.