# Maths a level d1

### Edexcel

The module consists of 6 chapters. The exam, which is for 90 minutes, usually has 7 questions (not counting sub-questions) in total. No knowledge of any C12 topics is required.

Algorithms - the general idea of algorithms and their implementation using flow charts, in particular bin packing, bubble sort, quick sort and binary search.

Algorithms on graphs -

The route inspection problem -

Critical path analysis -

Linear programmings -

Matchings -

### AQA

The module is of about 15 short chapters. The specification states that basic C1 & C2 knowledge; however, in practice GCSE Mathematics is barely required. It is examined in a 90 minute (1hr 30min) paper with exams in both January and Summer sessions per year.

Algorithms - Basic introduction to algorithms, including sorting algorithms (bubble, shuttle, shell, quick) and algorithms in 'computerised' English and flowcharts are required, as well as specialist algorithms as below.
Graph theory - an introduction to graphs (as used in Decision Maths), and different types. Lots of terminology.
Network algorithms - Prim's and Kruskal's algorithms to find minimum spanning trees. Dijkstra's algorithm to find minimum route to travel between two nodes. Chinese Postman algorithm to find minimum route to cover all edges. Also, an introduction to the travelling salesman problem, with the minimum and maximum route algorithms, and when they fail.
Mappings - setting up a mapping, using the optimum mapping algorithm.
Linear programming - reducing problems to a linear problem, and using graphs to find the optimum solution. Simplex method is not covered.

### OCR (MEI)

The module consists of four chapters, all of which assume basic C1&C2 knowledge. It is examined in a 90 minute paper (exams in January and June of each year).

Algorithms - a basic introduction to them, and why and how they are used. Candidates may be asked to apply an algorithm (eg sorting or packing) or come up with one of their own to solve a simple problem.
Graph theory - again, an introduction to graphs, including how to use them to solve problems, and the different types (Eulerian/non-Eulerian, directed, and so forth). A lot of terminology to learn.
Networks - what a network is and how it is used. Candidates learn about Kruskal's, Prim's, and Dijkstra's algoriths and how to use them.
Linear programming - how to reduce a problem into an 'LP' and how to use this graph to find a solution, usually maximising (using the Simplex method) or minimising something.