Download Key Stage 5 AS Maths

Key Stage 5 AS Maths
Key Stage 5 mathematics is the final step on the mathematics ladder for most of the
keen mathematicians. As it is the final stage of the syllabus, you can expect to cover all
topics and areas that you have been taught before as you go through both levels of Key
Stage 5; the Core Mathematics 12 and Statistics 1 units of study. As well as recapping
previous stages to a higher level, you will also be taught some new theories and topics
such as surds, simultaneous equations and functions. The second level of Key Stage 5
mathematics revolves around statistics, you will be introduced to sta tistical diagrams
which include scatter diagrams, stem and leaf plots along with box and whisker plots
and cumulative frequency diagrams and concepts such as linear interpolation and use
of coding. In addition to this you will become familiar with statistical probability which
involves predicting outcomes based on both previous outcomes as well as new
outcomes. Wherever possible, we encourage our students to use and apply their
learning to real and relevant contexts.. If you complete Key Stage 5 mathematics you
can call yourself an official mathematician as you will have completed all modules of the
maths syllabus, congratulations. At EGIS we provide our students with a Bridging the
Gap to A-level Maths induction booklet which helps our students reinforce key areas of
algebra learning from Key Stage 4 to ensure they are well equipped to enter the new
programme of study.
In term 1 our students completed the Organising and Summarising Data and the
Probability units. The aim now is to complete the syllabus by the end of term 2,
allowing ample exam revision time during the final term.
Statistics 1 Plan for Term 2
Topic/ Unit
Correlation
Sub Topics

Calculate the product
moment correlation
coefficient (pmcc) of data
provided it follows a linear
relationship.

Interpret the pmcc

Know that coding does
not affect the pmcc
Resources
Chapter 6

Combine Linear
Regression and
Correlation in one
question about a set of
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data.

Derivations and tests of
significance will not be
required.
Linear Regression

Draw a scatter diagram
Chapter 7
to decide if linear
regression is appropriate.

Calculate the equation of
a linear regression line
using the method of least
squares.

May be required to draw
this line onto a scatter
diagram.

Understand
explanatory(independent)
and esponse(dependent)
variables.

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Be able to interpret a
scatter diagram or linear
regression equation.

Use a linear regression
equation to make
predictions within the
range of values of the
explanatory variable and
determine the feasibility
of using extrapolation.

Variables other than x
and y may be used.

Linear change of variable
may be required through
the coding of data.
Discrete Random

The concept of a discrete
random variable.
Variables

The probability function
p(x) and the cumulative
distribution function F(x)
for a discrete random
variable.
Chapter 8

Simple use of the
probability function
p(x)=P(X = x).

Mean E(X) and variance
Var (X) of a discrete
random variable.

Use E(X) and E(X2) to
calculate variance.

Knowledge of how coding
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affects the mean and
variance.

The Discrete Uniform
Distribution and the mean
and variance of this.
Normal Distribution

Knowledge of the shape,
symmetry and proportions
of a normal distribution.

Use the normal
Chapter 9
distribution table to find
proportions.

Use given information to
find the z value and then
find proportions.

Work backwards if given
proportions to find W,
mean or standard
deviation.

Questions may involve
the solution of
simultaneous equations.

Knowledge of the
Probability Density
Function is not required.

Interpolation is not
necessary.

Derivation of the mean,
variance and cumulative
distribution is not
required.
Teacher worksheets