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Scheme of Work 2010 – 2011
Statistics 1
Week/
Date
Learning Outcomes
[Can be differentiated]
Exploring data 1: Introduction (Recap of statistics in GCSE Maths)

Teaching & Learning Activities
(All resources here are
hyperlinked to the MEI website)
Poster activities. Learners revise
techniques known and present back
to class
Be able to use a tally chart to produce a frequency table (page 4
1
of the textbook).

Be able to describe the shape of a distribution (e.g. symmetrical
distribution, or positive or negative skew) (pages 5 and 6 of the 

textbook).

Be able to construct stem-and-leaf diagrams (pages 6 - 8 of the
HW and/or
Assessments
Multiple choice section test
Questions
Exploring Data 1 Section test
solutions
Study Plan
Notes and Examples
Crucial Points
textbook).

Understand what is meant by categorical
data (qualitative), numerical data, continuousdata
and discrete data (pages 12, 13 of the textbook).

Understand sigma notation (page 13 of the textbook).

Know that the mean, mode, median and midrange are all
measures of central tendency, know how to calculate them and
when each should be used (pages 13 - 16 of the textbook).
Exploring Data 2: Frequency Distribution

Be familiar with frequency tables and able to use them to
calculate the mean (pages 17 - 19 of the textbook).
2-3

Understand how data can be grouped into class intervals and
how to deal with class boundaries for
both continuous and discrete data (pages 22 - 24 of the
textbook).

Poster activities. Learners revise
techniques known and present back
to class.
Be able to use grouped data to estimate the mean (pages 25 29 of the textbook).
HE Applications project: Learners are
given data on HE applications and
have to present back and interpret
their findings using statistics.
Learners can use Excel or Autograph
(Teacher can demonstrate basic use
of each)
Study Plan
Notes and Examples
Crucial Points
Multiple choice section test
Questions
Exploring Data 2 Section test
solutions
HE data presentation. Learners will
be filmed!


Know how to calculate the range of a set of data and be aware 
of its limitations as a measure of spread (pages 32, 33 of the 
Exploring Data 3: Measures of Spread

Interactive Resources
Mean and SD
Other resources
Calculating measures of spread
Multiple choice section test
Questions
Exploring Data 3 Section test
solutions
textbook).


Know the meaning of mean square deviation (msd) and be fluent

with both methods of calculating it (pages 35, 36 of the

textbook).

Know the meaning of root mean square deviation (rmsd) and be

fluent at calculating it (pages 35, 36 of the textbook).

Know the meaning of variance, be fluent at calculating it and
Study Plan
Notes and Examples
Crucial Points
know how it is different from the mean square deviation
(divisor n - 1 instead of n (pages 36 - 38 of the textbook).

Know the meaning of standard deviation, be fluent at calculating
it and know how it is different from the root mean square
deviation (square root of the variance, rather than square root of
the msd) (pages 36 - 38 of the textbook).

Be able to calculate the mean, msd, rmsd, variance and
standard deviation of combined data sets (page 39, 40).

Know that approximately 95% of data lie within two standard
deviations of the mean for most data sets and that data values
more than 2 standard deviations from the mean are therefore
identified as outliers and should be investgated carefully to
ensure they are valid (pages 40, 41 of the textbook).
Exploring Data 4: Linear Coding

Be able to use linear coding to simplify calculations
of mean and standard deviation and convert them between
Interactive Resources
Linear Coding
Active learning resources
Linear Coding puzzle
Linear Coding puzzle Solutions




Other resources
Study Plant
Notes and Examples
Crucial Points
4
different units (pages 46 - 48 of the textbook).





Multiple choice section test
Questions
Exploring Data 4 Section test
solutions
Exploring Data Chapter
Assessment
Exploring Data Chapter
assessment solutions
HE Applications project: Learners are
given data on HE applications and
have to present back and interpret
their findings using statistics.
Data presentation 1: Introduction

Be able to interpret and draw bar charts (pages 57 - 59 of the
textbook).

Learners can use Excel or Autograph
(Teacher can demonstrate further
use of each)
Be able to interpret and draw vertical line charts (pages 57 - 59
of the textbook).

Know that bar charts are best used to illustrate categorical
data (page 57 of the textbook).

Know that vertical line charts are best used to
illustrate discrete data (page 57 of the textbook).




Know the difference between a bar chart and a histogram (page

62 of the textbook).

Know that histograms are normally used to
5
illustrate continuous data (page 62 of the textbook).

Understand that the vertical axis of a histogram is frequency
density, NOT frequency (page 64 of the textbook).

Know that histograms can be used to represented grouped data
with unequal class widths (page 65 of the textbook).

Know how to calculate frequency densities (pages 63 - 64 of the
textbook).

Know how to construct a histogram; (pages 62 – 69 of the
textbook).

Understand that, for a histogram, the areas of the bars are
proportional to the frequencies (Pages 62 – 63 of the textbook).

Know and understand the circumstances in which it is
acceptable to use histograms to illustrate discrete data (pages
66 - 68 of the textbook).

Be aware of the problems with class boundaries when using
histograms to illustrate discrete data (page 67 of the textbook).
Study Plan
Notes and Examples
Crucial Points
Multiple choice section test
Questions
Section Test Solutions
HE Applications project: Learners are
given data on HE applications and
have to present back and interpret
their findings using statistics.
Data Presentation 2: Quartiles, Box and Whisker Plots and
Cumulative Frequency Curves

Know how to calculate the upper quartile, lower quartile and
the interquartile range via calculation and using a cumulative

frequency curve; (pages 71 – 76).

Know how to construct a box-and-whisker diagram (boxplot);
6
(pages 73 and 77 of the textbook).




Learners can use Excel or Autograph
(Teacher can demonstrate further
use of each.
Multiple choice section test
Questions
Section Test Solutions
Data Presentation Chapter
Assessment
Chapter assessment solutions

Know how to recognise outliers; (pages 73 – 74 of the textbook).

Know how to construct a cumulative frequency table from a

grouped frequency table; (pages 74 – 75 of the textbook).
Know how to construct and interpret a cumulative frequency 

curve; (pages 76 – 77 of the textbook).
Other resources
Study Plan
Notes and Examples
Crucial Points
Know how to use a cumulative frequency diagram to work
out percentiles; (question 9 of Exercise 2D and the Notes and
Examples).


Understand what is meant by the complement of an event and 
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how to calculate its probability.
Probability 1: Introduction
7 - 10
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Understand and be able to calculate simple expectation.
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Understand what is meant by mutually exclusive events.
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Be able to calculate the probability of either one event or
another.
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Interactive Resources
Venn Diagrams Spreadsheet
Active learning resources
Venn Diagram Matching Activity
Venn Diagram Matching Activity
Solutions
Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions
Multiple choice section test
Questions
Probability 1 Section Test
Solutions


Understand how to use tree diagrams to calculate probabilities. 

Be able to use the addition law and multiplication law to

calculate probabilities.
Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions


Understand the concept of conditional probability; (pages 107 –
Active learning resources
Probability Matching Activity
Probability Matching Activity
Solutions
Probability Hexagonal Jigsaw
Probability Hexagonal Jigsaw
Solutions
Other resources
Venn Diagrams Worksheet
Venn Diagrams Worksheet
Solutions
Probability 2: Probability from two or more trials
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Probability 3: Conditional probability
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
109 of the textbook).
Know the formula for conditional probability P(A and B) = P(A) 

times P(B l A); (page 109 of the textbook).
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Understand that for independent events: P(A l B) = P(B) so,
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Understand how to use Venn diagrams when solving conditional

probability questions; (page 111 of the textbook).

Understand how to use tree diagrams in solving conditional
P(A and B) = P(A) times P(B); (page 109 of the textbook).
probability questions; (page 117 of the textbook).
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

Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions


Know what a discrete random variable (DRV) is; (Pages 119 – 

120 in the textbook).
Know the notation and conditions for a DRV; (Page 120 in the 
Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions
Discrete Random Variables 1: Introduction
11 - 12
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
textbook).
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Be able to construct a vertical line chart showing the probabilities
of the possible outcomes of a DRV; (Pages 120 – 121 in the
textbook).
Multiple choice section test
Questions
Probability 2 Section test
solutions
Multiple choice section test
Questions
Probability 3 Section test
solutions
Probability Chapter Assessment
Probability Chapter assessment
solutions
Multiple choice section test
Questions
Discrete Random Variables 1
Section Test Solutions
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

Other resources
Discrete Random Variables 1
Discrete Random Variables 2
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Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions
Further Probability 1: Factorials, permutations and combinations 

 Know what a factorial is and how to calculate it. (Pages 139 – 

140 in the textbook).
 Be able to cancel efficiently when dividing factorials. (Examples
Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions
Discrete Random Variables 2: Expectation and variance

Know what is meant by the expectation of a discrete random
variable and the variance of a discrete random variable and be
able to calculate these; (Pages 127 – 130 in the textbook).
on page 140 of the textbook).
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Know how to identify and calculate the number of permutations;
13
(Page 142 in the textbook).
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Know how to identify and calculate the number
of combinations (Pages 143 – 144 in the textbook).
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Know how to calculate a binomial coefficient, and how to use
Pascal’s triangle to provide shortcuts in calculating probabilities.
(Pages 145 – 146 in the textbook).
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Be able to calculate probabilities in less simple cases. (Pages
147 – 148 in the textbook).

Know that: nCr = nCn-r and n+1Cr+1 = nCr + nCr+1 ; (Pages 145 - 146
in the textbook).
Multiple choice section test
Questions
Discrete Random Variables 2
Section test solutions
Discrete Random Variables
Chapter Assessment
Chapter Assessment Solutions
Multiple choice section test
Questions
Further Probability 1 Section test
solutions
Further Probability Chapter
Assessment
Further Probability Chapter
assessment solutions
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Know the conditions required in order for the binomial
distribution to be used to calculate probabilities and be able to 
apply it to a general probability case; (Pages 155 – 157 in the 
The Binomial Distribution 1: Introduction

Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions
Multiple choice section test
Questions
Binomial Distribution 1 Section
test solutions
14 - 15
textbook).

Know what a probability distribution is, and be able to calculate 
it; (Pages 155 – 156 in the textbook).

Understand that the binomial distribution is an example of a
probability distribution; (Pages 155 – 156 in the textbook).
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Be familiar with the notation B(n, p) to denote a binomial
distribution with n trials and probability of success p; (Page 156
in the textbook).
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Know and be able to use the formula: P(X = r) = nCr prqn-r for 0
≤ r ≤ n; (Page 156 in the textbook).
The Binomial Distribution 2: Using the binomial distribution
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Know how to find the expectation of the binomial
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Active learning resources
Binomial puzzle
Binomial puzzle solutions
distribution (Page 159 in the textbook).
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Be able to use the binomial distribution to work out probabilities
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in a given situation; (Pages 160 – 161 in the textbook).
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Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions
Multiple choice section test
Questions
Binomial Distribution 2 Section
test solutions
Binomial Distribution Chapter
Assessment
Binomial Distribution Chapter
assessment solutions
Hypothesis testing using the binomial distribution 1: Introduction 
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 Be able to use tables of cumulative binomial probability (page 

174).
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 Understand the process of hypothesis testing and the associated
Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions
Multiple choice section test
Questions
Hypothesis testing 1 Section test
solutions
16 - 18
vocabulary (page 170 - 171).

Be able to identify the null hypothesis and alternative
hypothesis (H0 and H1) when setting up a hypothesis test on a
binomial probability model (page 170 – 171).
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Be able to conduct hypothesis tests at various significance levels
(page 171).
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Be able to draw a correct conclusion from the results of a
hypothesis test on a binomial probability model (page 170 –
171).
Hypothesis testing using the Binomial Distribution 2: More about 
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hypothesis testing
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Be able to identify the critical region and acceptance region for
Interactive Resources
Hypothesis testing
Instructions for using the
"Hypothesis Tester"
a hypothesis test (pages 117 - 119).
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Understand when to apply one-tailed tests and two-tailed tests 
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(pages 182 – 183).
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Know how to carry out a two-tailed test (pages 182 – 184).



Study Plan
Notes and Examples
Crucial Points
Additional Exercise
Additional Exercise Solutions
Hypothesis Testing 2 Section
Test Questions
Multiple choice section test
solutions
Hypothesis Testing Chapter
Assessment
Hypothesis testing Chapter
assessment solutions