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The content for this section is sub-divided
into the following areas:
Specifying the problem and planning
Top
| Content |
Resources |
| see
that random processes are unpredictable
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| identify
key questions that can be addressed by statistical
methods |
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| discuss how data relate to a problem |
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| identify possible sources of bias and
plan to
minimise it |
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| select and justify a sampling scheme
and a
method to investigate a population,
including
random and stratified
sampling |
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| identify which primary data they need to collect
and in what format, including grouped
data, considering appropriate equal
class intervals |
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| design an experiment or survey decide
what primary and
secondary data to use. |
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Collecting data
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| Content |
Resources |
| design
and use data-collection sheets for grouped
discrete and continuous data
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N
W
questionnaires |
| collect data using various methods, including
observation, controlled experiment,
data logging, questionnaires and
surveys |
W
class questionnaire
W
letters
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| gather data from secondary sources, including
printed tables and lists from ICT-based
sources |
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| design and use two-way tables for discrete and
grouped data.
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| deal with practical problems such as non-response
or missing data |
W
two way tables |
Processing and representing data
Top
| Content |
Resources |
| draw
and produce, using paper and ICT, pie
charts for categorical data, and diagrams
for continuous data, including line
graphs for time series, scatter graphs, frequency
diagrams and stem-and-leaf diagrams, cumulative
frequency tables and
diagrams, and
box plots
and
histograms for grouped continuous
data
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N
W
O
W W
B
pie charts W
bar charts and pie charts (Answers) O
W scatter
graphs W
cumulative frequency (Answers) W
W
W
cumulative frequency |
| calculate mean, range and median of small data
sets with discrete then continuous data |
O
W
averages |
| identify the modal class for grouped data |
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| understand and use the probability scale |
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| understand and use estimates or measures of
probability from theoretical models (including
equally likely outcomes), or
from
relative frequency |
W
probability |
| list all outcomes for single events, and for two
successive events, in a systematic way |
W
possibility space |
| identify different mutually
exclusive outcomes and know that the sum of
the probabilities
of all these outcomes is 1 |
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| know when to add or multiply two probabilities:
if A and B are mutually exclusive, then the probability of A or
B occurring is P(A) + P(B), whereas if A and
B are independent events, the probability of A and B occurring is P(A) x P(B) |
W
and/or rules |
| use tree
diagrams to represent outcomes of
compound events, recognising
when events
are independent |
W
tree diagrams |
| find the median, quartiles and interquartile
range for large data sets and
calculate the mean for large data sets
with grouped data |
O
W
averages from frequency tables
O
W
averages from grouped frequency tables
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| calculate
an appropriate moving average |
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| draw
lines of best fit by eye, understanding
what these represent.
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| use relevant statistical functions on a
calculator or spreadsheet. |
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Interpreting and discussing results
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| Content |
Resources |
| relate
summarised data to the initial questions
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| interpret a wide range of graphs and diagrams
and draw conclusions |
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| identify seasonality and trends in time
series |
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| look at data to find patterns and
exceptions |
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| compare distributions and make inferences,
using the shapes of distributions
and measures of average, range and
spread, including
median and quartiles |
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| understand
frequency density |
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| consider and check results, and modify their
approach if necessary |
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| have a basic understanding of correlation as
a measure of the strength of the association
between two variables |
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| identify correlation or no correlation using lines
of best fit |
W
scatter graphs (Answers) |
| distinguish between positive, negative and
zero correlation |
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| appreciate that zero correlation does not necessarily imply ‘no
relationship’ but
merely ‘no linear relationship |
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| use the vocabulary of probability to interpret
results involving uncertainty and prediction |
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| compare experimental data and theoretical probabilities |
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| understand that if they repeat an experiment,
they may – and usually will – get
different outcomes, and that increasing sample
size generally leads to better estimates
of probability and population characteristics |
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| discuss implications of findings in the context
of the problem |
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| interpret social statistics including
index numbers, the
General Index of Retail Prices time
series population growth and
survey data. |
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