GCSE STATISTICS - KS4
WHO’S WHO?
Progress Leader: Miss Sharples
Teaching Staff: Mr A Taylor
Link Governor: Mr Lyon
COURSE INFORMATION
Statistics is about making decisions when there is uncertainty. Perhaps one of the most versatile areas of maths, it gives students the skills to collect, analyse, interpret and present data. Students are introduced to the skills of statistical enquiry, and practise the underpinning statistical calculations and interpretation using real world data and authentic contexts. Our approach supports skills development for progression to a range of subjects and develops an awareness of statistics beyond the classroom. It complements subjects such as GCSE Biology, Psychology, Geography, Business and Economics, and opens the door to a variety of careers – from weather forecasting to the biological sciences.
COURSE CONTENT
• The use of statistical techniques in a variety of authentic investigations.
• Identifying trends by carrying out calculations and data visualisation techniques.
• The application of statistical techniques across the curriculum.
• Critically evaluating data, calculations and evaluations that would commonly be encountered in studies and everyday life.
• Understand how technology has enabled the collection, visualisation and analysis of large quantities of data to inform decision making, and how to generate diagrams and visualisations to represent data.
• Understand ways that data can be organised, processed and presented, including statistical measures to compare data.
• Apply appropriate mathematical and statistical formulae.
COURSE SPECIFICATION
Students follow Pearson Edexcel Level 1/Level 2 GCSE (9–1) in Statistics specification. Click here to view the specification.
COURSE ASSESSMENT
Paper 1 and Paper 2
Written examination – 50% each of the qualification – 80 marks each
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The collection of data
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Processing, representing and analysing data
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Probability
Assessment Overview
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Students must answer all questions
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The papers assess all content
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Questions on statistical methods, familiar and unfamiliar contexts and the component parts of the statistical enquiry cycle
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The papers contain short response, medium response and extended response questions
To read the tables please rotate to landscape or view on a larger screen.
YEAR
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10
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TERM
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UNIT OF STUDY
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KEY SKILLS / LEARNING
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Autumn
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Unit 1
Types of data, Population and sampling, sampling methods, Planning and collecting data
Unit 2
Qualitative and discrete data/Continuous data/Tabulation
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Primary & Secondary, Quantitative & Qualitative, Discrete and Continuous, Categorical rank, ordinal, class boundaries, grouped and ungrouped, bivariate and multivariate, independent and dependent variables.
Census, Sample data for population estimate, Sampling Frames
Petersons Data Capture, random samples and how to generate, stratified sampling, judgement, quota systemic etc.
Collecting Primary and Secondary data. Cleaning data, accuracy of data types. Pilot Surveys, Control groups, hypothesis, testing, statistics enquiry cycle
Pictograms; Bar charts; Multiple or composite bar charts for qualitative and discrete data; Vertical line graphs; Stem and leaf diagrams;
Venn diagrams; Box plots; Pie charts (including comparative pie charts); Cumulative frequency graphs;
Understand the distinction between well-presented and poorly presented data;
Understand the potential for visual misuse, by omission or misrepresentation;
Select the appropriate representation for the data; Group data
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Spring
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Unit 3
Measures of central tendency
Measures of dispersion
Box Plots, skewness and calculating and representing outliers
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mode, median and mean
range, quartiles, interquartile range, inter-percentile range, inter-decile range and standard deviation
Box plots, skew and outliers
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Summer
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Unit 4
Spearman’s Rank and Pearson’s product moment correlation coefficient
Project work
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Describing correlation by inspection, lines of best fit and Spearman’s rank correlation coefficient, Pearson’s product moment correlation coefficient
Design, plan and carry out a statistical investigation
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YEAR 11
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Autumn
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Unit 5
Calculating moving averages, seasonal and cyclic trends
Unit 6
Probability
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Plot points as a Time Series, draw a trend line by eye and use it to make predictions. Interpret seasonal and cyclic trends in context;
Calculate and use a 4-point moving average or other specified appropriate moving average;
Find the mean seasonal variation and extrapolate the data to make predictions for future years.
Simple probability and theoretical probability
Probability from two-way tables, sample space diagrams, tree diagrams and Venn diagrams
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Spring
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Unit 7
Index numbers
Unit 8
Types of distribution
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Interpreting index numbers in context and simple calculations
Binomial distribution
Normal Distribution
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Summer
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Course complete
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Revision based on mock examination question level analysis.
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ENRICHMENT OPPORTUNITIES
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Project work – practical experience of using the data handling cycle in a real-world context.
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Paris trip.
A LEVEL/BTEC REQUIREMENTS:
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Students are usually required to have a 9 - 5 pass at GCSE to study A level statistics.
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Statistics is considered an excellent support to a wide variety of subjects and disciplines such as Psychology, Biology, Chemistry, Maths, Economics, Geography, Business and medicine.
HOW TO SUPPORT YOUR CHILD'S LEARNING
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Look at newspaper articles, and discuss the use of statistics within them.
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Discuss topical news, and the statistics used to within them.
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Discuss real life graphs on the news or in papers
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Watch sport together and talk about the statistics that are used, e.g possession, expected goals.
WHERE TO GO:
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The national football museum – Manchester
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The museum of Liverpool life – Liverpool
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National railway museum - York
WHAT TO WATCH:
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The Imitation Game (2014)
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Moneyball (2011)
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The Pagemaster (1994)
WHAT TO READ:
ONLINE:
BBC Bitesize
https://www.mathsgenie.co.uk/statistics.html
https://www.mathsisfun.com/data/
https://www.worldometers.info/
https://www.statsacademy.co.uk//
FUTURE CAREERS:
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Statistics is recognised to develop learners’ cognitive, interpersonal and intrapersonal skills. Statistics can open the door to career pathways in;
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Technology – Data analyst, Data scientist, Engineer.
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Public services – Data analyst for fire, police, ambulance services.
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Health and wellness – Animal health / clinical trial / public health statistician / sport statistician.
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Environments and finance – Environmental statistician, financial analyst.