Edexcel GCSE 200 Statistics (Higher)

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Scheme of work

This scheme of work has been produced to help you implement this Edexcel specification. It is offered as an example of one possible model that you should feel free to adapt to meet your needs and is not intended to be in any way prescriptive. It is in editable word format to make adaptation as easy as possible.

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Statistics (Higher) — Edexcel scheme of work

Content/
Prior knowledge/
Time allowed / Learning objectives / Differentiation and extension / Resource / Homework / Exemplar resources
Module 1: 1b
PRIOR KNOWLEDGE
GCSE Mathematics Higher Module 1- Collecting data
Time allowed: 1 hr /
  • Recognise that data can be obtained from primary and secondary sources.
  • Recognise the difference between quantitative and qualitative variables.
  • Recognise the difference between discrete and continuous data.
  • Recognise and use scales of measurement- categorical, rank.
  • Categorise data through the use of well-defined, precise definitions or class boundaries.
  • Appreciate the implication of grouping for loss of accuracy in presentations.
  • Understand, use and define situations for grouped and ungrouped data.
  • Understand the meaning of bi-variate data which may be discrete, continuous, grouped or ungrouped.
/
  • Use other scales for data, eg ordinal scale, ratio scale.
  • Make a list of possible pairs of bi-variate data, eg height v weight.
  • Categories are range of variables from a variety of everyday contexts.
/ Pearson/Edexcel GCSE Statistics textbook Chapterx / Homework at each stage could comprise consolidation of work in class by completion of exercises set, additional work of a similar nature, or extension work. /
  • Written testing to assess knowledge of content.
  • Plan and collect data for coursework.
  • Primary sources should include raw data, surveys, questionnaires (which may have more than two categories), investigations and experiments.
  • Secondary sources include databases, published statistics, newspapers, internet pages, etc.
  • The use of terms such as class width and class interval is expected.
  • Plotting and interpreting points in a 2D frame work is expected.
  • Aspects of this module will be enhanced by practical applications of the theory.

Content/
Prior knowledge/
Time allowed / Learning objectives / Differentiation and extension / Resource / Homework / Exemplar resources
Module 2: 1c Population sampling
PRIOR KNOWLEDGE
GCSE Statistics Higher Module 1- Types of data
Time allowed: 1-2 hrs /
  • Understand the meaning of the term population.
  • Understand the word census with regard to small scale and large scale populations.
  • Understand the reasons for sampling and that sample data is used to estimate values in a population.
  • Understand the terms random, randomness and random sample.
  • Understand the use of random numbers.
  • Understand, design and use a sampling frame.
  • Be able to select a random sample or stratified sample by one (and more than one) category as a method of investigating a population.
  • Appreciate how bias in a sampling procedure might occur and how it might be minimised.
  • Understand and use systematic, quota and cluster sampling.
  • Understand the strengths and weaknesses of various sampling methods, including bias, influences and convenience.
/
  • Discuss the size of the sample needed for particular sampling procedures.
  • Discuss the feasibility of taking a census in large populations.
/ Pearson/Edexcel GCSE Statistics textbook Chapterx / Homework at each stage could comprise consolidation of work in class by completion of exercises set, additional work of a similar nature, or extension work /
  • Written testing to assess knowledge of content.
  • Plan and collect data for coursework.
  • Random numbers may be collected from random number tables, calculators and spreadsheets.
  • An appreciation of an appropriate sample size is expected.
  • Designing a sample frame is expected.
  • Understanding of the National Census is expected.
  • Understand the types of question used for a census and how the collected data is used.

Content/
Prior knowledge/
Time allowed / Learning objectives / Differentiation and extension / Resource / Homework / Exemplar resources
Module 3 1d Collecting data/primary data
PRIOR KNOWLEDGE:
GCSE Statistics Higher Module 2- Population and sampling
Time allowed: 2-3 hrs /
  • Collect or obtain data using a variety of methods (see notes).
  • Obtain primary data by questionnaires and experiments or simulations.
  • Understand the effects of accuracy on measurements.
  • Understand the advantages and disadvantages of using interviews versus questionnaires.
  • Design and use effective data capture sheets and methods of recording data.
  • Understand the role, and use of pilot studies and pre-testing.
  • Understand and account for the problems of design, ambiguity of wording, leading questions, definitions and obtaining truthful responses with simplest form of random response in sensitive cases.
  • Understand the advantages and disadvantages of open and closed questions.
  • Be aware of the problems related to identifying the appropriate population, the distribution and collection of surveys, errors in recorded answers, non-response and missing data.
  • Design simple statistical experiments to obtain data.
  • Understand the need for identification of the variables to be investigated and the meaning of explanatory and response variables.
/
  • Investigate the collection of primary data in the real world, eg tax return, passport application, National Census.
  • Investigate how the manner of an interview could affect the outcome (eg, students role-play interviews).
  • Investigate a leading question – to what extent does it affect the response?
  • Investigate psychometric testing.
/ Pearson/Edexcel GCSE Statistics textbook Chapterx / Homework at each stage could comprise consolidation of work in class by completion of exercises set, additional work of a similar nature, or extension work /
  • Written testing to assess knowledge of content.
  • Plan and collect data for coursework.
  • Data collection to include: surveys, experiments (including controlled experiments), counting, data logging, convenience sampling, questionnaires and measurement.
  • Measurement of data to include an appreciation that the measurement of continuous variables such as time and length is subject to some error.
  • The minimisation of ambiguity and bias is expected.
  • Students should be able to comment on the design of simple experiments, eg the use of controls.

Content/
Prior knowledge/
Time allowed / Learning objectives / Differentiation and extension / Resource / Homework / Exemplar resources
Module 4: 1d Collecting data/secondary data
PRIOR KNOWLEDGE:
GCSE Mathematics Higher Module 1- Collecting data
GCSE Statistics Higher Module 3- Collecting primary data
Time allowed:1-2 hrs /
  • Identify appropriate sources of secondary data.
  • Extract data from secondary sources, including those based on ICT.
  • Understand the aspects of accuracy, reliability, relevance and bias as related to secondary data.
  • Understand surveys and the appropriateness of the conditions.
/
  • Investigate the reliability of data collected from different sources, eg the internet, news papers, etc.
  • Compare the data collected from different sources, eg sporting statistics, historic dates, etc.
  • Investigate the misuse of quoted statistics in the media.
/ Pearson/Edexcel GCSE Statistics textbook Chapterx / Homework at each stage could comprise consolidation of work in class by completion of exercises set, additional work of a similar nature, or extension work /
  • Written testing to assess knowledge of content.
  • Plan and collect data for coursework.
  • Questioning the reliability of secondary data will be expected.
  • Appropriate sources of secondary data to include: newspapers; Office of National Statistics; internet, etc.

Module 5: 2a Tabulation
PRIOR KNOWLEDGE:
GCSE Mathematics Higher Module 1- Collecting data
GCSE Statistics Higher Module 1- Types of data
Time allowed 1-2 hrs /
  • Construct frequency tables by tallying raw data were appropriate, including open- ended class intervals and classes of varying width.
  • Tabulate using class intervals for discrete and continuous data.
  • Tabulate using various forms of grouping the data, including qualitative or quantitative categories.
  • Combine categories to simplify tables with an understanding of the problems of over simplification, the effects on readability, the identification or masking of trends and the loss of detail.
  • Problems associated with under and over simplification through inappropriate number of significant figures or an unsuitable group size.
  • Read and interpret data presented in tabular or graphical form.
  • Design suitable tables, including summary tables and two-way tables.
/
  • Further examples of tables to collect and/or summarise information in the real world.
  • Compare different methods of tabulating data for ease of use.
  • Tabulate data with two or more characteristics, eg choropleth tables.
/ Pearson/Edexcel GCSE Statistics textbook Chapterx / Homework at each stage could comprise consolidation of work in class by completion of exercises set, additional work of a similar nature, or extension work /
  • Written testing to assess knowledge of content.
  • Present and interpret data collected for coursework.
  • Students should be able to list outcomes from single or two successive events.

Content/
Prior knowledge/
Time allowed / Learning objectives / Differentiation and extension / Resource / Homework / Exemplar resources
Module 6: 2b Diagrams and representations/
dicrete data
PRIOR KNOWLEDGE:
GCSE Mathematics Higher Module 2 - Charts and graphs
GCSE Statistics Higher Module 1 - Types of data
Time allowed: 3-4 hrs /
  • Construct, draw, use and understand
Pictograms
Bar charts
Multiple or composite bar charts for qualitative, quantitative and discrete data and comparative pie charts with area proportional to frequency
Vertical line (stick) graphs for discrete data and cumulative frequency step polygons
Stem and leaf diagrams
Choropleth maps.
  • Identify simple properties of the shape of distributions of data including symmetry, positive and negative skew.
  • Understand the distinction between well-presented and poorly presented data.
  • Understand the potential for visual misuse, by omission or misrepresentation.
  • Transform from one presentation to another.
  • Understand how to discover errors in data and recognise data that does not fit a general trend or pattern, including outliers.
/
  • Further examples of these graphs (particularly graphs used for comparison), eg back-to-back stem and leaf diagrams.
  • Investigate the misrepresentation of statistics in the media.
  • Compare information presented in different forms, eg stem and leaf v bar chart.
/ Pearson/Edexcel GCSE Statistics textbook Chapterx / Homework at each stage could comprise consolidation of work in class by completion of exercises set, additional work of a similar nature, or extension work /
  • Written testing to assess knowledge of content.
  • Present and interpret data collected for coursework.
  • Students should be able to list outcomes from single or two successive events.
  • Reasons for choosing a particular form of representation are expected.
  • Comparative line graphs are expected.
  • Analytical definitions of an outlier will be expected.
  • For box plots see Module 9.

Content/
Prior knowledge/
Time allowed / Learning objectives / Differentiation and extension / Resource / Homework / Exemplar resources
Module 7: 2b Diagrams and Representations continuous data
PRIOR KNOWLEDGE:
GCSE Mathematics Higher Module 2- Charts and graphs
GCSE Mathematics Higher Module 8- Histograms
GCSE Statistics Higher Module 6- Diagrams and representations (discrete data)
Time allowed: 3-4 hrs /
  • Construct, draw, use and understand
Pie charts
Histograms with equal and unequal class intervals and the concept of frequency density
Frequency diagrams
Cumulative frequency diagrams
Population pyramids
Stem and leaf diagrams.
  • Identify simple properties of the shape of distributions of data including symmetry, positive and negative skew.
  • Transform from one presentation to another.
  • Understand that many populations can be modelled by the Normal distribution.
  • Understand how to discover errors in data and recognise data that does not fit a general trend or pattern, including outliers.
/
  • Further examples of these graphs (particular graphs used for comparison), eg cumulative frequency diagrams used for comparison, Normal distributions, etc.
  • Investigate the misrepresentation of graphs used to represent continuous data in the media or on the Internet.
/ Pearson/Edexcel GCSE Statistics textbook Chapterx / Homework at each stage could comprise consolidation of work in class by completion of exercises set, additional work of a similar nature, or extension work /
  • Written testing to assess knowledge of content.
  • Present and interpret data collected for coursework.
  • Students should be able to list outcomes from single or two successive events.
  • Reasons for choosing a particular form of representation are expected.
  • Comparative line graphs are expected.
  • Analytical definitions of an outlier will be expected.
  • For box plots see Module 9.

Content/
Prior knowledge/
Time allowed / Learning objectives / Differentiation and extension / Resource / Homework / Exemplar resources
Module 8: 2c Measures of Central Tendency 2i Estimation
PRIOR KNOWLEDGE:
GCSE Mathematics Higher Module 5- The mean (large data sets)
GCSE Mathematics Higher Module 7- Median and interquartile range (large data sets)
GCSE Statistics Higher Module 1- Types of data
Time allowed: 3-4 hrs / Convert raw data to summary statistics, design, construct and present summary tables.
  • Work out the mean, median and mode of
-raw data presented as a list
-discrete data presented as a frequency distribution.
  • Identify the modal class interval for grouped frequency distributions for discrete and continuous data.
  • Work out and use estimates for the mean and median of grouped frequency distributions for discrete and continuous data.
  • Understand the effects of transformations of the data on the mean, mode and median.
  • Understand the effect on the mean, mode and median of changes in the data including the addition or withdrawal of a population or sample member.
  • Understand the appropriateness, advantages and disadvantages of each of the three measures of central tendency.
  • Be able to make a reasoned choice of a measure of central tendency appropriate to a particular line of enquiry, nature of data and purpose of the analysis.
  • Calculate and use a weighted mean.
  • Understand that increasing sample size generally leads to better estimates of population parameters.
  • Estimate population means from samples.
  • Estimate population proportions from samples with applications in opinion polls and elsewhere.
  • Estimate population size based on the Peterson capture/recapture method.
  • Understand the effect of sample size on estimates and the variability of estimates, with a simple quantitative appreciation of appropriate sample size.
/
  • Use box plots to compare heights of students in each year group of the school.
  • Investigate the use of percentile range in real-world statistics.
  • Investigate the optimal sample size required in Peterson’s capture/ recapture method
  • Calculate a weighted mean in a practical context.
/ Pearson/Edexcel GCSE Statistics textbook Chapterx / Homework at each stage could comprise consolidation of work in class by completion of exercises set, additional work of a similar nature, or extension work /
  • Written testing to assess knowledge of content.
  • No more than 30 numbers in a list will be examined.
  • Graphical and other methods for the median are expected.
Transformation of data will be of the form
x  ax + b
 and notation is expected.
Content/
Prior knowledge/
Time allowed / Learning objectives / Differentiation and extension / Resource / Homework / Exemplar resources
Module 9: 2d Measures of dispersion
PRIOR KNOWLEDGE:
GCSE Mathematics Higher Module 7- Median and interquartile range (Large data sets)
GCSE Statistics Higher Module 1- Types of data
GCSE Statistics Higher Module 8- Measures of central tendency
Time allowed: 2- 3 hrs /
  • Convert raw data to summary statistics, design, construct and present summary tables.
  • Work out and use the range for data presented in a list or frequency distribution.
  • Work out the quartiles, percentiles and interquartile range for discrete and continuous data presented either as a list, frequency table or grouped frequency table.
  • Construct, interpret and use box plots.
  • Formally identify outliers.
  • Calculate and use variance and standard deviation.
  • Understand the advantages and disadvantages of each of the measures of dispersion, range, quartiles, interquartile range, percentiles, deciles, interpercentile range, variance and standard deviation.
  • Use an appropriate measure of central tendency together with range, quartiles, interquartile range, percentiles, deciles, interpercentile range, variance and standard deviation to compare distributions of data.
  • Calculate, interpret and use standardised scores to compare values from different distributions.
  • Understand how to discover errors in data and recognise data that does not fit a general trend or pattern, including outliers.
/ Use a spread sheet to calculate standard deviation