GMC5: Processing data
This list contains a collection of resources to help meet General Mathematical Competency 5 (GMC5). More resources to support T level Science can be found on our T Level science resource packages page.
GMC5 states:
Students should:
- Be able to analyse the quality of the data, including how the data have been processed and scaled: were there sufficient data to draw valid conclusions? Students should demonstrate an understanding that data processing procedures and outputs should be interrogated and interpreted critically against anatomy and physiology knowledge
- Understand the stages of data handling and processing:
- collect
- record
- analyse
- interpret
- Understand the difference between qualitative and quantitative data:
- qualitative - subjective, categorical data that approximates and characterises
- quantitative - objective, measurable data that can be defined as a value
- Be able to find, and understand when to use, different averages: mode, mean and median
- Be able to find, and understand when to use, different measures of spread in data such as range and standard deviation
Designing questionnaires
This activity covers the key points to consider when designing an effective questionnaire.
It is suitable for a whole-class introduction to the topic, providing ample opportunities for group discussion. The practical task enables students to design their own questionnaires.
The presentation covers why questionnaires are used, what makes a good question and how bias can be recognised.
Types of data
This task consists of a presentation that explains and reviews the distinctions between different types of data. It explains the difference between the following categories of data:
- qualitative and quantitative
- discrete and continuous
- primary and secondary
The teacher guidance includes an overview of the task, suggested approaches and possible extension activities.
Body temperature
This task asks the question ‘How do you know if you are really unwell?’
The activity explores the data surrounding body temperature, shows how to summarise continuous data and explores the effect on summary statistics that changing the size of the class interval has.
Anthropometric data
In this task, based on a resource developed by the Nuffield Foundation, students are given a large dataset of children’s and young adults’ anthropometric data to use to investigate whether particular sets of data are related. The students are asked to present their findings in the form of a report/presentation, with the opportunity to use spreadsheet software to present data.
Population Data
This resource contains seven activities related to population statistics.
Data Assessment is fourteen pages of questions to be used a test of the topics covered in the seven lessons.
Population Change Information Sheet is an extensive document which can be made available or use by students.
Lesson 1 covers what social scientists call the Demographic Transition Model. This analyses the relationship between birth rates, death rates and population growth, and how all of these tend to vary as a country becomes more developed. Students need to interpret and draw bar charts showing the relative size of different age groups within populations. They also need to draw line graphs.
Lesson 2 is concerned with how we can select a fair sample? Sampling methods covered are random, systematic, cluster sampling, stratified and quota sampling. Data used is recent population data of the 196 countries of the world. Students are encouraged to see that the real challenge of sampling is to devise the smallest sample size that will yield reliable results.
Lesson 3 deals with diagrams representing data. It examines the difference between birth and death rate in different countries. Students need to use a sampling process then draw various types of bar chart and radar diagram. They are asked to compare the diagrams drawn from their sample of data with the full data set illustrated in the presentation. Teacher notes within the presentation give support and advice about the lesson.
Lesson 4 explains how the standard deviation is calculated and what it can be used for. The presentation gives a clear explanation of the process by showing calculations of the standard deviation of the birth rates and death rates for European countries. Students then do a similar process on samples of countries from other continents using their own samples.
Lesson 5 deals with correlation. A possible correlation between birth rate and death rate is sought but not found. Countries from the different continents are shown in different colours in the various diagrams. The correlation between infant mortality rate and birth rate in a sample of African countries is shown and examples of interpolation given. Students need to use the World Population Data Sheet or other sources of population data.
Lesson 6 deals with cumulative frequency and comparison of cumulative frequency curves. The data is from the World Population Data Sheet and box plots are shown as a way of comparing sets of data. Range and inter-quartile range are explained and used to show differences between European and African birth and death rates.
Lesson 7 focuses on the construction and use of histograms. Frequency density is explained and students are shown why frequency density is used rather than frequency. The presentation uses histograms to compare sets of data as are box plots and cumulative frequency curves.
Understanding Mean, Median, Mode and Range S4
In this resource, students learn to understand the terms: mean, median, mode, range and explore the relationships between these measures and their relationship to the shape of a distribution. Students will have met the terms mean, median, mode and range but they may not have a clear understanding of their meaning and the relationships between them. One purpose of this session is to expose and discuss any misconceptions.
