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Beginner · module B7

Data Literacy and Visualisation

By the end: Collect and organise data, summarise it with simple measures, choose the right chart, and spot misleading data

Covers
Reading, questioning, summarising and presenting data, the skill every AI user needs
Contents
4 chapters, 18 topics
Time
About 2 hours
Level
Beginner
Your progress
0 / 18

This module builds on How Artificial Intelligence Works: Data and Learning. We suggest looking at it first, but the choice is yours.

Chapter 1 Foundations of Data Literacy

  1. 1.1

    What Is Data Literacy?

    Reading, questioning and using data to make decisions

    Discussion: one headline, two interpretations

    6 minBeing written
  2. 1.2

    The Data Literacy Process

    Ask, collect, organise, analyse, interpret and communicate

    Interactive: put the steps in order

    8 minBeing written
  3. 1.3

    Primary and Secondary Data

    Data you collect compared with data collected by others

    Card sort

    6 minBeing written
  4. 1.4

    Designing Good Survey Questions

    Clear, fair questions that do not lead the answer

    Interactive: fix the biased questions

    8 minBeing written
  5. 1.5

    Sample and Population

    Why a small group can represent a large one, and when it cannot

    Unplugged: group survey

    8 minBeing written

Chapter 2 Summarising Data

  1. 2.1

    Frequency Tables and Tally Marks

    Counting and organising raw data

    Unplugged: car spotting

    6 minBeing written
  2. 2.2

    Averages: Mean, Median and Mode

    Three ways to describe a typical value, and when each one misleads

    Interactive: find the typical value

    10 minBeing written
  3. 2.3

    Spread of Data: Range

    How far data is spread, and why the average alone is not enough

    Interactive: compare two sets with the same average

    6 minBeing written
  4. 2.4

    Chance and Probability in Everyday Life

    What "70 per cent chance of rain" means, and chance in AI predictions

    Experiment: toss a coin fifty times

    10 minBeing written

Chapter 3 Visualising Data

  1. 3.1

    Parts of a Graph

    Title, axes, labels, scale and legend

    Interactive: label the parts

    6 minBeing written
  2. 3.2

    Bar Graphs, Line Graphs and Pie Charts

    What each chart shows best

    Interactive: make each chart from one dataset

    10 minBeing written
  3. 3.3

    Choosing the Right Chart

    Matching the chart to the question

    Interactive: pick the chart for each question

    6 minBeing written
  4. 3.4

    Misleading Charts

    Cut axes, cherry-picked data and confusing scales

    Interactive: spot the trick

    8 minBeing written
  5. 3.5

    Dashboards

    Several charts together to answer a question

    Spreadsheet lab: build a simple dashboard

    15 minBeing written

Chapter 4 Data in the Real World

  1. 4.1

    Big Data in Simple Terms

    Volume, velocity and variety, with everyday examples

    Discussion

    6 minBeing written
  2. 4.2

    Data Storytelling

    Turning numbers into a clear message with a beginning, middle and end

    Activity: tell a story from school-meal data

    10 minBeing written
  3. 4.3

    Data Privacy and Data Security

    Keeping data private and safe, and what happens in a data breach

    Case study discussion

    8 minBeing written
  4. 4.4

    Module Review and Assessment

    Recap of the module with a scored quiz

    Module quiz with explanations

    10 minBeing written