IN THIS LESSON

Telling Visual Stories with Data

Anyone can throw data into a graph. But making a chart that actually helps people understand something important? That takes thought, strategy, and empathy.

When you visualize data, you’re not just putting numbers in boxes - you’re making choices:

  • What do you want people to notice first?

  • What should they feel, question, or even challenge?

  • What would make them stop scrolling?

Every chart is a kind of argument.

Different charts tell different kinds of stories — and some stories can only be told the right way if you pick the right form.

Choose the Right Graph …

“How much time do teens spend on different activities in a typical day?”

  • A bar graph compares categories: TikTok, school, sleep, gaming, etc. Who wins in the time race?

  • A pie chart shows proportion. What slice of your day does school take vs. leisure?

  • A stacked bar chart could compare how different students spend their 24 hours. Whose days are more balanced?

Here’s a thought: if you used a pie chart for everything, what kinds of patterns would stay hidden?

    • Compares categories

    • “How many students at your school prefer TikTok vs. YouTube?”

    • Shows trends over time

    • “How does screen time change across a school week?”

    • Shows parts of a whole

    • “What percentage of your day is spent on sleep, school, and scrolling?”

    • Explores relationships between two variables

    • “Is there a link between hours of sleep and mood?”

    • Shows frequency distributions

    • “How many students spend 0-1, 2-3, or 4+ hours on homework?”

The chart you choose should match the kind of question you’re asking.

Warning: Pie charts get messy fast. Avoid them if you have too many slices!

Labelling Axes and Titles

A chart without labels is like a song with no lyrics — people won’t know what they’re looking at.

Good charts include:

  • A clear, specific title (what’s this chart about?)

  • Labels for both axes (what’s being measured?)

  • Units (hours, %, number of people, etc.)

  • A legend, if there’s more than one dataset or color used

Watch:

Data Visualization & Misrepresentation

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  • Add a short summary or a list of helpful resources here.