Session 8 — Tell a Data Story

Duration: 60 min · Format: live online

What you'll learn: by the end, you can run the full data cycle — ask, collect, show, tell — find one interesting thing in your data, and present a clear one-page data story. This is the Unit 2 project.

Soft skill focus — Communication

Today you'll also grow Communication. A data story is only useful if the listener actually gets the point — the "Tell" step is pure communication.

Try this: when you share your finding, see if you can say in one sentence what you just learned. If you can't, say the meaning, not just re-read the chart.

Think about: How would you explain your finding to someone who never saw your chart?

What you'll need

• The data-story steps diagram below (you'll see it on screen).
• Google Sheets open in a tab if you want to collect and chart digitally.
• Paper, a pencil, and colours ready (and your earlier survey work, if you want to reuse it).

Hook

Let's think about these — jump in with your answers (chat or unmute):

• "If I told you 'pizza got 12 votes' — is that interesting?"
• "What if I said 'pizza beat everything else — 12 out of 20 people picked it!' — better, right?"

Here's the big idea: data isn't just numbers — it can tell a story. Today you become a data storyteller.

Teach — The four-step data-story cycle

Here's how a data story works: it follows four steps. Look at this diagram as we walk through each one:

1. Ask — pick a question you care about (What game does our class love most? Cats or dogs? Favourite pizza topping?).
2. Collect — survey at least 10 people; make a neat tally or type it into Google Sheets.
3. Show — turn the counts into a chart (bar chart or pictograph) and give it a title.
4. Tell — find the interesting bit and say it in one or two sentences: "Most people chose ___." / "I was surprised that ___." / "This means ___."

⚠ Watch for the missing "Tell": it's easy to stop at the chart. Push yourself to the last step — the story (the interesting finding), which is the whole point of the project.

Think about this: "What's the difference between a chart and a data story?" (A chart shows the numbers; a data story says what the numbers mean.)

Activity — Build your data story

Your turn — run the full cycle and make a one-page data story. Here's your checklist:

• [ ] I wrote a clear question
• [ ] I collected answers from 10+ people
• [ ] I organised my data (tally or Sheets)
• [ ] I made a chart with a title
• [ ] I found one interesting thing
• [ ] I wrote my data story (1–2 sentences)
• [ ] I presented it

Work through it (share your screen or paper if you like). If you already have survey data from earlier sessions, reuse it and focus on the Show and Tell steps. Aim for a one-page data story (chart + your sentences) ready to present for about a minute.

Check yourself

Present your one-page story (about 1 minute). Then try these questions:

1. What are the four steps of a data story? → Ask, Collect, Show, Tell.
2. How many people should you survey, at least? → 10 or more.
3. What is an "insight"? → The one interesting thing you found in the data — the part worth telling.
4. Did the data surprise you? → Sometimes the answer is different from what we guessed — that's the best part of being a data detective.

Wrap-up

• Celebrate Unit 2: you've learned to collect, chart, and tell stories with data — the fuel behind every smart machine. Two units done!
• Rate your surprise-o-meter: how surprised were you by your result, from 1 (I knew it!) to 5 (whoa, no way!)?
• Try this at home: present your one-page data story to your family this week, then bring your best idea to Unit 3, where we design and build a real prototype.

Tips & extra challenges

• Watch out: don't think "the chart is the finished project." The finding you tell is the goal — the chart is just how you show it.
• Want more? Try this: write a mini data report in five short parts — Question → Data → Chart → Finding → So what? — kept to one page. Mini-challenge: turn the raw win into a percentage so the story hits harder — "Pizza won with 12 of 20 votes (that's 60%)" — using =COUNTIF to count each answer and a quick =B2/SUM(B$2:B$4) (formatted as a percent) for the share. Then write two different headlines for the same finding — one that sounds exciting and one that sounds boring — and decide which is honest. Stretch: in Google Colab, put the counts in a list and print the total, the max, and the average.

Vocabulary

Resources

• Google Sheets — collect data and make charts.
• Create a Graph — quick, colourful charts.
• Our World in Data — see how experts tell data stories.
• Google Colab — try the Python stretch (extension).

Practice set

Practise on your own — these build from easy to hard on the full data-story cycle: Ask, Collect, Show, Tell.

1. Name the steps. Put the four data-story steps in order. → Ask → Collect → Show → Tell.
2. Which step is missing? A student wrote a question, surveyed 12 people, and made a titled bar chart — then stopped. What did they skip? → The Tell step — the interesting finding, said in a sentence.
3. Chart vs. story. Turn this chart fact into a data story sentence: "Dogs 9, cats 6, fish 2." → Example: "Dogs were the clear favourite — 9 of 17 people chose them, more than cats and fish combined."
4. Find the insight. Data: reading 3, gaming 11, sport 4. What's the one interesting thing worth telling? → Gaming was by far the most popular — it beat reading and sport put together.
5. Spreadsheet task. Answers are listed in D2:D21 (20 people). Write the formula to count how many chose "pizza," then say how you'd turn that into a percentage of 20. → =COUNTIF(D2:D21,"pizza"); divide that count by 20 (e.g. =COUNTIF(D2:D21,"pizza")/20, formatted as a percent).
6. Write the report (hard). Using data pizza 12, pasta 5, salad 3 (20 people), write a five-part mini report: Question → Data → Chart → Finding → So what? → Example: Question: "Best party food?" Data: surveyed 20 people. Chart: bar chart, titled. Finding: pizza won with 12 of 20 votes (60%). So what: we should order mostly pizza for the party.

Going deeper (optional)

Optional — for a challenge. A good data storyteller checks whether their finding is fair to report, because a small or lopsided survey can tell a misleading story. Ask your own result two "detective" questions: How many people did I actually ask? and Who did I ask? Here's an example — if you survey only 4 people and 3 like football, saying "most kids love football" is a stretch, because 4 people can't speak for the whole school, and if all 4 were on the football team the sample was lopsided from the start. Add a small honest line to your story: "I asked ___ people, all from ___." This doesn't ruin your finding — it makes it trustworthy, and it quietly plants the ideas of sample size and bias you'll meet again later.

Common mistakes & fixes

If it's not working, check these:

• Mistake: stopping at the chart and never saying what it means (skipping "Tell"). → Fix: write a one-sentence finding for every project — "Most people chose ___" or "I was surprised that ___."
• Mistake: surveying too few people, then claiming it speaks for everyone. → Fix: keep the 10+ people rule and add an honest line about how many you asked.
• Mistake: a "finding" that just re-reads the chart ("pizza got 12") instead of interpreting it. → Fix: go for the so what — compare, surprise, or conclude ("pizza beat everything else combined").
• Mistake: presenting a chart with no title, so the audience is lost. → Fix: check the title before presenting — the audience must know what the numbers are about.
• Mistake: changing the data to make the story more exciting. → Fix: remember honesty — a data story reports the real result, even when it's not the one you hoped for.

What's next

Unit 3 — Build Something Real: the grand finale — design thinking, build a prototype, and present your very own invention.