Seminar focus: interrogate a data story
Use the human graph and Stats NZ examples as common texts for a facilitated discussion. Ākonga separate observation from interpretation, challenge assumptions, and revise one claim when the evidence does not support it.
- Seminar move: Notice–interpret–challenge protocol with accountable talk prompts
- Seminar outcome: A revised claim explaining what the data shows and what remains unknown
🎯 Learning Intentions
- Understand what statistics are and why we use them
- Recognise the difference between data and information
- Explore how statistics tell stories about people in Aotearoa
🎥 Media Anchor (8 mins)
Video: Research Skills for Students
- What makes a statistical question useful for real decision-making?
- Name one way data can be misread if the question is weak.
1. Hook: Data Detective (10 mins)
What does data tell us about our class?
Activity: Quick class census. Ask 3 questions (e.g., favourite kai, transport to school, iwi affiliation). Create a live human graph.
Ask: "What does this 'picture' tell us that a list of names doesn't?"
2. Concept: The PPDAC Cycle (15 mins)
Introduce the PPDAC Cycle which guides all statistical investigations:
- Problem (Pātai) - Asking the question
- Plan (Mahere) - Deciding how to get answers
- Data (Raraunga) - Collecting information
- Analysis (Tātari) - Looking for patterns
- Conclusion (Whakatau) - Answering the question
Metaphor: Like detective work, we need a process to solve the mystery.
3. Exploration: Stats NZ (20 mins)
Activity: Visit the Stats NZ website.
Find one interesting fact about:
- Population of Aotearoa
- The environment
- Māori wellbeing
Discuss: "How does the government use this information to make big decisions?"
4. Reflection (5 mins)
Exit Ticket: Write down one question you have about our school that data could help answer.
(e.g., "Do Year 8s eat healthier lunches than Year 7s?")
📋 Teacher Planning Snapshot
Ngā Whāinga Ako — Learning Intentions
Ākonga argue about what statistics is for, working from one dataset the whole class can see.
Ngā Paearu Angitū — Success Criteria
- ✅ I can say what a statistical question needs in order to be answerable.
- ✅ I can judge whether a claim someone makes is supported by the data shown.
Differentiation & Inclusion
Scaffold support: A shared dataset displayed large enough for the whole class to argue over. Extension: bring a statistical claim from the news for the class to test.
ELL / ESOL: Statistical vocabulary introduced as the class needs it in the argument, not front-loaded.
Inclusion: Every ākonga states a position before discussion opens, so the confident do not set the frame.
Mātauranga Māori lens: The maramataka is a data system built by generations of recorded observation. This week's question — what is worth investigating — is the same question its keepers answered.
Prior knowledge: Students should have basic familiarity with data displays (bar graphs, dot plots). No prior statistical investigation experience required — the PPDAC inquiry cycle provides accessible scaffolding for first-time investigators.
Curriculum alignment
This lesson develops the Level 4 statistical-investigation objective through a real stage of the PPDAC cycle. See the unit curriculum companion for the exact source statement and lesson-to-evidence map.