Lesson 8: Drawing Conclusions
Answering your original question using the evidence you found.
🎯 Learning Intentions
- Interpret data to make statements
- Write a conclusion that directly answers the investigative question
- Identify limitations in the data
🎥 Media Anchor (8 mins)
Video: Research Skills for Students
- What level of evidence is enough to support a class conclusion?
- How do we avoid over-claiming from a small sample?
1. "I Notice, I Wonder" (10 mins)
Look at your graphs and tables. Complete these sentences:
- "I notice that most students..."
- "I notice that the difference between..."
- "I wonder why..."
Example: "I notice that 80% of students bring lunch from home. I wonder if this changes in winter?"
2. Structure of a Conclusion (15 mins)
A good conclusion has three parts:
- Claim: The answer to your question. ("Year 8 students prefer rugby over soccer.")
- Evidence: The numbers backing it up. ("My data shows 15 students chose rugby, while only 5 chose soccer.")
- Meaning: What does this mean in context? ("This suggests rugby is the dominant sport culture in our class.")
3. Task: Draft your Conclusion (20 mins)
Write your conclusion paragraph.
Checklist:
- Did I mention specific numbers?
- Did I answer my specific I-V-G question?
- Is it true based on my data?
4. Evaluation (5 mins)
Reflection: What could you have done better?
- "My sample size was too small."
- "My question was confusing."
- "I only asked my friends."
Admitting mistakes is part of good science!
Curriculum alignment
- Materials — Practices: Investigating how materials change shape in response to forces and relating the difference between temporary and permanent shape changes using evidence about material properti…
- Materials — Knowledge: Suspensions are not solutions, and the components may separate over time depending on particle size.
- Organism Diversity — Knowledge: These differences mean that some orgabnisms within the same species are better adapted to their environment than others.
- Organism Diversity — Practices: Evaluating evidence from case examples to infer how adaptation contributes to evolutionary change (e.g. beak shape changes in finch populations over generations, light and dar…
- Materials — Knowledge: In any state of matter, particles don’t change size, and there is no matter between the particles — only empty space.
📋 Teacher Planning Snapshot
Ngā Whāinga Ako — Learning Intentions
Students will engage with this resource to develop statistical investigation skills — planning inquiries, collecting and analysing data, interpreting distributions, and communicating findings. Tūhuratanga (investigation) is framed as a tool for understanding our communities and environment in Aotearoa New Zealand.
Ngā Paearu Angitū — Success Criteria
- ✅ Students can identify an investigative question, collect relevant data, and display it clearly.
- ✅ Students can interpret statistical findings and discuss what they might mean for a real-world community or environmental context.
Differentiation & Inclusion
Scaffold support: Provide structured investigation frameworks (PPDAC cycle templates) for entry-level access. Offer partially completed data tables for students who need additional support. Extend capable learners by asking them to critique a statistical claim from a news article, or to design their own community data investigation.
ELL / ESOL: Pre-teach statistical vocabulary (median, mode, range, distribution, sample, population). Pair visual representations (graphs, tables) with plain-language explanations. Allow students to discuss statistical ideas orally before writing. Encourage use of home language for initial sensemaking.
Inclusion: Statistical investigation offers natural differentiation — all students can engage with the same real-world question at different levels of mathematical complexity. Neurodiverse learners benefit from structured, step-by-step investigation processes. Use collaborative group investigation formats that distribute roles (data collector, recorder, analyst, presenter).
Mātauranga Māori lens: Tūhuratanga — the practice of careful investigation — resonates deeply with mātauranga Māori. The maramataka is a sophisticated data system: tracking environmental patterns, seasonal cycles, and ecological indicators over generations. Iwi environmental monitoring — counting kaimoana populations, tracking water quality, observing bird migrations — is applied statistical thinking. Framing statistics within community and environmental inquiry connects data to mana whenua responsibilities.
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
- Statistics — Statistical Investigation: Plan and conduct investigations using the statistical enquiry cycle — determining appropriate variables and data collection methods; gathering, sorting, and displaying multivariate category, measurement, and time-series data to detect patterns, variations, relationships, and trends; comparing distributions visually; communicating findings, using appropriate display.
- Statistics — Probability: Investigate situations that involve elements of chance by comparing experimental distributions with expectations from models of the possible outcomes, acknowledging uncertainty.