Lesson 10: Investigation Project

Final assessments and sharing our statistical discoveries.

🎯 Learning Intentions

Present final statistical investigation
Reflect on the PPDAC cycle
Demonstrate understanding of the statistical enquiry process

🎥 Media Anchor (8 mins)

Video: Effective Presentations

Which evidence slide best proves your final conclusion?
What feedback question will improve your next investigation cycle?

1. Presentations (30 mins)

Students present their findings to the class or small groups.

Audience Responsibility: Ask one question about the data or method. (e.g., "Why did you choose a bar graph?")

2. Self-Assessment (10 mins)

Rate your own investigation using the rubric:

Problem: Is the question clear?
Plan: Was the method sound?
Data: Is it precise?
Analysis: Are graphs accurate?
Conclusion: Is the answer supported by evidence?

3. Final Whakataukī Reflection (5 mins)

Recall: "He aha te mea nui o te ao? He tangata, he tangata, he tangata."

Discuss: How did your investigation help you understand people better?

(e.g., "I learned that most people in our class worry about climate change, which connects us.")

4. Unit Wrap Up (5 mins)

Congratulations! You are now statistical detectives. You know how to question the numbers you see in the news and social media.

Return to Unit Overview

📋 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.