📚 Unit Plans → 🌍 Year 8 Community Data Inquiry Studio — Rangahau Tauanga
Years 7–8 Pāngarau / Mathematics

Community Data Inquiry Studio — Rangahau Tauanga

Ten project checkpoints: frame one useful local question, gather trustworthy data, find its story, and share an evidence-based conclusion.

Choose your teaching approach · Community Data Inquiry Studio

Build one investigation through the full PPDAC cycle

This studio route teaches the same ten statistical concepts as the seminar edition, but teams carry one locally relevant question from first proposal to final presentation. Each lesson adds a usable piece to a cumulative investigation portfolio.

Prefer structured discussion and claim critique? Open the Statistical Reasoning Seminar →
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Duration

10 lessons

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Year Level

Year 8 (Level 4)

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Subject

Mathematics & Statistics

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Focus

PPDAC Cycle

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

What is the greatest thing in the world? It is people, people, people.

Statistics help us understand people — their needs, experiences, and stories told through data.

📋 Unit Overview

In this unit, ākonga conduct one authentic statistical investigation using the PPDAC cycle. Each lesson moves the same project forward: they pose a question, plan ethical data collection, gather and clean data, choose useful displays, analyse variation, and communicate a conclusion to an audience who can use it. The unit is designed around action and evidence, not a sequence of disconnected worksheets.

Learning Outcomes

  • Pose investigative questions that can be answered with data
  • Plan and conduct data collection (surveys, experiments, existing data)
  • Organise data using tables, graphs, and digital tools
  • Analyse data using measures of centre (mean, median, mode) and spread
  • Draw conclusions and communicate findings clearly
  • Consider ethical aspects of data collection and use

🔄 The PPDAC Cycle

Statistical investigation follows a cycle:

Problem

Pose a question

Plan

Design the investigation

Data

Collect information

Analysis

Explore patterns

Conclusion

Answer the question

📖 Lessons

1 What is Statistics?

Introduction to statistics and its role in everyday life. Exploring data in Aotearoa contexts.

🎯 Focus: Understanding why data matters

2 Posing Good Questions

Learning to ask investigative questions that can be answered with data.

🎯 Focus: Problem phase of PPDAC

3 Planning Data Collection

Survey design, sampling methods, and ethical considerations.

🎯 Focus: Plan phase of PPDAC

4 Collecting Data

Conducting surveys, gathering existing data, recording accurately.

🎯 Focus: Data phase of PPDAC

5 Organising Data

Tables, tally charts, and using spreadsheets to organise data.

🎯 Focus: Preparing for analysis

6 Displaying Data

Bar graphs, pie charts, line graphs — choosing the right display.

🎯 Focus: Visual representation

7 Measures of Centre

Mean, median, and mode — what they tell us about data.

🎯 Focus: Analysis phase

8 Drawing Conclusions

Interpreting results and answering the original question.

🎯 Focus: Conclusion phase

9 Presenting Findings

Communicating statistical findings clearly and effectively.

🎯 Focus: Communication skills

10 Investigation Project

Complete independent investigation using the full PPDAC cycle.

🎯 Focus: Summative assessment

🇳🇿 Aotearoa Context Ideas

Investigation topics connected to Aotearoa:

  • 📱 Screen time and wellbeing among NZ youth
  • 🏠 Housing costs across different regions
  • 🐦 Native bird populations and conservation
  • 🌊 Beach clean-up data — types of rubbish collected
  • 🚌 School travel methods and sustainability
  • 🏉 Sports participation rates by gender
  • 🌿 Te reo Māori usage in homes
  • 📊 Stats NZ data about our communities

📎 Unit Resources

📄 PPDAC Planning Template 📋 Community Needs Survey 🏃 Sports Performance Data 🌧️ NIWA Climate Data Analysis 🎯 Investigation Brief & Rubric 📚 Curriculum Companion

📚 Research Base | Te Pūtake Rangahau

The unit applies two established approaches from Te Whare Ako:

📋 Kaiako Planning Snapshot

🎯 Ngā Whāinga Akoranga — Learning Intentions
  • Pose a statistical question, plan a data collection method, and carry out the investigation using the PPDAC cycle.
  • Represent and analyse data using appropriate graphs, identifying patterns and distributions.
  • Write evidence-based conclusions that directly answer the original statistical question.
✅ Paearu Angitu — Success Criteria
  • I can write a clear statistical question and explain how I will collect data to answer it fairly.
  • I can create a graph that appropriately represents my data and describe what it shows.
  • I can write a conclusion using statistical language that refers back to my evidence.
🧭 Teacher Planning Snapshot
  • Year level: Year 8 | Duration: 10 lessons | NZC Level 4 (Mathematics and Statistics — Statistical Literacy and Investigation)
  • Mātauranga Māori: "He aha te mea nui o te ao? He tangata, he tangata, he tangata." Statistical investigation in this unit centres on human stories and community contexts — not abstract datasets. Kaitiakitanga informs the ethical use of data: who collects it, who it represents, and what it is used for. Encourage investigations that draw on tāngata whenua community questions and position data as a taonga that must be handled with respect and accountability.
  • Entry support: Scaffolded PPDAC template. Begin with whole-class demonstration investigation. Pre-teach graph types with annotated examples. Pair-based data collection for entry-level students.
  • On-level: Students design and carry out an independent investigation, choose appropriate graph types, and write structured PPDAC conclusions.
  • Extension: Use secondary data sources (StatsNZ, iwi reports). Compare own findings to published data. Critically examine survey design and potential sampling bias.
♿ Inclusion and Accessibility
  • ESOL / ELL: Sentence frames for each PPDAC stage. Bilingual data collection tools where available. Visual graph-type selection guide.
  • Accessibility: Digital graphing alternatives (Desmos, Google Sheets). Oral conclusions accepted. Partner data entry support during collection phase.
  • Neurodiverse learners: Chunked PPDAC template with one stage per page. Visual checklist for investigation steps. Choice of investigation topic to maximise engagement and ownership.
📊 Assessment Framework

Formative Assessment

  • Lesson 1 (What is Statistics?): Can students distinguish between raw data and information, and give an example of how statistics tell stories about people in Aotearoa? Assessed through the data vs information sorting activity.
  • Lesson 2 (Posing Good Questions): Can students write a clear investigative question that meets the criteria — measurable, specific, and answerable with data they can collect? Assessed through the question-refinement peer review.
  • Lessons 3–4 (Planning & Collecting): Can students design an ethical, unbiased survey and collect data systematically using tally marks or spreadsheets? Assessed through the data collection plan and troubleshooting reflection.
  • Lessons 5–7 (Organising, Displaying, Measures of Centre): Can students clean and sort data, choose the correct graph type, and calculate mean, median, and mode appropriately? Assessed through the frequency table, graph accuracy check, and measures-of-centre problem set.

Summative Assessment

Statistical Investigation Project (built across Lessons 2–10): Students do the mathematics as they learn it. Every lesson produces one piece of the final evidence trail, and Lessons 8–10 turn that trail into a conclusion and presentation. Use the print-ready investigation brief and rubric.

  • Written Conclusion: A statement that directly answers the investigative question using evidence from the data, identifies limitations, and reflects on what they would change if repeating the investigation.
  • Investigation Presentation: A poster or slide deck that summarises the entire PPDAC journey — the question, plan, data collection process, visual displays, analysis, and conclusion — presented to an audience with the ability to answer questions about their methods.
🔗 Unit Progression & Next Steps

Students follow the PPDAC cycle (Problem, Plan, Data, Analysis, Conclusion) across 10 lessons, building from foundational concepts to independent investigation:

  • 📖 Lesson 1: What is Statistics? — Understand what statistics are, distinguish data from information, and explore how statistics tell stories about people in Aotearoa.
  • 📖 Lesson 2: Posing Good Questions — Learn the difference between survey and investigative questions; practise writing summary and comparison questions that can be answered with data.
  • 📖 Lesson 3: Planning Data Collection — Explore data collection methods (survey, experiment, observation), design unbiased questions, and plan ethical data collection.
  • 📖 Lesson 4: Collecting Data — Conduct data collection using tally marks and spreadsheets; troubleshoot real-time problems during the collection process.
  • 📖 Lesson 5: Organising Data — Clean data by removing errors, sort into categories, and build frequency tables to prepare for analysis.
  • 📖 Lesson 6: Displaying Data — Choose the correct graph type for different data, create accurate bar graphs, pie charts, or dot plots with proper titles, labels, and keys.
  • 📖 Lesson 7: Measures of Centre — Calculate mean, median, and mode; understand which measure suits different situations; analyse data range and spread.
  • 📖 Lesson 8: Drawing Conclusions — Interpret data to make evidence-based statements, write a conclusion that answers the investigative question, and identify limitations.
  • 📖 Lesson 9: Presenting Findings — Design a poster or slide deck summarising the investigation; communicate key findings visually to an audience.
  • 📖 Lesson 10: Investigation Project — Present the final statistical investigation, reflect on the PPDAC cycle, and demonstrate understanding of the full enquiry process.

Bridge: The PPDAC skills developed here transfer directly to any subject requiring evidence-based reasoning — from science experiments to social studies research projects — and prepare students for the more complex multivariate analyses at Year 9–10.

Pedagogical Foundations | Ngā Tūāpou Akoranga

Statistics is not arithmetic with error bars — it is a framework for making justified claims about an uncertain world. Three researchers explain why statistical inquiry requires more than calculation procedures.

Social Constructivism
Lev Vygotsky
Statistical thinking is inherently social: the class dataset is richer than any individual’s, and the interpretation discussion is where concepts form. Vygotsky’s Zone of Proximal Development explains why shared data analysis — students comparing, questioning, and challenging each other’s conclusions — produces deeper statistical understanding than individual calculation exercises.
Learning Science
Graham Nuthall
Nuthall’s research established that students need at least three independent encounters with a concept through different representations before it becomes long-term knowledge. For statistics, this means: a table of data, a graph of the same data, and a verbal description of the pattern — three forms, one encounter. This unit’s multi-representation sequences are not variety for variety’s sake; they are the three-encounter law applied to quantitative reasoning.
Progressive Education
John Dewey
Dewey’s argument that genuine learning requires real questions and real data — not textbook datasets about populations students have never met — explains why this unit asks students to investigate phenomena from their own communities. A survey of students’ own daily routines generates better statistical reasoning than national survey data precisely because students care about the answer.

→ Explore all theorists at Te Whare Ako — Teaching Theory