Statistical Reasoning Seminar · Lesson 3: Planning Data Collection

Lesson 3: Planning Data Collection — free unit plan for New Zealand teachers and students. Part of the Te Kete Ako curriculum resource collection.

Statistical Reasoning Seminar · Lesson 3

Seminar focus: decide whether a plan deserves trust

Ākonga deliberate over competing sampling and survey plans for the same question. They must identify who may be excluded, how bias could enter, and which data-care condition is non-negotiable.

Other teaching approach: Community Data Inquiry Studio →

🎯 Learning Intentions

  • Understand different data collection methods (survey, experiment, observation)
  • Design clear survey questions to avoid bias
  • Plan for ethical data collection

🎥 Media Anchor (8 mins)

Video: Research Skills for Students

  • Which data collection method best matches your investigation question?
  • How will your plan improve reliability and fairness of results?

1. Discussion: How do we get answers? (10 mins)

Brainstorm ways to get data:

  • Survey: Asking people questions (e.g., opinions, habits)
  • Observation: Watching and counting (e.g., cars passing by, birds in garden)
  • Experiment: Testing something (e.g., how far paper planes fly)
  • Existing Data: Using internet research (e.g., Stats NZ data)

2. Concept: Bias and Fairness (15 mins)

What is bias? When data doesn't tell the whole truth.

  • Question Bias: "Don't you agree that rugby is the best?" (Leading question)
  • Sampling Bias: Asking only your friends about school issues.

Activity: "Fix the Bias." Students correct biased survey questions.

3. Task: Design Your Plan (20 mins)

Students create a plan for their investigation:

  1. Question: (Using I-V-G from Lesson 2)
  2. Method: Survey? Observation? Experiment?
  3. Tools: Paper survey? Google Form? Tally chart?
  4. Who/What: Who will you ask? Where will you observe?

4. Ethics Check (5 mins)

Is your plan creating harm?

  • Permission: Do people know you are collecting data?
  • Privacy: Are you asking overly personal questions?
  • Respect: Are you being culturally safe?
← Previous Lesson Next Lesson: Collecting Data →

📋 Teacher Planning Snapshot

Ngā Whāinga Ako — Learning Intentions

The class debates sampling on one shared scenario, including who a method silently excludes.

Ngā Paearu Angitū — Success Criteria

  • ✅ I can explain how a sampling method could bias a result.
  • ✅ I can argue for one method over another using stated criteria.

Differentiation & Inclusion

Scaffold support: One shared scenario with the sampling frame supplied, so debate focuses on consequences. Extension: cost two methods against accuracy.

ELL / ESOL: Teach 'bias', 'representative', 'frame' as things you can point to in the scenario.

Inclusion: Ākonga who find open debate hard can be assigned the sceptic role with a written brief.

Mātauranga Māori lens: Who is counted, and who is left out of a count, is not a technical detail — it is the whole basis on which a community can act on the result.

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.