Seminar focus: critique how a graph frames the story
Compare accurate, incomplete, and misleading displays of the same data. Ākonga identify how graph type, scale, labels, and visual emphasis influence interpretation, then defend the fairest representation.
- Seminar move: Gallery critique using accuracy, clarity, and framing criteria
- Seminar outcome: A graph-choice judgement backed by visible evidence
🎯 Learning Intentions
- Choose the correct graph type for different data types
- Create accurate bar graphs, pie charts, or dot plots
- Ensure all graphs have titles, labels, and keys
🎥 Media Anchor (8 mins)
Video: Poster Design Principles
- Which graph type communicates your data most clearly and why?
- What design choice could accidentally mislead your audience?
1. Graph Matching (10 mins)
Match the data type to the graph:
- Category Data (e.g., fav colour) → Bar Graph (counts) or Pie Chart (percentages)
- Numerical Data (e.g., height) → Dot Plot or Histogram/Stem & Leaf
- Time Data (e.g., temperature over week) → Line Graph
2. Bad Graphs (10 mins)
Show examples of misleading graphs (e.g., scale not starting at zero, missing labels).
Rules for Good Graphs:
- Title - What is this about?
- Axes - Label X and Y clearly.
- Intervals - Consistent counting steps.
- Labels - What do the bars represent?
Acronym: TAIL
3. Task: Create Your Display (30 mins)
Students create at least one graph for their investigation.
Options:
- Draw by hand on graph paper (focus on precision).
- Use Google Sheets/Excel to generate a chart.
Challenge: Write one sentence below the graph describing what the "tallest bar" or "biggest slice" means.
📋 Teacher Planning Snapshot
Ngā Whāinga Ako — Learning Intentions
Ākonga compare competing displays of the same shared data and expose how one misleads.
Ngā Paearu Angitū — Success Criteria
- ✅ I can identify the specific feature that makes a display misleading.
- ✅ I can argue which display best serves a stated purpose.
Differentiation & Inclusion
Scaffold support: Three displays of one dataset, one of which misleads. Extension: find a misleading display in real media and diagnose it.
ELL / ESOL: Name the axis, the scale and the baseline aloud together before critiquing.
Inclusion: Diagnosing a misleading display is accessible to ākonga who are not yet fluent in constructing one.
Mātauranga Māori lens: A display is an argument about what matters. Ask ākonga whose interests each display serves.
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.