📋 Teacher Cheat Sheet — Session 6: What Does the Data Say?

Data Science for Young Minds · Grade 3 · Ages 8–9
~60 min Ages 8–9 Session 6 of 8 ND-Friendly
⏱ Session Agenda
TimeBlockWhat's Happening
0–5🔁 Warm-UpGallery walk — students look at each other's charts from Session 5
5–18📖 Lesson 1–2Reading charts step by step · Observation vs. inference
18–38🎮 ActivityChart Detectives — groups analyze 3 pre-made charts and write what the data says
38–50📖 Lesson 3–4Patterns and trends · Sentence frames: "The data shows…" "I notice…" "This might mean…"
50–56✍️ ActivityStudents write 3 statements about their own chart using sentence frames
56–58🔁 Recap"What is the difference between an observation and an inference?"
58–60👋 ClosePreview Session 7: "What if the chart is trying to trick you?"
Key insight to land: Reading a chart is a skill. You first say what you SEE (observation), then what you THINK it means (inference). Both matter — but they're different things.
📦 Materials Needed
Pencils Student worksheets Students' own charts from Session 5 (gallery walk) 3 pre-made chart posters or printed chart sheets (see below) Sticky notes (for gallery walk responses)
💡 Gallery Walk: post 4–6 student charts on the wall. Students walk around and write one observation on a sticky note for each chart. Takes 5–7 min and builds community.
📚 Key Vocabulary
Observation — what you can see directly in the data ("the tallest bar is…")
Inference — what you think the data means, using your reasoning ("this might mean…")
Pattern — something that repeats or stands out in the data
Trend — a direction the data moves (higher, lower, same)
Conclusion — what you decide based on what the data shows
Compare — looking at two or more values and noticing similarities or differences
💬 Discussion Questions + Teacher Notes
  • "Look at this chart. What do you SEE?"
    → Accept only observations: "The blue bar is the tallest." "Summer has 7." Redirect anything that starts explaining WHY — that's an inference. Keep this first pass factual only.
  • "What might EXPLAIN what you see?"
    → Now welcome inferences: "Maybe more kids have summer birthdays because…" Emphasize "might" — inferences need evidence to become conclusions.
  • "Is 'most kids prefer dogs' an observation or inference?"
    → Observation — if the chart shows dogs had the highest count, that IS directly visible. Vs. "people prefer dogs because they're friendlier than cats" — that's an inference (not in the data).
  • "Can a chart be wrong?"
    → The chart shows what the data says. If the data was collected badly (biased question, small sample, errors), the chart might be accurate but misleading. Sets up Session 7.
  • "What do you notice about the difference between the most popular and least popular answers?"
    → Teach "difference" as subtraction: "8 − 3 = 5 more people chose dogs than fish." Connects math to data literacy.
🎮 Chart Detectives — Sentence Frames
Post these sentence frames when students analyze charts. They scaffold both observation AND inference writing.
👁️ Observation frames (what you SEE):
"The most common _____ is _____."
"_____ people chose _____."
"The tallest bar is _____, which means _____."
"_____ and _____ have the same frequency."
🧠 Inference frames (what you THINK it means):
"This might mean that _____."
"I wonder if _____ because the data shows _____."
"Based on the data, I think _____."
💡 Laminate these and put one on each table group — students refer to them all year.
📊 Observation vs. Inference
Core distinction to teach clearly:
ObservationInference
From the chart directlyFrom your reasoning
"Dog has 8 votes""Kids prefer dogs"
Anyone can verify itCould be debated
Always true of the dataNeeds more evidence
Both are valuable! Observations are the evidence. Inferences are the thinking.
✍️ Wrap-Up Prompt
Write on board:
"What is one thing the data says for SURE, and one thing you THINK it might mean?"
5 min — write both sentences. Bridge to Session 7: "Next time we'll look at charts that LOOK true but might be trying to trick us!"
🧠 ND-Friendly Tips
  • Sentence frames — Critical for students who struggle to start writing. Don't just post them — walk through filling in one example together before releasing.
  • Gallery walk — Give a specific task (write one sticky per chart) rather than "look around." Reduces overwhelm and gives anxious students a clear purpose.
  • Observation vs. inference — Some students conflate these. Use physical gestures: point to the chart = observation; point to your brain = inference.
  • Celebrate specificity — "The dog bar is 8" is better than "dogs are popular." Praise precise language: "Great — you used the exact number!"
  • Pair share first — Let students tell a partner before writing. Verbal articulation often unlocks writing for language-hesitant students.
Data Science for Young Minds · Grade 3 · Session 6 Cheat Sheet · sdabagh.github.io/learn/data-science