📋 Teacher Cheat Sheet — Session 2: Types of Data

Data Science for Young Minds · Grade 4 · Ages 9–10

~60 min Ages 9–10 Session 2 of 8 ND-Friendly

⏱ Session Agenda

Time	Block	What's Happening
0–5	🎯 Hook	"Which of these is different?" Show 4 data examples — 3 numerical, 1 categorical. Let students spot the odd one out.
5–20	📖 Lesson	Categorical vs. numerical · Discrete vs. continuous · Which graph type fits each
20–42	🎮 Activity	Data Sorting Challenge — 20 cards sorted into categorical / numerical / either
42–52	💬 Debrief	Gallery walk of sorted cards · Discuss disagreements · Graph matching
52–58	✍️ Write	Worksheet Part 3 — classify 10 variables, choose graph types
58–60	👋 Close	Exit ticket: "Name one categorical and one numerical variable from your own life."

Pacing note: Discrete vs. continuous is often confusing — don't rush it. Use "can it be a fraction?" as the quick test (you can't have 2.5 siblings, but you can have 2.5 hours of sleep).

📦 Materials Needed

Prepare before class:

20 data cards per group (printed or handwritten index cards) 3 label cards per group: CATEGORICAL / NUMERICAL / EITHER Blue marker + green marker per group (color-code) Worksheets Pencils

💡 Card examples: favorite color · height · number of pets · hair color · temperature · shoe size · test score · country of birth · hours of sleep · number of books

📚 Key Vocabulary

Categorical — data that names groups or labels (no math operations)

Numerical — data that is a number you can calculate with

Discrete — countable whole numbers only (0, 1, 2, 3…)

Continuous — can be any value including fractions (height, temperature)

Variable — any characteristic being measured or observed

💬 Discussion Questions + Teacher Notes

"What's the difference between 'eye color' and 'number of siblings'?"
→ Eye color names a group — you can't calculate the average eye color. Number of siblings is a count you can add, average, compare. This is the core categorical vs. numerical distinction.
"Can you have 2.5 siblings? Can you have 2.5 hours of sleep?"
→ No to siblings (discrete — whole people only). Yes to sleep (continuous — time can be any decimal value). This question reliably un-sticks confused students.
"Which graph would you use for eye color data? What about height data?"
→ Eye color → bar chart or pie chart (categories). Height → histogram or line plot (numerical range). The type of data determines the graph — this is the key rule students need to internalize.
"What about 'zip code' — is that categorical or numerical?"
→ Great edge case! Zip codes look numerical but they're categorical — you wouldn't average zip codes. This seeds the idea that "looks like a number" ≠ numerical data.
"Why does it matter what type of data you have?"
→ Wrong graph type = misleading or meaningless visualization. A bar chart of temperatures over time hides the trend that a line graph would show clearly.

🎮 Data Sorting Challenge — Setup Guide

Groups of 3–4. Each group gets 20 data cards and 3 label cards. Discuss and sort every card. Be ready to defend your choices.

20 Card Examples:

Categorical:
Favorite color · Hair color · Country of birth · Pet type · Favorite sport · Season born · Language spoken · T-shirt size (S/M/L) · School grade · Eye color

Numerical:
Height (cm) · Age (years) · Test score · Hours of sleep · Number of pets · Temperature (°F) · Distance to school · Number of books read · Weight (kg) · Pulse rate

Edge cases to discuss: Zip code (looks numerical, is categorical) · Shoe size (discrete numerical) · Star rating 1–5 (ordinal — either is acceptable)

Key debrief question: "Did any card cause a disagreement in your group? How did you resolve it?"

🎯 Opening Hook

Write 4 items on board: Blue · Green · Red · 42

"Which one is different and why?"

Accept all answers. Then reveal: the first three are colors (categories), 42 is a number. You can't average the colors — but you can work with 42. This launches categorical vs. numerical.

📊 Graph Type Reference

Categorical data →
Bar chart · Pie/circle chart · Pictograph

Numerical (discrete) →
Bar chart · Line plot · Dot plot

Numerical (continuous) →
Line graph · Histogram · Scatter plot

Post this on board — leave it up for Sessions 3–8.

🧠 ND-Friendly Tips

Color code the two types — Blue = categorical throughout the session. Green = numerical. Use this consistently on cards, board, worksheet.
Provide one clear example of each first — "Eye color = categorical. Height = numerical. Now you sort the rest."
The "can you average it?" test — Post as a visible rule: "If you can calculate the average, it's probably numerical."
Allow "either" as a valid answer — Some data genuinely straddles both types. Accepting uncertainty reduces anxiety.
Defend your sort — Require one sentence of reasoning per card in the debrief. This externalizes thinking.