📝 Student Worksheet — Session 7: When Data Tricks You

Data Science for Young Minds · Grade 3 · Ages 8–9
📚 Part 1 — Vocabulary
Misleading
Truncated axis
Small sample
Biased question
Critical reader
Reliable data
🕵️ Part 2 — Spot the Trick

Each example below has a data trick. Name the trick and explain why it is a problem.

Example 1 — The Toothpaste Ad

"9 out of 10 dentists recommend SparkleBright toothpaste!" — The company surveyed 10 dentists who work in their own offices.

What type of trick is this?

Why is it a problem?

How would you fix it?

Example 2 — The Two Bars
Test Scores: Our School vs. Other Schools
Our school
88
Other schools
85
Y-axis starts at 83, not 0

What type of trick is this?

What does the chart make you think? What is actually true?

How would you fix it?

Example 3 — The Survey Question

Survey question: "Our new park is a wonderful improvement to the neighborhood, right?" Options: Agree / Strongly Agree.

What type of trick is this?

Why is it a problem?

Write a fair version of this question:

🔍 Part 3 — Apply the 3-Question Test

Apply the 3-question test to this data claim. Check ✅ or ❌ for each question, then decide: trustworthy or not?

Data claim: "In a survey of 5 students in our school, 4 said they prefer math over reading. That means 80% of students at our school prefer math!"
Q1: Does the scale start at 0? ☐ ✅ Yes   ☐ ❌ No   ☐ N/A
Q2: Was the sample large enough and fairly chosen? ☐ ✅ Yes   ☐ ❌ No
Q3: Was the question fair — not leading or biased? ☐ ✅ Yes   ☐ ❌ No   ☐ Can't tell

Overall: Is this data trustworthy? Why or why not?

✏️ Part 4 — Fix a Misleading Chart

This bar chart has a truncated axis. The y-axis starts at 40. Redraw the chart on the right with a correct axis starting at 0.

❌ Misleading chart (axis starts at 40)

Hours of Screen Time — Two Groups
Group A
45
Group B
42
Scale: 40 → 42 → 44 → 46

✅ Your honest redraw (start at 0)

Draw your corrected bar chart here

What looks different in your honest version?

✍️ Part 5 — Think About It

Can data be 100% accurate and still be misleading? Give an example.

What is one question you will always ask when you see a chart from now on?

Think about the data YOU collected in Sessions 3–5. Could anyone say YOUR data is misleading? Why or why not?

🏠 Take-Home Challenge — Myth Buster at Home!

Find one data claim in an ad, on a package, or on a screen this week. Apply the 3-question test!

The claim I found:

Where I found it:

Q1 — Scale starts at 0?   ☐ Yes   ☐ No   ☐ N/A
Q2 — Large, fair sample?   ☐ Yes   ☐ No   ☐ Can't tell
Q3 — Fair question?   ☐ Yes   ☐ No   ☐ Can't tell

Trustworthy or misleading? Why?

Data Science for Young Minds · Grade 3 · Session 7 Worksheet · sdabagh.github.io/learn/data-science