📝 Student Worksheet — Session 6: Correlation vs. Causation

Data Science for Young Minds · Grade 5 · Ages 10–11

Name

Date

Class Period

📚 Part 1 — Vocabulary

Correlation

Causation

Positive Correlation

Negative Correlation

Confounding Variable

Spurious Correlation

🔗 Part 2 — Correlation or Causation?

For each statement, circle C = Correlation or CA = Causation, then briefly explain your reasoning.

Statement	Circle one	Your reasoning
Students who eat breakfast tend to get higher test scores.	C CA
Smoking causes lung cancer (supported by many controlled studies).	C CA
Countries with more TVs per person have higher life expectancy.	C CA
Watering a plant makes it grow taller (in a controlled experiment).	C CA
Nicolas Cage movie releases correlate with pool drownings.	C CA
Children with bigger shoe sizes read better.	C CA

🕵️ Part 3 — Spurious Correlation Detective

For each spurious correlation below, fill in all three boxes.

Case 1: Ice cream sales go up → drowning rates go up

The correlation:

The hidden confound:

Honest headline:

Case 2: Children with bigger shoe sizes are better readers

The correlation:

The hidden confound:

Honest headline:

Case 3 (Challenge): More hospitals in an area → more deaths in that area

Why this looks suspicious:

The real explanation:

Should we close hospitals? Why/why not?

✍️ Part 4 — C-E-R Argument Writing

Scenario: A researcher finds that cities with more coffee shops have lower rates of heart disease. A newspaper headline reads: "Coffee Shops Prevent Heart Disease, New Study Finds!"

Write a C-E-R argument explaining whether the headline is justified.

CLAIM — What do you think is actually true?

EVIDENCE — What data or facts support your claim?

REASONING — How does the evidence connect to your claim? What confound might explain it?

💡 Part 5 — Real-World Stakes

1. A study finds that students who attend tutoring programs score higher on math tests. A school decides to make tutoring mandatory for all struggling students. What questions should you ask before concluding tutoring causes better scores?

2. Why is it dangerous to make policies based on spurious correlations? Give one real example of harm that could result.

3. What is one question you can always ask to test whether a correlation might actually be causation?

🏠 Take-Home Challenge — Correlation Hunter

Find one example of a correlation claim in real life (news, social media, a teacher/parent statement, advertisement, etc.).

☐ Source: ___________________________________________

☐ What two things are said to be correlated?

☐ Does the source claim causation? (Yes / No / Unclear)

☐ Can you think of a confounding variable that might explain it?

My analysis: