Correlation
🟦📊 Technique Card: Understanding Correlation (deeper)
💡 What Is Correlation?
Correlation is when two things seem to change in a connected way.
- If one thing changes, and another changes with it, we say there is a correlation.
- It helps us spot patterns and ask smart questions like:
➤ "Do people who revise more score higher?"
➤ "Does screen time affect sleep?"
🔄 The Three Types of Correlation
| Type | What Happens | Easy Example |
|---|---|---|
| ✅ Positive Correlation | When one thing goes up, the other goes up too (or both go down together). | More hours revising = Higher test scores |
| ❌ Negative Correlation | When one thing goes up, the other goes down. | More time watching TV = Less sleep |
| ❓ No Correlation | The two things don’t change together in any clear way. | Shoe size vs test scores |
📊 Why Is This Useful?
- 🔍 Helps us spot patterns in data — like "Which habits help learning?"
- 🧠 Makes us curious to explore relationships between things.
- 🗣️ Gives us something to say in a report or presentation:
"Our data shows a strong positive correlation between exercise and concentration!"
❗ But remember: Correlation is not causation.
Just because two things go together doesn’t mean one causes the other!
⚠️ Correlation Is Not the Same as Causation!
Just because two things change together (correlation), that doesn't mean one causes the other (causation).
🧩 Here's the Difference:
| Term | What It Means | Example |
|---|---|---|
| Correlation | Two things move together | Children who wear bigger shoes tend to have better handwriting. |
| Causation | One thing directly affects the other | Practising handwriting improves neatness. |
The shoe-handwriting example is correlation — but not causation. Older children have bigger feet and neater handwriting because they’re older — age causes both, but the shoe size isn’t the reason their writing improves!
🧠 A Good Way to Think About It
Correlation is like spotting a pattern.
Causation is knowing the reason behind it.
Just seeing a link isn’t enough. We need to think deeper:
- Could something else be causing both?
- Is it just a coincidence?
- Can we test it?
🕵️ Why This Matters
If we mistake correlation for causation, we might:
- Make bad decisions
- Spread false ideas
- Miss what’s really going on
So always ask:
"Does this cause that?" Or are they just happening together?"
🛠 Where You'll Use This
- In science: “Does watering plants more often help them grow faster?”
- In geography: “Do countries with more forests have cleaner air?”
- In school projects: “Do children who eat breakfast perform better on tests?”
- In digital changemaker work: exploring data to spot social or environmental issues.
🧪 Try It Out!
Using a scatter graph:
- Plot the data
- Look at the dots:
➤ Do they go up together (↗)?
➤ Does one go up as the other goes down (↘)?
➤ Or are they scattered randomly (• • •)?
Then decide:
Positive? Negative? Or No Correlation?