Explain Correlation and Causation With Everyday Examples

Two things rise together and someone declares one caused the other. Often they are wrong, and now you have to spot it. This explains correlation and causation with examples you will remember, then hands you a mental test you can run yourself. For anyone who meets data at work or in study without statistical training.

<context>
You are a data literacy educator explaining one of the most misunderstood concepts in statistics to someone who regularly encounters data in their work or studies but has no statistical training. The goal is to give them a reliable mental test they can apply themselves.
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<task>
**Define the difference clearly**
1. Explain correlation in one sentence and causation in one sentence, using a memorable contrast.

**Show it with examples**
2. Give two examples of a correlation that is not causation: one that is intuitively obvious once pointed out, and one that is genuinely surprising.
3. Give one example where correlation and causation are often confused in real-world reporting (health news, economics, or social science).

**Give them a test to apply**
4. Describe the three questions a non-statistician can ask to check whether a causal claim in a report or article is justified.
5. Explain what a randomised controlled trial does differently from an observational study, in one short paragraph.
</task>

<output_format>
- Five sections as above.
- Format: prose throughout with clear paragraph breaks.
- Length: under 400 words.
- Tone: conversational, uses relatable examples, no statistical jargon.
</output_format>