What is correlation?
PICTURE THIS: HOW TO EXPLAIN IT
Simple meaning
Correlation measures how two variables move together, often with Pearson's r for linear association.
WHY — Correlation vs Causation instead of guessing?
Why interviewers care about Correlation vs Causation:
separate people who only read docs from people who shipped.
and tied to Data Science work.
Name the idea, why it exists, then one short example.
End with when you use it and one common pitfall.
STEPS — What happens step by step?
Before you speak the answer, walk the interviewer through these steps:
- 1Correlation measures how two
variables move together, often with Pearson's r for linear association.
- 2A value near 1
or -1 is a strong linear link
- 3near 0 is little
linear link.
- 4Correlation is symmetric and
does not tell you which variable, if either, causes the other.
- 5Common mistake
What juniors usually get wrong.
- 6Close
When you pick this over the alternative.
EXAMPLE — See it in action
Here's a short line you can speak, broken into clear beats:
Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.
Key takeaway
Correlation measures how two variables move together, often with Pearson's r for linear association. A value near 1 or -1 is a strong linear link