What is a p-value in plain language?
PICTURE THIS: 1, 2, 2, 8
Simple meaning
A p-value is the probability, under the null hypothesis, of seeing a result at least as extreme as the one you observed.
WHY — P-value instead of guessing?
Why interviewers care about P-value:
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:
- 1A p-value is the
probability, under the null hypothesis, of seeing a result at least as extreme as the one you observed.
- 2It is not the
probability that the null is true, and it is not the probability that the result was caused by chance in a vague sense.
- 3Small p-values mean the
data are surprising if the null is true.
- 4Give an example
One tiny concrete case you can say aloud.
- 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
A p-value is the probability, under the null hypothesis, of seeing a result at least as extreme as the one you observed. It is not the probability that the null is true, and it is not the probability that the result was caused by chance in a vague sense.