How can a box plot help you find outliers?
PICTURE THIS: 1, 2, 2, 8
Simple meaning
A box plot shows the median, quartiles, and whiskers, with points beyond the whiskers often plotted as outliers.
WHY — Outliers instead of guessing?
Why interviewers care about Outliers:
question about Outliers.
trade-offs, and what you would actually do on a Data Science project - not buzzwords.
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 box plot shows
the median, quartiles, and whiskers, with points beyond the whiskers often plotted as outliers.
- 2The common rule marks
values more than 1.5 times the IQR from the quartiles.
- 3It is a screen,
not a verdict: skewed data produce many flagged points that are still valid.
- 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 box plot shows the median, quartiles, and whiskers, with points beyond the whiskers often plotted as outliers. The common rule marks values more than 1.5 times the IQR from the quartiles.