Easy Missing Data Question 46 of 220

What is mean imputation?

Data Science track · Speak this in 60–90 seconds · Faridabad & Delhi NCR

PICTURE THIS: 1, 2, 2, 8

Mean3.25average

Median2middle

Mode2most often

Simple meaning

Mean imputation replaces missing numeric values with the column mean.

WHY — Missing Data instead of guessing?

Why interviewers care about Missing Data:

Missing Data questions separate

people who only read docs from people who shipped.

Keep it short, concrete,

and tied to Data Science work.

Stay structured

Name the idea, why it exists, then one short example.

Close cleanly

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:

1
Mean imputation replaces missing
numeric values with the column mean.
2
It is simple but
understates variance and can distort correlations, especially if many values are missing.
3
Use it only as
a baseline and prefer methods that respect the missingness mechanism when stakes are high.
4
Give an example
One tiny concrete case you can say aloud.
5
Common mistake
What juniors usually get wrong.
6
Close
When you pick this over the alternative.

EXAMPLE — See it in action

Here's a short line you can speak, broken into clear beats:

Say this line

“It is simple but understates variance and can distort correlations, especially i”

Break into beats

Itissimplebutunderstatesvariance

Speaking order

2987408337471632900

Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.

Key takeaway

Mean imputation replaces missing numeric values with the column mean. It is simple but understates variance and can distort correlations, especially if many values are missing.