Which method is most appropriate for imputing missing values in a numerical feature with significant outliers?

Question

Data Science — Easy

Which method is most appropriate for imputing missing values in a numerical feature with significant outliers?

Accepted Answer

Median imputation is robust to outliers because the median represents the middle value of a dataset, whereas the mean is highly sensitive to extreme values. Using the mean in the presence of outliers would shift the imputed value toward the extreme, introducing bias. Options C and D are not standard imputation techniques for missing data.