Handling Missing Data

Summary

Deciding whether to drop, impute, or flag missing values — the right choice depends on why the data is missing and how a model would react to each option, not a single universal rule.

• 1Learn the difference between data missing at random versus missing systematically.
• 2Practice both dropping and imputing (mean/median/mode) missing values on the same dataset.
• 3Learn how tree-based models handle missing values differently from linear models.