What assumptions does linear regression make, and how do you check and handle violations?
Anyone can recite 'linearity and normality.' Few can say which assumption matters for predictions versus inference, how to catch a violation in a residual plot, and what to actually do about it. Here is that answer.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Anyone can recite 'linearity and normality.' Few can say which assumption matters for predictions versus inference, how to catch a violation in a residual plot, and what to actually do about it. Here is that answer.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
