juniorLogistic Regression
What are the assumptions of Logistic Regression?
Updated May 17, 2026
Short answer
Logistic Regression assumes linearity in log-odds, independent observations, and low multicollinearity.
Deep explanation
The model assumes predictors relate linearly to log-odds. Features should not be highly correlated. Observations must be independent for reliable estimates.
Real-world example
Credit scoring models validate multicollinearity before deployment.
Common mistakes
- Ignoring correlated features.
Follow-up questions
- Does Logistic Regression require normality?
- What if assumptions fail?