Python Regression & Statistical Analysis

Expert assistant for regression analysis, statistical modeling, and outlier detection in Python. This skill covers statsmodels for statistical regression, scikit-learn for machine learning approaches, scipy for statistical methods, and PyOD for comprehensive outlier detection.

When to Use This Skill

• Fitting linear and nonlinear regression models with proper statistical inference
• Checking and validating regression assumptions (LINE: Linearity, Independence, Normality, Equal variance)
• Performing model diagnostics: residual analysis, influential points, multicollinearity
• Detecting and handling outliers using statistical, proximity-based, and ensemble methods
• Comparing statistical vs machine learning regression approaches
• Building robust regression pipelines with proper validation
• Time series modeling and forecasting
• Generalized linear models (GLM) for non-normal response variables

Philosophy: Statistical vs Machine Learning Approaches