Correlation Analysis

Overview

Correlation analysis measures the strength and direction of relationships between variables, helping identify which features are related and detect multicollinearity.

When to Use

• Identifying relationships between numerical variables
• Detecting multicollinearity before regression modeling
• Exploratory data analysis to understand feature dependencies
• Feature selection and dimensionality reduction
• Validating assumptions about variable relationships
• Comparing linear and non-linear associations

Correlation Types

• Pearson: Linear correlation (continuous variables)
• Spearman: Rank-based correlation (ordinal/non-linear)