Multivariate Analysis

Multivariate analysis is a branch of statistics that involves the observation and analysis of more than two statistical variables at a time. Unlike univariate or bivariate analysis, which examine variables in isolation or in pairs, multivariate techniques are designed to uncover the complex interrelationships, dependencies, and underlying structures within a dataset containing multiple measurements. These methods, which include techniques like multiple regression, principal component analysis (PCA), and cluster analysis, are crucial for modeling real-world phenomena where outcomes are typically influenced by numerous interconnected factors, allowing for more robust predictions, classifications, and hypothesis testing.