In epidemiology, researchers often deal with datasets containing numerous variables, such as genetic markers, environmental factors, and demographic information. PCA helps in reducing the dimensionality of such datasets, making it easier to identify underlying patterns and associations among variables. This is particularly useful for multivariate analysis and disease modeling.
