a linear multivariate ordination technique that determines a reduced set of coordinate axes.

A type of factor analysis.

(1) a method of factoring a correlation matrix directly, without estimating communalities. Linear combinations of variables are estimated which explain the maximum amount of variance in the variables. The first component accounts for the most variance in the variables. Then the second component accounts for the most variance in the variables residualized for the first component, and so on. (2) transforms a collection of measured variables into a set of orthogonal maximum variance linear combinations.

Regression analysis to determine from a set of independent variables (predictors) those contributing most to the explained variance. See regression.

In statistics, principal components analysis (PCA) is a technique for simplifying a dataset, by reducing multidimensional datasets to lower dimensions for analysis."Principal component analysis is a method often used for reducing multidimensional datasets to lower dimensions for analysis." http://energycommerce.house.gov/108/home/07142006_Wegman_Report.pdf