This article provides a method of interpreting a surprising inequality in multiple linear regression: the squared multiple correlation can be greater than the sum of the simple squared correlations between the response variable and each of the predictor variables. The interpretation is obtained via principal component analysis by studying the influence of some components with small variance on the response variable. One example is used as an illustration and some conclusions are derived.
No takes yet. Share an insight, caveat, or question.
Carles M. Cuadras (1993) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: