Choose Index below for a list of all words and phrases defined in this glossary.
Multicolinearity - Multicolinearity is the degree of correlation between Xs. It is an important consideration when using multiple regression on data that has been collected without the aid of a design of experiment (DOE). A high degree of multicolinearity produces unacceptable uncertainty (large variance) in regression coefficient estimates. Specifically, the coefficients can change drastically depending on which terms are in or out of the model and also the order they are placed in the model.
Use Ridge Regression or Partial Least Squares (PLS) Regression to get around these problems if DoE is not an option.
[Category=Data Quality ]
Source: iSixSigma, 04 February 2011 08:38:07, https:web.archive.org/web/20111109014246/http:www.isixsigma.com/index.php?option=com_glossary
Data Quality Glossary. A free resource from GRC Data Intelligence. For comments, questions or feedback: dqglossary@grcdi.nl