What is another word for multicollinearity?
Pronunciation: [mˌʌltɪkˌɒlɪnˈi͡əɹɪti] (IPA) 
Multicollinearity refers to the state where two or more predictor variables in a statistical model are highly correlated with each other. It can lead to biased and unstable results, making it important to avoid this issue in data analysis. Some synonyms for multicollinearity include collinearity, correlation, interdependence, co-linearity, confounding, and covariation. Other related terms include co-variance, association, dependence, and interrelatedness. By understanding these alternative terms, researchers can more effectively identify and address multicollinearity issues in their data analysis, leading to more accurate and reliable results.
